Patent Publication Number: US-11023664-B2

Title: Persisting annotations applied to an electronic hosted whiteboard

Description:
BACKGROUND 
     The present invention relates to web conferencing, and more specifically, to presentations presented in a web conference. 
     Web conferencing is a popular means of collaboration among people. By leveraging use of a virtual white board, which is real time collaboration tool that may be hosted in a web conference, a presenter can convey visual information to an audience, for example text, images, etc. In addition, the presenter and/or other people collaborating in the web conference can add annotations to the virtual white board to share those annotations with other participants of the web conference. Thus, using a web conference with a hosted virtual white board, participants no longer need to all be present in the same physical meeting room in order to collaborate and share visual information. 
     SUMMARY 
     A method includes receiving a plurality of annotations for a presentation presented in a web conference. The method also can include assigning to each of the plurality of annotations a respective relevance parameter, wherein each relevance parameter indicates a relevance of a respective one of the plurality of annotations to a portion of the presentation to which the annotation pertains. The method also can include generating, using a processor, for each of the annotations, a decay model based on the respective relevance parameter, wherein the decay model indicates different durations of time the annotation is to be visible to different participants participating in the web conference based on respective expertise levels of the participants. The method also can include presenting each respective annotation with the presentation in accordance with the decay model generated for the respective annotation. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram illustrating an example of a network computing environment. 
         FIG. 2  depicts an example view of a virtual white board in which a presentation is presented during a web conference. 
         FIG. 3  depicts a data table in which feedback for annotations may be stored. 
         FIG. 4  depicts a chart presenting a plurality of annotation decay models for various annotations. 
         FIG. 5  is a flow chart illustrating an example of a method of present annotations with a presentation in accordance with decay models generated for the respective annotations. 
         FIG. 6  is a block diagram illustrating example architecture for a server configured to host a web conference. 
         FIG. 7  is a block diagram illustrating example architecture for a client device. 
     
    
    
     DETAILED DESCRIPTION 
     The present invention relates to web conferencing, and more specifically, to presentations presented in a web conference. 
     In accordance with the inventive arrangements disclosed herein, a presentation can be presented to a plurality of participants participating in a web conference. One or more participants in the web conference can contribute annotations to the presentation, and a system hosting the web conference can receive the annotations. The system can assign to each annotation a respective relevance parameter. Each relevance parameter can indicate a relevance of a respective annotation to a portion of the presentation to which the annotation pertains. 
     Based on the relevance parameter, the system can, for each annotation, generate a decay model. The decay model for each annotation can control the availability of the annotation to be visible to respective participants participating in the web conference. For example, the decay model can indicate different durations of time the annotation is to be visible to different participants participating in the web conference based on respective expertise levels of the participants. Each annotation can be presented with the presentation in accordance with the decay model generated for the respective annotation. Various other operations also can be performed based on the relevance parameters. 
     Several definitions that apply throughout this document now will be presented. 
     As defined herein, the term “web conference” means a real time communication session in which a plurality of participants are displayed the same view (e.g., a virtual white board) on their client devices and in which two or more of the plurality of participants may contribute annotations to a presentation presented in the displayed view. 
     As defined herein, the term “presentation” means text, images, video, audio and/or the like presented in a web conference. 
     As defined herein, the term “virtual white board” means an interactive view hosted in a web conference in which a presentation is presented and in which two or more participants of the web conference may provide, in real time, annotations related to the presentation. 
     As defined herein, the term “annotation” means text contributed by a participant in a web conference to a presentation presented in the web conference. An annotation may contribute additional material to the presentation, provide comments on the presentation, ask questions regarding the presentation, or the like. 
     As defined herein, the term “feedback” means information obtained from a participant in a web conference pertaining to an annotation contributed to a web conference. 
     As defined herein, the term “ranking” means a value assigned to an annotation in feedback or based on feedback. 
     As defined herein, the term “relevance parameter” means a value assigned to an annotation that indicates a relevance of the annotation to a portion of a presentation to which the annotation pertains. 
     As defined herein, the term “decay model” means a functional data structure specifying parameters used to determine one or more time frames in which an annotation is to be presented to respective participants participating in a web conference or respective users viewing the web conference. 
