Abstract:
A method and communication system are disclosed for conducting a conference among conference participants connected by a communication system. This system has at least one conference server and at least one image reproduction unit at each conference environment. The method involves collecting context data concerning at least one of the conference participants at multiple timed intervals; calculating a relationship value from the context data at the timed intervals; determining a relationship status, wherein the relationship status is expressed using one of several categories defined by a threshold value, depending on the calculated relationship value; and displaying the relationship status on at least one image reproduction unit during the conference. The method may be performed at the beginning of the conference and/or when a new participant joins the conference.

Description:
FIELD OF INVENTION 
       [0001]    The invention concerns a method and a device for managing a conference, in particular a virtual conference. 
       BACKGROUND OF THE INVENTION 
       [0002]    Conferences are becoming ever more important in the business world. The practice already exists of holding conferences with people who are physically present in a conference room and people who are not in the conference room but rather, for example, at a job site, working from home, or located somewhere else, wherein the people who are not physically present are included via electronic means of communication. So that all conference participants can be seen appropriately, it is preferable from a social standpoint if people who know each other better can also convey that while communicating. The many social contacts that are also but not only cultivated through social networks and via digital communication media, together with increasingly busy schedules, mean that people who are not in the room are not recognized or activities in common are forgotten. This has also been described as “digital dementia.” In such cases, a conference participant is treated as an outsider, which leads to irritation and can impair the conference. In addition, “experiences” that have occurred with a specific conference participant in the past can make it possible, for example, to reach a solution more rapidly if personal preferences, sensitive issues, or areas open to compromise are known. If such experiences are known for each conference participant, it can increase the productivity of a conference. 
         [0003]    Previously it was not possible to learn about personal qualities and characteristics unless there was time to do so during the conference, or unless there was a prior conversation about who was there, where participants had previously met, and how well they knew each other. There is often no time for this, and so these possibilities are lost, especially if a participant is not physically present in the conference room. In such situations, something that could be a powerful tool for rapidly establishing an efficient and successful discussion, individual trust, or understanding often goes unused. A discussion related to this lack could drag on unnecessarily, because the participants didn&#39;t fully understand each other at first. 
         [0004]    One goal of the present invention is to offer a method and a device for managing communications in conferences that can at least in part overcome the aforementioned disadvantages of the prior art. A particular goal of the present invention is to offer a method and a device for managing communications in conferences that can increase the efficiency and productivity of conferences. 
         [0005]    The invention achieves this goal at least partially by means of the features in the independent claims. Advantageous embodiments and developments of the invention are provided in the dependent claims. 
       SUMMARY OF THE INVENTION 
       [0006]    One embodiment of the invention proposes a method for managing a conference, in which, from the perspective of at least one participant, at least one other participant is displayed in a virtual room, wherein the method includes the following steps, to be taken at the beginning of the conference and/or when a new participant joins in and/or when initiated by one of the at least one participants:
       a) Collect context data concerning each or at least one selected from among at least one other participant and/or the new participant at multiple timed intervals;   b) Calculate a relationship value from the context data at the timed intervals;   c) Determine a relationship status, wherein the relationship status is expressed using one of several categories defined by a threshold value, depending on the calculated relationship value; and   d) Display the relationship status during communication.       
 
         [0011]    For purposes of this disclosure, a conference is understood to be a communication event involving multiple, preferably more than two participants, including the exchange of at least audio and video data, wherein the data exchange is accomplished using electronic means of communication, preferably governed by a packet-based protocol such as TCP/IP or the like. For purposes of the invention, a virtual room is a suitable viewing surface on a device used by at least one participant. In other words, this is called a virtual conference or teleconference. For purposes of the invention, context data are understood to be data about the participant&#39;s relationship with one or more of the other participants, as described in more detail below. For purposes of the invention, a relationship value is a numerical value used to quantify the intensity of a relationship. With each communication process that occurs between persons, the context data with reference to those persons are changed. Because the context data are reacquired at the time of the conference, the relationship status is continually updated. The current relationship status for any or all of the other participants can be displayed instantly for the at least one participant, so that known but forgotten relationships or experiences can effectively be recalled. This also makes it possible, without intensive advance preparation, to associate with each other at rated trust levels and better assess the other participant. Long “warm-up periods” can be shortened or eliminated. The productivity and efficiency of the conference can be increased. Assignment to defined categories facilitates the participants&#39; intuitive comprehension of the relationship status. 
         [0012]    Context data can be collected from data sources such as:
       social networks;   on-house communication and staff network data banks;   connection data banks of communication providers such as e-mail, telephone, VoIP, and mobile wireless service providers.
 
