Abstract:
A system and method for knowledge management is disclosed. The method discloses: monitoring messages transmitted over a peer-to-peer network; profiling the messages; receiving a messages report request; identifying message profiles corresponding to the message report request; selecting messages corresponding to the identified message profiles; and generating the requested messages report from the selected messages. The system discloses means for implementing the method.

Description:
CROSS-REFERENCE TO CO-PENDING APPLICATIONS  
       [0001]    This application relates to and incorporates by reference co-pending U.S. patent application Ser. No. 10/093658, entitled “System And Method For Harvesting Community Knowledge,” filed on Mar. 7, 2002, by Adar et. al. This related application is assigned to Hewlett-Packard Co. of Palo Alto, Calif. 
     
    
     
       BACKGROUND OF THE INVENTION  
         [0002]    1. Field of the Invention  
           [0003]    The present invention relates generally to systems and methods for information sharing and knowledge management, and more particularly for searching for and analyzing previously transmitted messages within a system for harvesting community knowledge.  
           [0004]    2. Discussion of Background Art  
           [0005]    Satisfying information needs in a diverse, heterogeneous information environment is challenging. In order to even approach the process of finding information resources or answers to questions, individuals typically must know either where to look, or whom to ask. This is a challenging task, especially in large enterprises where many of the members are unaware of each other&#39;s skill sets, and of all the information resources available to them.  
           [0006]    Such challenges become ever more significant, as modern enterprises realize that their value and strength as ongoing ventures depends increasingly upon an ability of their members to easily share information. For example, individual members of an enterprise may have questions that need answered, or may need to come up to speed on particular areas of knowledge before beginning their new assignment. The enterprise itself may also need to access its strengths and weaknesses in various product, services, and research areas. Unfortunately however, meeting these information needs is often an elusive goal for many enterprises.  
           [0007]    Current systems for storing information and/or organizational expertise include Knowledge Databases (K-bases), such as document repositories and corporate directories, and Knowledge Management systems, which rely on users to explicitly describe their personal information, knowledge, and expertise to a centralized K-base.  
           [0008]    [0008]FIG. 1 is a dataflow diagram of a conventional knowledge management system  100 . In a typical architecture, information providing users  102  explicitly decide what descriptive information they provide to a central database  104 . An information seeking user  106  then performs a query on the central database  104  in order to find an information provider who perhaps may be able to answer the seeker&#39;s question.  
           [0009]    There are several significant problems with such systems. Knowledge management systems, like that shown in FIG. 1, require that information providers spend a significant amount of time and effort entering and updating their personal information on the central database  104 . For this reasons alone, such systems tend to have very low participation rates. In addition, even information providers, who take time to enter and update their information, may accidentally or purposefully misrepresent their personal information, levels of knowledge, and expertise. Furthermore, they may neglect or be unable to reveal much of their tacit knowledge. Tacit knowledge is commonly known as knowledge a user possesses, but which the user considers trivial, or may not even be consciously aware of.  
           [0010]    Because of the inaccuracy and/or incompleteness of such personal information, information seekers, even after all of their searching efforts, may still find their questions left unanswered, perhaps because the “expert” they identified may not have the bandwidth to respond, or may have been asked same question so that they, out of frustration or boredom, stop responding.  
           [0011]    Frequently Asked Questions (FAQ) generation within organizations is another information management problem area, which is often very time consuming and costly. As one example, most new employee&#39;s would find a FAQ list directed just to new employees very helpful. However, enterprises tend to generate such FAQs in very time consuming and inaccurate ways, such as by surveying selected employees as to what information they would have liked to know when they started work, or by just speculating as to what a new employee would perhaps want to know. As another example, an enterprise&#39;s IT department tasked with installing new hardware and/or software on the enterprise&#39;s network may be deluged with calls from all those affected. A FAQ on the installation might solve many of the problems which have arisen, however, by the time such a FAQ is created some weeks later, the installation has been completed and the problems are moot. These, however, are just two examples of FAQ generation problems. Most organizations in fact need a great number of diverse FAQs in order to operate more efficiently.  
           [0012]    In response to the concerns discussed above, what is needed is a system and method for harvesting community knowledge that overcomes the problems of the prior art.  