     As defined herein, the term “client device” means a processing system including at least one processor and memory that requests shared services from a server, and with which a user directly interacts. Examples of a client device include, but are not limited to, a workstation, a desktop computer, a mobile computer, a laptop computer, a netbook computer, a tablet computer, a smart phone, a personal digital assistant, a smart watch, smart glasses, a gaming device, a set-top box, a smart television and the like. Network infrastructure, such as routers, firewalls, switches, access points and the like, are not client devices as the term “client device” is defined herein. 
     As defined herein, the term “server” means at least one processing system including at least one processor and memory that hosts shared services and provides the shared services to a plurality of client devices. 
     As defined herein, the term “processor” means at least one hardware circuit (e.g., an integrated circuit) configured to carry out instructions contained in program code. Examples of a processor include, but are not limited to, a central processing unit (CPU), an array processor, a vector processor, a digital signal processor (DSP), a field-programmable gate array (FPGA), a programmable logic array (PLA), an application specific integrated circuit (ASIC), programmable logic circuitry, and a controller. 
     As defined herein, the term “computer readable storage medium” means a storage medium that contains or stores program code for use by or in connection with an instruction execution system, apparatus, or device. As defined herein, a “computer readable storage medium” is not a transitory, propagating signal per se. 
     As defined herein, the term “responsive to” means responding or reacting readily to an action or event. Thus, if a second action is performed “responsive to” a first action, there is a causal relationship between an occurrence of the first action and an occurrence of the second action, and the term “responsive to” indicates such causal relationship. 
     As defined herein, the term “real time” means a level of processing responsiveness that a user or system senses as sufficiently immediate for a particular process or determination to be made, or that enables the processor to keep up with some external process. 
     As defined herein, the term “automatically” means without user intervention. 
     As defined herein, the term “participant” means a person (i.e., a human being) participating in a web conference. 
     As defined herein, the term “presenter” means a person (i.e., a human being) that presents in a presentation in a web conference. 
     As defined herein, the term “user” means a person (i.e., a human being). A user may be a participant in a web conference, or a user who is not a participant in the web conference but who later views the web conference. 
       FIG. 1  is a block diagram illustrating an example of a network computing environment  100 . The network computing environment  100  can include a server  110  and a plurality of client devices  120 ,  122 ,  124 ,  126 . The client devices  120 - 126  can be communicatively linked to the server  110  via a communication network  105 . The communication network  105  is the medium used to provide communications links between various devices and data processing systems connected together within the network computing environment  100 . The communication network  105  may include connections, such as wire, wireless communication links, or fiber optic cables. The communication network  105  can be implemented as, or include, any of a variety of different communication technologies such as a local area network (LAN), a wide area network (WAN), a wireless network, a mobile network, a Virtual Private Network (VPN), the Internet, the Public Switched Telephone Network (PSTN), or the like. 
     The server  110  can execute a web conferencing application  112  configured to host a web conference in which participants  130 ,  132 ,  134 ,  136  participate using client devices  120 - 126 . In this regard, each client device  120 - 126  can execute a respective web conferencing client  140 ,  142 ,  144 ,  146  via which the participants  130 - 136  participate in the web conference. The web conferencing clients  140 - 146  can be web browsers or other applications specifically configured for web conferencing. 
     At least one participant, for example the participant  130 , can provide a presentation  150  in the web conference that is presented to each of the participants  130 - 136 . For example, the participant  130  can use the web conferencing client  140  to provide the presentation  150  on a virtual white board hosted by the web conferencing application  112 . The web conferencing application  112  also can present virtual white board, with the presentation  150 , to the other participants  132 - 136 . 
     While the presentation  150  is presented, one or more participants  130 - 136  can provide annotations to the presentation  150  by interacting with their respective web conferencing clients  140 - 146 . For example, via the web conferencing client  142 , the participant  132  can provide the annotation  160  on the virtual white board or in another view hosted by the web conferencing application  112 . The participant  134  also can generate an annotation  162  in a similar manner using the web conferencing client  144 . 
     In response to receiving each annotation  160 ,  162  from a respective web conferencing client  140 - 146 , the web conferencing application  112  can store the annotation  160 ,  162  to a computer readable storage medium in a manner that associates the annotation  160 ,  162  with the presentation  150  and the particular portion of the presentation (e.g., page, slide, etc.) for which the annotation is generated. For instance, the web conferencing application  112  can store the annotations  160 ,  162  to a database contained on the computer readable storage medium. The web conferencing application  112  also can present the annotations  160 ,  162  to one or more of the participants  130 - 136 , for example by presenting the annotations  160 ,  162  on the virtual white board on which the portion of the presentation  150  to which the annotation  160 ,  162  pertains is presented, or by presenting the annotations  160 ,  162  in another view. 