It should be understood that this list does not include all possible sources. Widely different types of data sources, such as relationship networks, for example, can be evaluated and used in determining the relationship status.
       
 
         [0016]    In addition, the context data can be related to events such as:
       communication events such as telephone conversations, e-mails, SMS, MMS, etc.;   friend statuses, messages, likes, comments, blog entries, etc.;   organizational events;   professional collaboration;   projects;   meetings;   joint publications or conference presentations;   joint travel or events;   mutual interests;   living or working in proximity;   membership in the same associations, societies, political parties, or other personal organizations,
 
with the understanding that this list does not include all possible items. Widely different types of events can be evaluated and used in determining the relationship status. It is possible to call up and display context data or metadata and/or individual event content from the data sources during the conference.
       
 
         [0028]    Context data can be or include a counted number of events assigned to the other participant from the participant&#39;s perspective, wherein preferably the counted number of events used in calculating the relationship value is weighted according to how long before the time of the conference it happened and/or according to the type and/or circumstances of the event. This makes it possible to rate the relationship by simply adding up the communication events. As an example of weighting according to how long ago the event happened, an event that occurred longer ago can be weighted lower than a more recent event. As an example of weighting according to the type of event, a jointly organized project or joint publication can be weighted higher than a like on a social network. As an example of weighting according to the circumstances of the event, the length of telephone conversations, number of characters in selected text messages or text files, data volumes of selected files, etc. can influence the rating. 
         [0029]    The time intervals can include a current time interval that runs up to the time of the virtual conference, and a prior time interval that immediately precedes the current time interval, wherein the length of the time intervals is one month, in particular. One month is a reasonable length of time for active relationships. For finer classification, shorter time intervals such as two weeks, one week, or one day are also conceivable. For weaker relationships, a longer time period such as a year or longer can be suitable, so as to be able to include old school friends, fellow college students, vacation acquaintances, etc. for example. 
         [0030]    The relationship value is calculated preferably using the formula 
         [0000]        B ( T )= V×Z ( T )+(1− V )× B ( T− 1)
 
         [0000]    wherein T is a current time interval, T- 1  is an elapsed time interval immediately before the current time interval t, Z is a counted number of events in a given time interval, V is a factor that simulates having forgotten about events over time and is expressed by a value between 0 and 1, preferably 0.4-0.8, and B is the relationship value. By introducing a memory factor, a forgetfulness curve is added. The formula essentially represents a simple digital low-pass filter. Alternatively, other filtering characteristics can also be used. As an option, statistical outliers can be smoothed out using median filtering. 
         [0031]    In one preferred embodiment, collection of context data and preferably calculation of a relationship value from the context data are executed separately for all or for several selected or for one relationship level(s). It is especially preferred to collect context data, calculate a relationship value from the context data and determine a relationship status separately for all or for several selected or for one relationship level(s). The relationship level(s) can include:
       public relationships;   private relationships;   work-related relationships;       
 