         SUMMARY OF THE INVENTION  
         [0013]    The present invention is a system and method for knowledge management. One embodiment of the method of the present invention includes: monitoring messages transmitted over a peer-to-peer network; profiling the messages; receiving a messages report request; identifying message profiles corresponding to the message report request; selecting messages corresponding to the identified message profiles; and generating the requested messages report from the selected messages.  
           [0014]    The system of the present invention, includes all means for implementing the method.  
           [0015]    These and other aspects of the invention will be recognized by those skilled in the art upon review of the detailed description, drawings, and claims set forth below.  
       
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0016]    [0016]FIG. 1 is a dataflow diagram of a conventional knowledge management system;  
         [0017]    [0017]FIG. 2 is a dataflow diagram of one embodiment of a system for harvesting community knowledge;  
         [0018]    [0018]FIG. 3 is a flowchart of one embodiment of a method for harvesting community knowledge;  
         [0019]    [0019]FIG. 4 is a flowchart of one embodiment of a method for message traffic analysis, categorization, and reporting; and  
         [0020]    [0020]FIG. 5 is a dataflow diagram of one embodiment of a server for message traffic analysis, categorization, and reporting.  
     
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT  
       [0021]    [0021]FIG. 2 is a dataflow diagram of one embodiment of a system  200  for harvesting community knowledge. FIG. 3 is a flowchart of one embodiment of a method  300  for harvesting community knowledge. FIGS. 2 and 3 are herein discussed together. The system  200  includes a client computer  202  under the control of a user  204 , and connected to a computer network  206 . The client  202  both sends and receives messages respectively to and from other client computers and information sources via the network  206 . When a client computer generates and sends a message such client computer is herein alternately called a sending client, and when a client computer receives a message, such client computer is herein alternately called a receiving client. Preferably all client computers on the network include the same functionality, which is now described with respect to the client computer  202 , however some receiving clients may not currently have the present invention&#39;s software installed.  
         [0022]    User Profiling  
         [0023]    The method  300  begins with an observer module  208  generating and maintaining a client profile  210  on the client computer  202 , in step  302 . The observer module  208  begins a process of generating and maintaining the client profile  210  by monitoring and collecting data with respect to both internal and external computer  202  information and operations. Internal data includes: user  204  behavior on the computer  202 , installed client hardware  211 , installed client software  212 , and locally stored client files  214 . External data includes: a web page cache  217  populated through internet client  232  interactions with web  218  sites, and e-mail messages  221  populated through e-mail client  230  interactions with an e-mail network  222 . User operations, in addition to the term&#39;s normal meaning, is herein defined to include together or in the alternative: user behavior on the client computer  202 ; any information about the user; any information about the client computer  202 ; and/or any information about the computer&#39;s  202  interaction with the network  206 .  
         [0024]    During the monitoring process, selected data is captured, processed, and added to the client profile  210 . The selected data is then automatically analyzed and formatted for storage in the client profile  210 . Thus, the observer module  208  relieves the user  204  from having to manually describe themselves to other users on the network  206 . This dramatically reduces the participation costs for all users of the present invention, while ensuring that the client profile  210  is constantly kept up to date. Thus the client profile  206 , as generated and maintained by the present invention, serves as a very rich and detailed data structure for enabling the user  204  to efficiently and equitably participate in an information market.  
         [0025]    In order to maximize the user&#39;s  204  privacy and thereby encourage broad user participation within the information market, the client profile  210  is preferably stored only on the client computer  202 , however the profile  210  may also be stored remotely either in encrypted or password protected form and viewable only by the user  204 . Also to toward this goal, the user  204  is also preferably given an option of erasing their client profile  210 , or having the observer  208  rebuild a new client profile for the user  204 .  
         [0026]    Message Generation  
         [0027]    Next to be described is a system and method for generating messages in step  304  using the present invention. Messages are herein defined to include a wide variety of communications known to those skilled in the art, including any communication seeking, sending, and/or culling information from an information market. Thus messages can include questions, announcements, and/or information processing routines.  