     The participants  130 - 136  also can use the web conferencing clients  140 - 146  to provide feedback relating to the annotations  160 ,  162 . For instance, in response to the annotation  160  being presented to the participants  130 - 136 , one or more of the participants  130 - 136  can provide respective feedback  170 ,  172 ,  174 ,  176  relating to the annotation  160 . Similarly, response to the annotation  162  being presented to the participants  130 - 136 , one or more of the participants  130 - 136  can provide respective feedback  170 - 176  relating to the annotation  160 . The participants  130 - 136  can generate the feedback  170 - 176  by interacting with one or more menus presented by their respective web conferencing clients  140 - 146 . In response to receiving participant inputs to create the feedback  170 - 176 , the respective web conferencing clients  140 - 146  can communicate the feedback  170 - 176  to the web conferencing application  112 . 
     Each particular feedback  170 - 176  can include a first value indicating a rating assigned to the respective annotation  160  participant  130 - 136  providing the feedback  170 - 176  and a second value indicating an expertise level of the participant  130 - 136  providing the feedback  170 - 176 . In illustration, the feedback  174  can include a value indicating a rating the participant  134  assigns to the annotation  160  and a value indicating the expertise level of the participant  134  in the subject matter to which the annotation  160  pertains, for example the subject matter of a particular portion of the presentation for which the annotation is provided and/or the subject matter of the annotation itself. In one arrangement, the participant  134  can enter his or her expertise level using the web conferencing client  144 , or web conferencing client  144  can access and process a user profile of the participant  134  to determine the expertise level. In another arrangement, the feedback  174 , when sent by the web conferencing client  144  need only include the value indicating the rating, and the web conferencing application  112  can append to the feedback  174  the expertise level of the participant. For instance, the web conferencing application  112  can access and process a user profile of the participant  134  to determine the expertise level. 
     For each feedback  170 - 176 , the first value can be any value within a range of values suitable for rating the annotation  160 , for example within a range between zero and ten, with zero representing a low rating and ten representing a high rating. Similarly, the second value can be any value within a range of values suitable for indicating the expertise level of the participant  134 , for example within a range between zero and ten, with zero representing no expertise and ten representing a very high level of expertise. The present arrangements, however, are not limited to these examples. The web conferencing application  112  can process the feedback  170 - 176  received for each annotation  160 ,  162 , and assign a ranking  180 ,  182  to each of the respective annotations  160 ,  162  accordingly, as will be described. 
     For each annotation  160 ,  162 , the web conferencing application  112  also can process the content of the annotation  160 ,  162  and the content of the portion of the presentation  150  to which the annotation  160 ,  162  pertains using natural language processing (NLP), semantic analysis and regression analysis on the respective content to determine a level of correlation between the annotation  160 ,  162  and the presentation  150 . For example, the web conferencing application  112  can apply NLP and semantic analysis to identify concepts contained in the annotation  160  and identify concepts contained in the portion of the presentation  150  for which the annotation  160  is generated. The web conferencing application  112  can apply regression analysis to results of the NLP and semantic analysis to determine the level of correlation between the annotation  160  and the portion of the presentation  150 . The web conferencing application  112  can calculate the relevance parameter  190  based on such level of correlation. The web conferencing application also can calculate a relevance parameter  192  for the annotation  162  in a similar manner. 
     The higher the level of correlation between the annotation  160  and the portion of the presentation  150  to which the annotation  160  applies, the higher the relevance parameter  190  will be. Conversely, the lower the level of correlation between the annotation  160  and the portion of the presentation, the lower the relevance parameter  190  will be. By way of example, if the portion of the presentation  150  to which the annotation  160  applies includes text pertaining to fitting a curve to data points, and the annotation  160  includes text asking about distances between a data point and the curve, the relevance parameter assigned to annotation  160  can be relatively high (e.g., closer to a value of 1 than to 0). On the other hand, if the annotation  160  includes text in the nature of “I am having difficulty understanding this concept,” the relevance parameter assigned to annotation  160  can be relatively low (e.g., closer to a value of 0 than to 1). 