         [0035]    In other words, context data are acquired for each relationship level, a relationship value is preferably also calculated for each relationship level, and, especially preferably, the relationship status is also determined for each relationship level. This means that the aforementioned method can be applied fully for each separate relationship level. In addition, it is also possible to add levels together for a total score at any point in the process, wherein, for example, a maximal value for the relationship status of all levels is used as a total score or an overall relationship status is determined based on an appropriately weighted sum of the relationship values for all levels, or a total relationship value is calculated based on an appropriately weighted sum of the context data for all levels. The display of results can include all or one or more preset or one or more selected relationship levels. In other words, for example, the at least one participant can choose whether he wishes the display to show one selected relationship level or a relationship result for all or multiple integrated relationship levels. 
         [0036]    Again, it is understood that the list of relationship levels is not all-inclusive. For example, multiple levels can exist for work-related relationships if a participant includes multiple positions in the company. Multiple levels of private or public relationships can also be defined, such as those related to family, to professional (but not company-related) contacts, to a society, or to a political party. It is possible for each participant&#39;s relationship levels to be freely defined and configured. 
         [0037]    The relationship status can be displayed in any of the following ways:
       Audio signals;   Colors, in particular a background, a border, or fill;   Tags;   Icons, emoticons;   Images, graphics, caricatures;   Film clips, music clips, jingles.
 
But this list is not all-inclusive. The display choice can be such that the relationship status and the respective calculated levels “jump right out” at the viewer. Different types and/or means of display can be used for different relationship levels.
       
 
         [0044]    The relationship status preferably includes the categories “strong relationship,” “medium relationship,” “weak relationship,” and “no relationship.” The threshold values used to delimit the relationship statuses are set to be relevant to life experience and can be adjusted by the user as appropriate. 
         [0045]    It is understood that the method can be performed in a communication system using a computer program that includes program commands that make a computer carry out the process steps of the described process, if the computer program is stored on or called up by the computer, as well as a software product that is stored on a computer-readable medium and can preferably be installed directly into the internal memory of a computer and has program codes for carrying out the process steps of the described method when the computer program is run on the computer, plus a digital storage medium with electrically readable control signals that can be processed by a programmable computer in order to manage communication processes, wherein the control signals are generated and adjusted so as to make the computer carry out the process steps of the described method. Such a computer can be part of a conference system, a conference server, a conference terminal, a participant&#39;s individual device, etc. 
         [0046]    A device for executing the method is provided, wherein the process is carried out as described above. The problem addressed by the present invention is solved by these devices for the same reasons as the ones stated above for the corresponding method. The device can be, for example, a conference server or a central conference unit or terminal. 
         [0047]    Additional features, tasks, advantages and details of the present invention will become more apparent from the following description of concrete exemplary embodiments and their presentation in drawings in the included figures. It is understood that features, tasks, advantages and details of individual exemplary embodiments are transferrable to other exemplary embodiments and are considered to be disclosed also in connection with the other exemplary embodiments unless this is obviously inapplicable for technical or physical reasons. Exemplary embodiments can be combined with other exemplary embodiments and that combination can also be considered an exemplary embodiment of the invention. 
         [0048]    Present preferred embodiments of the invention are described below in more detail based on preferred exemplary embodiments and with reference to the figures. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0049]      FIG. 1  is a representation of a virtual conference room from a participant&#39;s perspective; 
           [0050]      FIG. 2A  is a representation of a selection of participants from the virtual conference room with additional information; 
           [0051]      FIG. 2B  is a representation of another selection of participants from the virtual conference room with additional information; 
           [0052]      FIG. 3  is a flow diagram illustrating one communication management process; and 
           [0053]      FIG. 4  is a block diagram illustrating process steps with references to hardware and software components from the process shown in  FIG. 3 . 
       
    
    