         [0028]    To begin, the user  204  accesses a user interface module  228 . The user interface module  228  preferably includes a set of software modules for interfacing with the user  204 . Such modules at a minimum include the e-mail client  230 , which stores a predetermined set of e-mail messages  221 , and the Internet client  232 , which stores information in the web page cache  217 . These two modules  230  and  232  provide the user  204  with alternate ways of using the present invention and preferably, both contain similar functionality, such as text windows and folders for storing messages both sent and received.  
         [0029]    Through the user interface module  228 , the user  204  initiates the message generating process, such as by clicking on an “Ask a Question” button in a toolbar within the user interface. In response, the user interface module  228  displays a number of pre-defined message types to the user  204 .  
         [0030]    One message type example is a “Find an Expert” message. The find an expert message is likely to be one of the more popular questions asked by the user  204 . The find an expert message includes a message field, an anonymous check box, and an optional filters field. The message field collects information provided by the user  204  which the user believes will help the present invention direct the message to receiving clients likely to be able to either answer the user&#39;s  204  question or be apprised of the user&#39;s  204  interest in some knowledge area and inviting further communication. The more detail the user  204  provides in the message field, the better directed will be the message to an appropriate set of receiving clients. The anonymous check box, if checked, directs the message to be sent only over a peer-to-peer network  226 , using randomization, without any information explicitly identifying the user&#39;s identity. Users of the present invention are expected to direct a large amount of message traffic over the peer-to-peer network  226  in order to maintain their anonymity. The optional filters field permits the user  204  to target the message to a set of receiving clients satisfying one or more filtering conditions.  
         [0031]    The network module  216  periodically scans the message database  236  for new messages generated by the user  204 . Then in step  306 , a network protocol module  219  formats the new message according to an XML (Extensible Markup Language) protocol for transmission by the network module  216  over the network  206 . Both a client computer sending the message and a client computer receiving the message must be apprised of the particular XML protocol used to format the message, in order for communication to occur.  
         [0032]    Preferably the peer-to-peer network  226  is limited to an enterprise&#39;s intranet so that only a predetermined set of client computers on the network  206  may have an opportunity to respond to the message. By limiting the scope of users allowed to see messages, a baseline level of confidentiality, expertise, and/or message response integrity may be maintained. For instance, the scope of users may be limited to only those who are employed within a particular enterprise, who belong to a particular professional society, or who are students and one or more universities. The exact scope of users will thus depend upon a particular application of the present invention.  
         [0033]    In alternate embodiments, messages may be transmitted over global e-mail and/or web networks, but in an encrypted format which again limits the scope of users. In other embodiments, there may be no limits on the scope of users who may be given an opportunity to respond to the messages.  
         [0034]    Message Transmission  
         [0035]    Next in step  308 , the network module  216  transmits the message over a predetermined portion of the computer network  206 . Messages transmitted over the peer-to-peer network  226  achieve a high level of anonymity, however many messages will likely be transmitted over the e-mail network  222  or displayed on a web  218  site in order to advertise the present invention and thereby build-up the peer-to-peer network  226 .  
         [0036]    As mentioned above, when the computer client  202  transmits a message over the network  206  it is called a sending client, while when the computer client  202  receives a message over the network  206  it is called a receiving client. Thus in normal operation, all client computers function as both sending and receiving clients.  
         [0037]    The present invention thus encourages a high level of participation and sharing of expertise by permitting users to maintain privacy and anonymity. User privacy is preserved by storing the user&#39;s  204  client profile  210  preferably only on the client computer  202  thereby encouraging users to permit the building of very rich profiles which go far beyond those users would otherwise voluntarily disclose to a central database. User anonymity is preserved by transmitting messages over the peer-to-peer network  226 .  
         [0038]    Message Filtering and Scoring  
         [0039]    For purpose of the discussion to follow, functionality within the client computer  202  for processing received messages is discussed as if the client computer  202  was one of the receiving client computers. Such a context switch is appropriate because preferably each client computer contains a complete and self contained version of the present invention&#39;s software.  
         [0040]    Thus in step  310 , the system module  234  within the client computer  202  retrieves, and commands a filtering/scoring module  238  to filter and score, newly received messages which have been stored in the messages database  236 .  