     Based on the respective relevance parameters  190 ,  192 , the web conferencing application  112  can selectively present the annotations  160 ,  162  to different participants  130 - 136  for differing amounts of time, for example using decay models, which will be described. The web conferencing application  112  also can determine where on virtual white board the annotations  160 ,  162  are presented based on the respective relevance parameters  190 ,  192 , as well as perform other processes, which will be described in greater detail. 
     At this point it should be noted that NLP is a field of computer science, artificial intelligence and linguistics which implements computer processes to facilitate interactions between computer systems and human (natural) languages. NLP enables computers to derive computer-understandable meaning from natural language input. The International Organization for Standardization (ISO) publishes standards for NLP, one such standard being ISO/TC37/SC4. Semantic analysis is the implementation of computer processes to generate computer-understandable representations of natural language expressions. Semantic analysis can be used to construct meaning representations, semantic underspecification, anaphora resolution, presupposition projection and quantifier scope resolution, which are known in the art. Semantic analysis is frequently used with NLP to derive computer-understandable meaning from natural language input. An unstructured information management architecture (UIMA), which is an industry standard for content analytics, may be used by the web conferencing application  112  to implement NLP and semantic analysis. Regression analysis also is known to those of ordinary skill in the art. Various types of regression analysis that may be used in the present arrangements include, but are not limited to, statistical regression, linear regression, parametric regression, Poisson regression, logistic regression, generalized regression, and the like. 
       FIG. 2  depicts an example view of a virtual white board  200  in which a presentation  150  is presented during a web conference. The virtual white board  200  can be presented on the respective client devices  120 - 136  by the respective web conferencing clients  140 - 146 . As noted, while the presentation  150  is presented, one or more participants  130 - 136  may provide annotations  160 ,  162  for the presentation  150 , and one or more of the participants also may provide feedback  170 - 176  regarding the annotations  160 ,  162 . To provide feedback  174  for an annotation  160 , the participant  134  can select the annotation  160  using a cursor  210  and initiate the web conferencing client  144  to present a menu  220 , for example by right-clicking on the annotation  160 . From the menu  220 , the participant  134  can select a value  230  to assign a rank to the annotation  160 . For instance, the participant can select a radio button or the like presented next to a desired value. Optionally, the menu  220  also can prompt the participant to enter a value indicating the participant&#39;s level of expertise in the subject matter of the presentation, for example the portion of the presentation for which the annotation  160  is generated. As noted, in anther arrangement such value can be obtained by accessing and processing the participant&#39;s user profile. 
     The web conferencing application  112  can generate the rankings  180 ,  182  based on feedback  170 - 176  received from one or more of the participants  130 - 136 , as will be described. Further, the web conferencing application  112  can display the rankings  180 ,  182  with the respective annotations  160 ,  162 . For instance, the web conferencing application  112  can display the rankings  180 ,  182  immediately above, below or next to the respective annotations  160 ,  162 . In one arrangement, the web conferencing application  112  can display the rankings  180 ,  182  only to the participant  130  who is the presenter of the presentation  150 . In another arrangement, the web conferencing application  112  can display the rankings  180 ,  182  to selected participants  130 - 136 , for example participants  130 - 136  having a threshold level of expertise in the subject matter of the presentation. In yet another arrangement, the web conferencing application  112  can display the rankings  180 ,  182  to all of the participants  130 - 136 . 
     Also, locations in the virtual white board  200  where the annotations  160 ,  162  are placed can be determined based on the respective relevance parameters  190 ,  192  assigned to each respective annotation  160 ,  162 . The annotation  160 ,  162  having the highest relevance parameter  190 ,  192  can be can be placed closest to the portion (e.g., text or image) of the presentation  150  to which the annotation  160 ,  162  pertains, while annotations  160 ,  162  having lower relevance parameters  190 ,  192  can be placed further away from that portion of the presentation. For instance, if there are three annotations  160 ,  162  each pertaining to the same portion of the presentation  150 , the annotation  160 ,  162  with the lowest relevance parameter  190 ,  192  can be placed furthest away from that portion of the presentation  150  in comparison to the other annotations  160 ,  162 . 
     Moreover, the length of time each annotation  160 ,  162  remains displayed for each particular participant  130 - 136  can be different. Each length of time can be determined based on the relevance parameter assigned to the respective annotation  160 ,  162 , and the level of expertise of the particular participant  130 - 136 , which will be further described. 