       [0054]    The figures are schematic presentations and not necessarily according to scale. The illustrations in drawings and the descriptions thereof shall be considered exemplary illustrations of the principle of the invention and shall in no way restrict the invention. 
       DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       [0055]    The present method is intended to be performed by a communication system used for conducting a conference among conference participants, one set of conference participants being at a first conference environment and at least one other set of conference participants being at another conference environment. The conference participants are connected by a communication system that has at least one conference server and at least one image reproduction unit at each conference environment on which images corresponding to at least some of the conference participants are displayed. The image reproduction unit may be a stand alone display device such as an LED screen, a computer monitor or a screen on a mobile commuication device such as a smart phone. The conference server contains a processor and a non-transitory memory containing a program which causes the communication system to perform the method described here. The communication system may also contain a local conferencing unit at one or more of the conference environments which has a processor and a non-transitory memory that can perform some or all of the steps of the present method. 
         [0056]      FIG. 1  shows a representation of a virtual conference room  100  from the perspective of a participant in a video conference. In other words, the conference room  100  corresponds to an image or partial image (called a window) on a participant&#39;s display screen. The one participant who is not shown here is also designated in the following as the viewer. 
         [0057]    The virtual conference room  100  includes a reference structure  110  that represents a conference table. Around the reference structure  110  is a group of participants  120  that includes participants  121 ,  122 ,  123 ,  124 , and  125 . In addition, around the participant group  120  there is a group of symbols  130  that includes symbols  131 ,  132 ,  133 ,  134 , and  135 , wherein each of the symbols  131 ,  132 ,  133 ,  134 , and  135  is assigned to one of the participants  121 ,  122 ,  123 ,  124 , and  125 . Precisely stated, symbol  131  is assigned to participant  121 , symbol  132  is assigned to participant  122 , symbol  133  is assigned to participant  123 , symbol  134  is assigned to participant  124 , and symbol  135  is assigned to participant  125 . The symbols  131 ,  132 ,  133 ,  134 , and  135  are so-called emoticons that symbolize an emotional and/or relationship status for each of the participants  121 ,  122 ,  123 ,  124 ,  125 . In addition, there is a group of objects  140 , which here includes only a single object  141  located on the reference structure  110  (conference table). The object  141  corresponds to a file or file folder for an object that can be opened on the same or a separate display screen area by the viewer. 
         [0058]      FIGS. 2A and 2B  each include a representation of a selection of participants from the virtual conference room  100  with additional information. More precisely,  FIG. 2A  shows a selection area  210  in whose upper left corner the participant  121  from  FIG. 1  is shown in accentuated form, here highlighted by a border and colored or gray background. An information block  220  is assigned to the participant  121 , visually set off from the selection window  210 . In addition, the selection area  210  includes the participants  123  and  125  with their respective symbols (emoticons)  133  and  135 . 
         [0059]    The information block  220  can provide specific personal information, for example, such as:
       personal notes,   personal assessments,   curriculum vitae.       
 
         [0063]    The selection area  210  has been generated, for example, by the viewer of the conference room  100  from  FIG. 1 . The selection area  210  allows the participant  121  to be accentuated after he/she is, for example, selected by the viewer or identified by the viewer&#39;s line of sight. In other words, the viewing participant him/herself can adjust the focus, or the focus can be recognized and established, for example, by facial identification using a camera at the conference location. The additional participants  123  and  125  in the selection area  210  can be, for example, participants who were previously selected or identified or were established by a conference server or similar means based on other criteria. 
         [0064]      FIG. 2B  further shows a selection area  230  in whose upper left corner the participant  123  is shown in accentuated form, here highlighted by a border and colored or gray background. An information block  235  is assigned to the participant  123 , visually set off from the selection area  230 . In addition, the selection area  230  includes the participant  125  with his/her symbol (emoticon)  135 . An information block  250  can be seen below the selection area  230 . 
         [0065]    The information block  240  can provide specific personal information, for example, such as:
       calling up recent publications,   results of the last meeting.       
 
         [0068]    The information block  250  can contain individual relationship information for other conference participants as summary information. The individual relationship information is obtained from historical data. The “sentiment detection” resulting from the data analysis can recognize emotional statements. By combining these emotional statements, a sympathy sequence can be established by comparison with the values for other people with whom a relationship exists. The summarized relationship can be rated on a sympathy □ antipathy scale. This is also possible on line, where any negative statements/responses and/or positive statements/responses are evaluated using sentiment detection. The summary information in that case is the summary relationship based on the emotional values for sympathy and antipathy provided by sentiment detection. 
         [0069]      FIG. 3  shows a communication management process  300 . When the process  300  is called up, a pre-selected list from among the participants in the conference is transferred to the process  300 . The pre-selected list can be generated by the viewer or by the system. 
         [0070]    After the process is started (called up) and after a transfer step not shown here is completed, in step  310  a participant is selected from among the participants generated in the process  300 . 
         [0071]    Next, in step  320  context data are acquired for the participant selected in step  310 . The context data reflect the relationship status with the selected participant on multiple relationship levels. For example, the relationship levels can include:
       Private relationships (p),   Public relationships (ö),   Work-related relationships (f).       
 