         [0041]    In order to perform filtering and scoring, the filtering/scoring module  238  compares the message with information stored in the user&#39;s  204  client profile  210 . If necessary however, the message may be compared with data stored elsewhere in the client computer  202 , such as in the e-mail client  230 , the e-mail messages  221 , the internet client  232 , the web page cache  217 , the client software  212 , the client files  214 , and the client messages  236 .  
         [0042]    A received message is filtered by the filtering/scoring module  238  when such message contains a predetermined set of criteria, inserted by the message sending client, in order to target selected receiving clients. Such filtering criteria is preferably very flexible and is left at the discretion of the sending client user. For example, the filtering criteria may look for a particular data string, or at some other information within a receiving client&#39;s client profile  210 .  
         [0043]    In an alternate embodiment however, a client profile  210  which does not meet the filtering criteria merely results in a low message score. In this way, a message which does not meet the filtering criteria does not automatically prevent the user  204  from seeing the message. In such embodiments an overall weighted average score may be generated which depends upon not only all of the filtering criteria, but also the message&#39;s score. How the message&#39;s score is generated is discussed next.  
         [0044]    The filtering/scoring module  238  preferably scores messages using statistical information retrieval techniques, including linguistic analysis. Information retrieval techniques are commonly known to be used for accessing and analyzing large blocks of data and then extracting all or selected portions of such data according to a wide variety of methods. Other techniques are also known to those skilled in the art.  
         [0045]    While the above filtering and scoring discussion assumes the message was received over the peer-to-peer network  226 , messages received over the e-mail network  222  as well as by other paths within the network  206  are similarly filtered and scored if the receiving client has the present invention&#39;s software installed.  
         [0046]    For example, receiving clients who have the present invention&#39;s software already installed and have received an e-mail message containing an embedded XML message, have a copy of the embedded message placed in their messages database  236  so that the message can be filtered and scored. Receiving clients who do not have the present invention&#39;s software installed, however, only see the e-mail message in their standard e-mail inbox, and no other processing is performed.  
         [0047]    Thus the filtering and scoring techniques of the present invention in combination with the rich client profiles stored on each receiving client&#39;s computer are together what enable messages to be brought to the attention of the right set of users.  
         [0048]    Such intelligently targeted messaging, however, also builds user confidence in and reliance on the present invention. This is because unlike in conventional systems where users often have to wade though in-boxes full of junk or marginally useful e-mail, users using the present invention generally know and rely on the fact that their time will not be wasted on such unimportant messages. Instead users of the present invention will be even more likely to timely respond to messages received because the messages will be so on-point to their expertise and/or interests.  
         [0049]    For example, in the past when a sending client needed to identify appropriate participants to participate in an experiment, or submit papers for a seminar, the user would clumsily post an advertisement on a web or other site, and/or send out a generalized e-mail to a very large distribution list. In such cases, targeted users often miss the importance of or are annoyed by such communications which are buried in a sea of information they already are trying to sift through. In contrast, the present invention automatically performs the necessary sifting so that if a user receives a message using the present invention, such message will be useful to them.  
         [0050]    Message Display and Response  
         [0051]    In step  312 , the received message is displayed to the receiving client if the message has not been filtered out and/or if the message score exceeds a predetermined threshold. Messages are preferably displayed to the receiving client according to their respective score. As discussed above, the score represents a likelihood that the receiving client will find the message relevant to or within their expertise.  
         [0052]    The receiving client then may select and respond to one of the messages. In step  314  a response from the receiving client is sent over the network  206  back to the sending client anonymously or in an encrypted format. After step  314  the preferred method ends.  
         [0053]    Message Traffic Analysis, Categorization, and Reporting  
         [0054]    [0054]FIG. 4 is a flowchart of one embodiment of a method  400  for message traffic analysis, categorization, and reporting. FIG. 5 is a dataflow diagram  500  of one embodiment of a server  502  for message traffic analysis, categorization, and reporting. FIGS. 4 and 5 are herein discussed together. The server  502  can either be a dedicated network server, or can be one of the client computers on the network  226  which has been nominated and configured for global network benefit. Preferably only client computers having superior processing power and storage capability are so nominated. The server  502  preferably includes: a server process  504 , a system module  506 , a network module  508 , a network protocol module  510 , and messages data area  512 . The messages data area  512  includes a messages database  514  and a message profile database  516 .  