       FIG. 3  depicts a data table  300  in which feedback  170 - 176  for annotations  160 ,  162  may be stored. In this example, the data table  300  includes feedback from three participants  130 - 136 , having respective user identifiers User_ID_ 444444 , User_ID_ 555555  and User_ID_ 666666 , for three annotations, indicated as AN_ 1 , AN_ 2  and AN_ 3 . Of course, there can be any number of portions of the presentation, annotations and participants, and the present arrangements are not limited to this example. 
     The data table  300  can include a column  310  indicating a title of the presentation  150 , a column  312  indicating particular portions (e.g., slides) of the presentation  150 , and a column  314  indicating the respective annotations AN_ 1 , AN_ 2  and AN_ 3 . The data table  300  also can include a column  316  indicating the rankings assigned by the participant having User_ID_ 444444  to each of the respective annotations AN_ 1 , AN_ 2  and AN_ 3 , a column  318  indicating the rankings assigned by the participant having User_ID_ 555555  to each of the respective annotations AN_ 1 , AN_ 2  and AN_ 3 , and a column  320  indicating the rankings assigned by the participant having User_ID_ 666666  to each of the respective annotations AN_ 1 , AN_ 2  and AN_ 3 . As noted, each ranking can indicate how the respective participant personally ranks the importance of the respective to the presentation. 
     The table also can include a column  322  indicating a level of expertise of the participant having User_ID_ 444444  to subject matters to which the respective annotations AN_ 1 , AN_ 2  and AN_ 3  pertain, a column  324  indicating a level of expertise of the participant having User_ID_ 555555  to subject matters to which the respective annotations AN_ 1 , AN_ 2  and AN_ 3  pertain, and a column  326  indicating a level of expertise of the participant having User_ID_ 666666  to subject matters to which the respective annotations AN_ 1 , AN_ 2  and AN_ 3  pertain. The data table  300  also can include a column  328  for a relevance parameter calculated for each of the annotations AN_ 1 , AN_ 2  and AN_ 3 . The relevance parameter for each annotation AN_ 1 , AN_ 2  and AN_ 3  can indicate the annotation&#39;s relevance to the portion of the presentation for which the annotation is provided, as will be further described. 
     In this example, there are no annotations provided for slide  1  of the presentation, there is one annotation. Thus, for slide  1 , values in columns  316 - 326  are null and the relevance parameter is zero. Annotation AN_ 1  is provided for slide  2  of the presentation, and annotations AN_ 2  and AN_ 3  are provided for slide  3  of the presentation. Each of the participants User_ID_ 444444 , User_ID_ 555555 , User_ID_ 666666  have provided feedback for each of the annotations AN_ 1 , AN_ 2  and AN_ 3 . Thus, the web conferencing application  112  can calculate the relevance parameter for each of the annotations AN_ 1 , AN_ 2  and AN_ 3  based on the participant rankings and level of expertise of each of the participants in the subject matters to which the respective annotations pertain, for example the subject matter of a particular portion of the presentation for which the annotation is provided and/or the subject matter of the annotation itself. 
     As noted, each of the participants may input his or her level of expertise indicated in columns  322 - 326 , or the web conferencing application  112  or web conferencing client  140  can automatically determine each level of expertise indicated in columns  322 - 326 . To automatically determine each level of expertise, the web conferencing application  112  or web conferencing client  140  can perform NLP and semantic analysis on the respective annotation and/or on information presented in the slide to which the annotation pertains. The NLP and semantic analysis can identify terms, concepts and information contained in the annotation and/or presentation information. The web conferencing application  112  or web conferencing client  140  can compare such terms and contents to information contained in the respective participant&#39;s user profile, for example areas of expertise indicated in the participant&#39;s user profile. Based on such comparison, the web conferencing application  112  or web conferencing client  140  can generate a value indicating the participant&#39;s level of expertise, which web conferencing application  112  can store in the appropriate column and row of the data table  300 . 
     The web conferencing application  112  also can apply NLP, semantic analysis and regression analysis to determine the relevance parameter for each annotation AN_ 1 , AN_ 2  and AN_ 3 , as previously described. 