         [0075]    The context data are acquired from data sources  390  such as social networks, a company database, a communications server, or other sources, for example, and can refer to items such as organizational data, communication data (connection data), project data, meeting data, joint publications, etc. The relationship status generated from the context data corresponds in each level to a counted number Z of events that have occurred at the respective level. 
         [0076]    Next, in step  330 , a relationship value B is calculated for each relationship level. The relationship value B for each relationship level is generated from the events that have occurred at the respective relationship level over time. A forgetfulness curve, characterized by a forgetfulness constant V, is applied in order to give priority to more recent events. In other words, first an applicable time interval T is selected, in which the various events that have occurred are counted in order to generate a counted number Z in each time interval T. The relationship value B is then calculated using a simple digital low-pass filter. Alternatively, other filter functions can be used or, for example, statistical outliers can be filtered out with median filtering. As a suitable filter function, the function 
         [0000]        B ( T )= V×Z ( T )+(1− V )× B ( T− 1)
 
         [0000]    can be used. Wherein T is a current time interval, T- 1  is a previous time interval immediately before the current time interval T, Z is the counted number of events in the given time interval, V is the forgetfulness factor that simulates having forgotten about events over time, and B is the relationship value. 
         [0077]    The length of each time interval T, T- 1  can be established by default as one month. However, other time intervals can also be used. It is also possible to use different time intervals for different relationship levels. It is conceivable that one month could be too short of a time period to count for weak relationships, so that possibly quarters, half-years, years, or even longer periods of time may be appropriate. 
         [0078]    By selecting the time interval T and the forgetfulness factor V, relationships can be standardized for a particular participant. For instance, less communicative people can have strong relationships, although they generally communicate less often than others. 
         [0079]    In the concrete example, for the three relationship levels ö, p, and f, the relationship values 
         [0000]        B   ö ( T )= V×Z   ö ( T )+(1 −V )× B   ö ( T− 1) for the public relationship level,
 
         [0000]        B   p ( T )= V×Z   p ( T )+(1 −V )× B   p ( T− 1) for the private relationship level, and
 
         [0000]        B   f ( T )= V×Z   f ( T )+(1 −V )× B   f ( T− 1) for the company relationship level are calculated.
 
         [0080]    Next, in step  340 , a relationship status is determined from each relationship level, using the relationship values calculated in step  330 . Here categories are used that reflect the strength of a relationship and are characterized by threshold values for each relationship value. For example, the categories “strong relationship,” “medium relationship,” “weak relationship,” and “no relationship” are used. If the relationship value B(T) is below a threshold value B weak , the relationship is assigned to the relationship level categorized as “no relationship.” If the relationship value B(T) is above the threshold value B weak  but below the threshold value B medium , the relationship is assigned to the relationship level categorized as “weak relationship.” If the relationship value B(T) is above the threshold value B medium  but below the threshold value B strong , the relationship is assigned to the relationship level categorized as “medium relationship.” If the relationship value B(T) is above the threshold value B strong , the relationship is assigned to the relationship level categorized as “strong relationship.” 
         [0081]    The relationship status for the defined participant is then displayed in step  350 . 
         [0082]    The subsequent step  360  determines whether all or all selected participants have been evaluated. If so (yes in step  360 ), the process  300  ends. Otherwise (no in step  360 ), the process jumps back to the aforementioned transfer step that leads back to step  310 . 
         [0083]    The process  300  can be performed by a central conference unit. Alternatively, the process  300  can also be performed by an individual conference participant&#39;s device or system. 
         [0084]    Since the relationship value B(T) in each relationship level ö, p, f can be recalculated based on how long ago each event occurred, including the event numbers Z per relationship level for the current time interval T as well as the relationship B for the last time interval T- 1 , the current relationship value can be recalculated at any time. In so doing, only relationship values that are above the threshold value B weak  can be used for a weak relationship. 
         [0085]    Obviously, the invention is not limited to the three levels listed. For example, the private level can be separated into a personal and a professional level, there can be multiple company-related relationship levels for different companies, there can be political or association-related levels, etc. Event counting can be weighted depending on the source. It is therefore conceivable for long-term projects with comparatively few communication events to be weighted higher than postings to a social network, SMSs, etc. 
         [0086]      FIG. 4  shows a block diagram that illustrates process steps related to hardware and software components of a communication system or conference system that executes the process from  FIG. 3 . It is assumed that multiple participants A, . . . , N are participating in a conference. The participants  121 ,  122 ,  123 ,  124 , and  125  from  FIG. 1  can be the participants A, . . . , N from  FIG. 4 . 
         [0087]    In a first process step and/or context data step  410 , a context data bank is provided for each participant A, . . . , N. The figure shows a first context data bank  411  for the participant A and an nth context data bank  415  for the participant N. When process paths for the participants A and N are described below as coming from the context data banks  411  and  415 , the statement should be understood as also referring to the other participants and related context data banks, etc. The context data banks  411 , . . . ,  415  are generated such that context data for the participants A, . . . , N are collected from data sources  390 . For example, data sources  390  can be:
       Social networks such as Facebook, Twitter, etc.   Public media such as news stories, databases, etc.,   Company media such as Intranet, databases, etc.,   Internet searches, for example on Google, etc.,   and others.       
 
         [0093]    In a second process step and/or sentiment detection step  420 , a sentiment detection matrix is provided for each participant A, . . . , N, of which a first sentiment detection matrix  421  for the participant A and an nth sentiment detection matrix  425  for the participant N are shown. Each of the sentiment detection matrices  421 , . . . ,  425  is generated such that the context data bases  411 , . . . ,  415  are accessed for all participants, so that sentiment detection is performed for each participant A, . . . , N with respect to every other participant A, . . . , N. 
         [0094]    In a third process step and/or relationship step  430 , for each participant A, . . . , N a relationship vector is provided for each (other) participant, of which a first relationship vector  431  for the participant A and an nth relationship vector  435  for the participant N are shown. The relationship vectors  431 , . . . ,  435  are acquired from the respective sentiment detection matrices  421 , . . . ,  425 , wherein the relationship vector  431  represents the relationships of the participant A with all participants A, . . . , N, and an nth relationship vector  435  represents the relationships of the participant N with all participants A, . . . , N. A participant&#39;s relationship with him/herself can be represented in the respective relationship vector as a “0” or “−1” or another characteristic value, or can be omitted. The relationship vectors are sent to a back-end conference application  460  which will be described later. 
         [0095]    There, separately from the previously described sentiment detection, context analysis is performed in a fourth process step and/or context analysis step  440 . In the illustrated case, context analysis is performed only for the participant A. Therefore, in the context analysis step  440 , only a single context analysis unit  441  is shown, which performs a context analysis for the participant A based on the context data stored in the context data bank  411 . The context analysis includes counting events for each relationship level ö, p, and f (see above). 
         [0096]    For each of the relationship levels ö, p, f (see above), the context analysis results in counted event numbers Z(T) in the preset time interval T, i.e., a counted event number Z öA  (T) for the public relationship level of the participant A, a counted event number Z p,A (T) for the private relationship level of the participant Λ, and a counted event number Z f,A (T) for the company relationship level of the participant A. 
         [0097]    The counted event numbers Z(T) are delivered to a fifth process step and/or filtering step  450 . The filtering step  450  includes a filter unit  451  for the participant A. The filter unit  451  applies a filtering function in order to calculate and categorize, based on the counted event numbers for each of the relationship levels ö, p, f, a relationship value B(T) in the preset time interval T, i.e., a relationship value B δ,A (T) for the public relationship level of the participant A, a relationship value B p,A (T) for the private relationship level of the participant A, and a relationship value B f,A (T) for the company relationship level of the participant A (no, weak, medium, or strong relationship, see above), so that this calculation can also be sent to the related conference application  460 . 
         [0098]    In the following conference application  460 , all relationship vectors  431 , . . . ,  435  as well as all relationship values B δ/p/f.A (T) are processed so that the participants&#39; representations can be displayed on a screen or similar device in a final process step or display step  470 . In the display step  470 , displays are generated for each participant A, . . . , N, of which a first display  471  for the participant A and an nth display  475  for the participant N are shown. The displays for the participants correspond, for example, to the displays shown in  FIGS. 1 ,  2 A, and  2 B. 
         [0099]    It should be noted that using the processes in the upper process branch, consisting of process steps  420  and  430 , determines the emotional qualities of the relationships between participants, while using the processes in the lower process branch, consisting of process steps  450  and  460 , determines the intensity of the relationships between participants. Therefore, in the display step  470  a two-dimensional differentiation of the relationship with respect to relationship quality and relationship intensity is achieved using the emoticons  131 - 135  in the symbol group. 