     For each annotation AN_ 1 , AN_ 2  and AN_ 3 , the web conferencing application  112  can process the assigned rankings and the level of expertise of the participants assigning the rankings to derive a net ranking. For example, each ranking assigned by a participant can be assigned a weight based on the expertise of the participant. Thus, rankings provided by participants having higher expertise can be given more weight than participants having a lower level of expertise. The web conferencing application  112  can average the weighted rankings and normalize those rankings to a ranking scale being used, for example within a range of zero to ten. The rankings  180 ,  182  depicted in  FIG. 2  can be net rankings determined in this manner. 
     The web conferencing application  112  can determine a period of time for which to present each annotation AN_ 1 , AN_ 2  and AN_ 3  based on the relevance parameter and the level of expertise of the participant to whom the annotation is presented. For example, based on the relevance parameter for each annotation AN_ 1 , AN_ 2  and AN_ 3 , the web conferencing application  112  can generate an annotation decay model for each annotation. 
     The web conferencing application  112  further may analyze results of the NLP and semantic analysis to compare each annotation AN_ 1 , AN_ 2  and AN_ 3  with previously received annotations. In some cases, the same types of annotations may be received repeatedly. For example, different annotations may ask the same question, but in different ways. Comparing the results of NLP and semantic analysis from different annotations  160 ,  162  can allow the web conferencing application  112  to identify such annotations. Because the same question is being asked repeatedly, the web conferencing application  112  can select at least one of the annotations  160 ,  162  identified by the web conferencing application  112  as best representing the question (e.g., having the highest relevance parameter  190 ,  192 ), and persist that annotation the presentation  150 . This can reduce the likelihood of other participants continuing to ask the same question, and prompt discussion of the question during subsequent presentations of the same presentation  150 . In one non-limiting arrangement, to persist an annotation  160 ,  162  to the presentation  150 , the web conferencing application  112  can update the relevance parameter  190 ,  192  assigned to that annotation  160 ,  162  to be equal to or greater than 0.90. 
     In one aspect of the present arrangements, if an annotation  160 ,  162  has a relevance parameter  190 ,  192  and/or ranking that exceeds a threshold value, the web conferencing application  112  can automatically update the presentation  150  to include the information contained in the annotation  160 ,  162 . In another aspect, the web conferencing application  112  can generate a notification to a presenter of the presentation  150  (e.g., the participant  130 ) indicating to the presenter that the presenter should consider updating the presentation  150  to include in the presentation  150  the content of the annotation  160 ,  162 . For example, responsive to the web conferencing application  112  assigning to an annotation  160 ,  162  a relevance parameter  190 ,  192  that is equal to or greater than 0.90, the web conferencing application  112  can generate the notification. 
       FIG. 4  depicts a chart  400  presenting a plurality of annotation decay models  402 ,  404 ,  406  for various annotations  160 ,  162  (e.g., annotations AN_ 1 , AN_ 2  and AN_ 3  of  FIG. 3 ). The web conferencing application  112  can generate each decay model  402 ,  404 ,  406  based on a value of a corresponding relevance parameter  190 ,  192  (e.g., annotations AN_ 1 , AN_ 2  and AN_ 3  of  FIG. 3 , respectively). For example, the web conferencing application  112  can execute an algorithm configured to generate a corresponding decay model  402 ,  404 ,  406  using a respective relevance parameter  190 ,  192  as an input variable. The algorithm can be configured to output decay models  402 ,  404 ,  406  having desired annotation decay characteristics for given relevance parameters  190 ,  192 . 
     Each decay model  402 ,  404 ,  406  can indicate, for a respective annotation, different durations of time the annotation is to be visible to different participants  130 - 136  having various levels of expertise. For example, the decay models  402 ,  404 ,  406  can indicate rates of decay. The higher the decay rate, the shorter the period of time will be that the web conferencing application  112  presents the annotation. The lower the decay rate, the longer the period of time will be that the web conferencing application  112  presents the annotation. For example, assume that annotation AN_ 1  is presented to a participant  136  having a level of expertise that if 3. According to the decay model  402 , the decay rate for that annotation AN_ 1 , when presented to the participant  136 , is 0.20, or 20%. Thus, a standard time period, which can be a predetermined time period, represents 20% of the total period the annotation AN_ 1  is to be presented. Thus, if the standard time period is 10 seconds, the annotation AN_ 1  will be presented for 50 seconds. If, however, the standard time period is 1 minute, the annotation AN_ 1  will be presented for 5 minutes. The present arrangements are not limited to any particular period of time being the standard period of time, however. Nevertheless, certain annotations can be presented to certain participants longer in comparison to other participants. In this regard, the web conferencing application  112  can make the annotations  160 ,  162  selectively visible to different participants  130 ,  132  for different amounts of time based on the decay models  402 ,  404 ,  406 . 
     In illustration, annotations having a low relevance parameter may not be of significant interest to highly skilled participants, for example such annotations may be directed to fundamental concepts. Thus, such annotations can be presented to highly skilled participants for a short period of time. Participants who are novices, however, may find such annotations useful, and the annotations can be presented for a longer period time to such participants. On the other hand, annotations having a high relevance parameter may be of significant interest to highly skilled participants. For example, such annotations may pertain to advanced concepts. Thus, such annotations may be presented to expert participants for a longer period of time. Participants who are novices may not have a high level of interest in such annotations, and thus the annotations can be presented to the participants who are novices for a shorter period of time. 
     In one aspect, at least one annotation  160 ,  162  that is highly complex can be presented only to participants having a level of expertise that exceeds a threshold value. In this regard, the web conferencing application  112  can during the web conference, selectively make visible the annotation  160 ,  162  to certain participants  130 - 136 , while not presenting such annotations  160 ,  162  to other ones of the participants  130 - 136 . The web conferencing application  112  can identify such annotations  160 ,  162  based, at least in part, on the relevance parameters assigned to such annotations  160 ,  162 . In addition, the web conferencing application  112  also can consider data indicating the complexity of the annotations  160 ,  162  as indicated by the NPL and semantic analyses performed on the annotations  160 ,  162 . 
     The decay models  402 - 406  also can be used to control availability of the annotations to other users who are not participants in the web conference, but who view web conference, and thus the presentation  150 , at a later time by playing back a recording of the web conference. The web conferencing application  112  can access user profiles of the users to determine their levels of expertise, for example as previously described, and apply the decay models  402 - 406  accordingly. 
     The web conferencing application  112  need not generate a decay model  402 - 406  for certain annotations  160 ,  162  having a very high relevance parameter (e.g., equal to or greater than 0.9). Instead, the web conferencing application  112  can persist such annotations  160 ,  162  to the presentation  150 , as previously noted. 
       FIG. 5  is a flow chart illustrating an example of a method  500  of present annotations with a presentation in accordance with decay models generated for the respective annotations. At step  502 , a plurality of annotations can be received for a presentation presented in a web conference. At step  504 , a respective relevance parameter can be assigned to each of the plurality of annotations. Each relevance parameter can indicate a relevance of a respective one of the plurality of annotations to a portion of the presentation to which the annotation pertains. At step  506 , for each of the annotation, a decay model can be generated. The decay model can be based on the respective relevance parameter and can indicate different durations of time the annotation is to be visible to different participants participating in the web conference based on respective expertise levels of the participants. At step  508 , each respective annotation can be presented with the presentation in accordance with the decay model generated for the respective annotation. 
       FIG. 6  is a block diagram illustrating example architecture for the server  110 . The server  110  can include at least one processor  605  (e.g., a central processing unit) coupled to memory elements  610  through a system bus  615  or other suitable circuitry. As such, the server  110  can store program code within the memory elements  610 . The processor  605  can execute the program code accessed from the memory elements  610  via the system bus  615 . It should be appreciated that the server  110  can be implemented in the form of any system including a processor and memory that is capable of performing the functions and/or operations described within this specification. For example, the server  110  can be implemented as a single processing system or a plurality of communicatively linked processing systems. 
     The memory elements  610  can include one or more physical memory devices such as, for example, local memory  620  and one or more bulk storage devices  625 . Local memory  620  refers to random access memory (RAM) or other non-persistent memory device(s) generally used during actual execution of the program code. The bulk storage device(s)  625  can be implemented as a hard disk drive (HDD), solid state drive (SSD), or other persistent data storage device. The server  110  also can include one or more cache memories (not shown) that provide temporary storage of at least some program code in order to reduce the number of times program code must be retrieved from the bulk storage device  625  during execution. 
     One or more network adapters  630  also can be coupled to server  110  to enable the server  110  to become coupled to other devices, systems, computer systems, remote printers, and/or remote storage devices through intervening private or public networks. Modems, cable modems, transceivers, and Ethernet cards are examples of different types of network adapters  630  that can be used with the server  110 . 