         [0100]    The description above is from the perspective of one viewer of the virtual conference room  100  in  FIG. 1 . If the virtual conference room  100  is available to multiple conference participants, it is possible (under potentially sensitive circumstances) for the relationship statuses of certain participants to be available only to certain participants on their individual devices, such as the selection windows  210 ,  230  of  FIGS. 2A ,  2 B, while other participants&#39; access to those relationship statuses is blocked. 
         [0101]    In summary, the present method is based on the assumption that, in this era of extremely full schedules, there is usually no time to prepare adequately in advance for a conference. In particular, for conferences with participants in other locations, participants are not always recognized, so that prior social relationships cannot be optimally used. In order to help fill the memory gaps, it is advantageous to expand the central conference unit. According to the invention, the conference unit acquires relationship data from social networks, in-house organizational data, communication, project, and meeting data, etc. There can be essentially three relationship levels (private, company, public), each of which can be divided into four categories (strong, medium, weak, none). Per level, an overall relationship is determined as a counted value within a defined period of time (month, year). From that, a filter function is used to calculate the relationship value, which falls into one of four categories. The filter function defines a forgetfulness curve using a forgetfulness constant. By selecting the time period and the forgetfulness constant, a relationship can be adapted to the characteristics of a person. Grouping into a category is done by comparison with a threshold value. Depending upon the capabilities of the device, the result can be linked to the person and displayed in the form of audio signals, icons, colors, emoticons, etc. The invention can calculate and display the status of a (personal) relationship with reference to an “aging process,” among other things. This relationship status can also be used to manage additional functions (prioritizing information, interrupting a conference, forwarding to a distributor). 
         [0102]    The features of the invention described with reference to the illustrated embodiments, for example the information block  220  in  FIG. 2A  that contains specific personal information such as personal notes, personal assessments, and/or curriculum vitae, can also exist in other embodiments of the invention, for example additionally or alternatively in the information block  240  with call-ups of recent publications and/or the results of the last conversation in  FIG. 2B , except when stated otherwise or when impossible for technical reasons. 
       LIST OF REFERENCE SIGNS AND SYMBOLS 
       [0000]    
       
           100  virtual conference room 
           110  Reference structure (conference table) 
           120  Group of participants 
           121 - 125  Participants in a conference 
           130  Group of symbols 
           131 - 135  Symbols for the participants  121 - 125   
           140  Group of objects 
           141  Object 
           210  Selection area (selection window) 
           220  Information block 
           230  Selection area 
           240  Information block 
           250  Information block 
           300  Process 
           310 - 360  Process steps 
           390  Data sources 
           410  Process step (context data step) 
           411 ,  415  Context data banks 
           420  Process step (sentiment detection step) 
           421 ,  425  Sentiment detection matrix 
           430  Process step (relationship value step) 
           431 ,  435  Relationship vectors 
           440  Process step (context analysis step) 
           441  Context analysis unit 
           450  Process step (filtering step) 
           451  Filter unit 
           460  Back-end conference application 
           470  Process step (display step) 
           471 ,  475  Display 
         f Company level 
         ö Public level 
         p Private level 
         B Relationship value 
         T Time interval (current) 
         T- 1  Time interval (previous) 
         V Forgetfulness vector 
         Z Event number
 
The list above is an integral component of the description.