     As pictured in  FIG. 6 , the memory elements  610  can store the web conferencing application  112  of  FIG. 1 . Being implemented in the form of executable program code, the web conferencing application  112  can be executed by the server  110  and, as such, can be considered part of the server  110 . The memory elements  610  also can store the annotations  160 ,  162 , the feedback  170 - 176  and the relevance parameters  190 ,  192  of  FIG. 1 , as well as the decay models  402 - 406  of  FIG. 4 . The web conferencing application  112 , annotations  160 ,  162 , feedback  170 - 176 , relevance parameters  190 ,  192  and decay models  402 - 406  are functional data structures that impart functionality when employed as part of the server  110 . 
       FIG. 7  is a block diagram illustrating example architecture for the client device  120 . The client devices  122 - 126  can be configured in a similar manner. 
     The client device  120  can include at least one processor  705  (e.g., a central processing unit) coupled to memory elements  710  through a system bus  715  or other suitable circuitry. As such, the client device  120  can store program code within the memory elements  710 . The processor  705  can execute the program code accessed from the memory elements  710  via the system bus  715 . It should be appreciated that the client device  120  can be implemented in the form of any system including a processor and memory that is capable of performing the functions and/or operations described within this specification. 
     The memory elements  710  can include one or more physical memory devices such as, for example, local memory  720  and one or more bulk storage devices  725 . The client device  120  also can include one or more cache memories (not shown) that provide temporary storage of at least some program code in order to reduce the number of times program code must be retrieved from the bulk storage device  725  during execution. 
     Input/output (I/O) devices such as a display  730 , and, optionally, a pointing device  735  and/or keyboard  740  can be coupled to the client device  120 . The I/O devices can be coupled to the client device  120  either directly or through intervening I/O controllers. For example, the display  730  can be coupled to the client device  120  via a graphics processing unit (GPU), which may be a component of the processor  705  or a discrete device. One or more network adapters  745  also can be coupled to client device  120  to enable the client device  120  to become coupled to other systems, computer systems, remote printers, and/or remote storage devices through intervening private or public networks. Modems, cable modems, transceivers, and Ethernet cards are examples of different types of network adapters  745  that can be used with the client device  120 . 
     As pictured in  FIG. 7 , the memory elements  710  can store the web conferencing client  140 . Being implemented in the form of executable program code, the web conferencing client  140  can be executed by the client device  120  and, as such, can be considered part of the client device  120 . Moreover, the web conferencing client  140  is functional data structure that imparts functionality when employed as part of the client device  120 . 
     While the disclosure concludes with claims defining novel features, it is believed that the various features described herein will be better understood from a consideration of the description in conjunction with the drawings. The process(es), machine(s), manufacture(s) and any variations thereof described within this disclosure are provided for purposes of illustration. Any specific structural and functional details described are not to be interpreted as limiting, but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the features described in virtually any appropriately detailed structure. Further, the terms and phrases used within this disclosure are not intended to be limiting, but rather to provide an understandable description of the features described. 
     For purposes of simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Further, where considered appropriate, reference numbers are repeated among the figures to indicate corresponding, analogous, or like features. 
     The present invention may be a system, a method, and/or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention. 
     The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. 
     Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device. 
     Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention. 
     Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions. 
     These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks. 
     The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions. 
     The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “includes,” “including,” “comprises,” and/or “comprising,” when used in this disclosure, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. 
     Reference throughout this disclosure to “one embodiment,” “an embodiment,” or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment described within this disclosure. Thus, appearances of the phrases “in one embodiment,” “in an embodiment,” and similar language throughout this disclosure may, but do not necessarily, all refer to the same embodiment. 
     The term “plurality,” as used herein, is defined as two or more than two. The term “another,” as used herein, is defined as at least a second or more. The term “coupled,” as used herein, is defined as connected, whether directly without any intervening elements or indirectly with one or more intervening elements, unless otherwise indicated. Two elements also can be coupled mechanically, electrically, or communicatively linked through a communication channel, pathway, network, or system. The term “and/or” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will also be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms, as these terms are only used to distinguish one element from another unless stated otherwise or the context indicates otherwise. 
     The term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in response to detecting,” depending on the context. Similarly, the phrase “if it is determined” or “if [a stated condition or event] is detected” may be construed to mean “upon determining” or “in response to determining” or “upon detecting [the stated condition or event]” or “in response to detecting [the stated condition or event],” depending on the context. 
     The descriptions of the various embodiments of the present invention have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.