         [0055]    While FIG. 5 shows only one server  502 , the present invention is equally functional when the peer-to-peer network  226  is supported by multiple, globally known servers, having similar functionality. Such multiple servers enhance the present invention by providing network fault tolerance, and increased network performance over geographically diverse networks. Such redundant servers are preferably mirrored, and client computers attempting to post messages to servers which are overloaded are preferably referred to other, less utilized servers.  
         [0056]    The method  400  begins in step  402  where the server process  504  stores copies of messages transmitted over the peer-to-peer network  226  in the messages database  514 . Preferably the server process  504  extracts or assigns a date/time stamp to each stored message. Next in step  404 , the server process  504  generates a message profile for each message stored in the messages database  514 . The message profile is preferably generated uses the same techniques of linguistic and statistical analysis, discussed earlier in this specification. As part of message profile generation, a set of keywords and key-phrases (herein commonly defined as “key-strings”) are identified within the message, as well as a frequency of occurrence for each key-string. The message profiles are stored in the message profile database  516 .  
         [0057]    In step  406 , the server process  504  receives a request to generate a report characterizing the message traffic transmitted over the peer-to-peer network  226 . This request may either be one of a set of fixed reports preprogrammed into the server data area  512 , or may be a custom request, received over the network  206 . The report request preferably includes a set of criteria which defines which messages should be included within the report and/or how messages should be categorized. Those skilled in the art know that there are almost an unlimited number of reports which may be generated from the messages stored in the message database  514 .  
         [0058]    Examples of preprogrammed fixed reports include: Frequently Asked Questions (FAQs) over a set of predefined time periods; FAQs having an inadequate number of responses (suggesting an enterprise knowledge deficiency); messages grouped by discussion topic; and recent messages grouped by their discussion topics (revealing the current “buzz” within the enterprise).  
         [0059]    Examples of custom reports include: Frequently Asked Questions (FAQs) over a specific time periods; messages containing specific key-strings; and messages inciting less than or greater than a specific number of responses.  
         [0060]    Such FAQ reports enable enterprises to address frequent knowledge needs on the part of specific enterprise sub-groups, such as new-employees and/or new-project members. For example, new employees typically have similar questions upon first joining an enterprise, yet often said employees don&#39;t even know where to begin to look to have their questions answered. Existing employees however can grow fatigued at answering the same new employee questions over and over again. Thus, using the present invention, a new employee FAQ list can be generated and automatically sent to the new employee on their first day. Similarly, employees may join a new project team and need to come up to speed on the issues and expertise of the team. Using the present invention, a new team member FAQ list can be generated and automatically sent to the new team member, so that they may proceed through the learning curve more efficaciously.  
         [0061]    Reports which address enterprise knowledge “deficiencies,” may be particularly useful to an enterprise, as such unanswered or infrequently answered questions may represent an unmet need for knowledge within the enterprise. Such an unmet need could perhaps then be remedied, through either targeted recruitment and/or employee training.  
         [0062]    Next in step  408 , the server process  504  searches through the message profile database  516  for profiles which most closely match the report&#39;s criteria.  
         [0063]    The criteria may include one or more of the following delimiters: message authorship information (i.e. any information available about the sending and receiving clients generating and responding to respectively transmitted messages); messages transmitted over particular time periods; messages containing particular key-strings; a frequency of message occurrence; message types (i.e. question, response, or topical); message threads; as well as any other well known delimiters used in database searching routines. The message authorship information can help generate reports which identify users who have sent or responded to a greater number of messages on a particular topic or within a particular time period. This would enable enterprises to further pinpoint areas of development and/or expertise.  
         [0064]    Preferably the server process  504  has access to a variety of analysis tools, such as a thesaurus and dictionary, so that messages which do not explicitly meet the search criteria are nonetheless included in the requested report if they are “similar enough” to the specified criteria. The “similar enough” standard is preferably explicitly defined using well known linguistic and statistical analysis techniques, but is determined empirically, during present invention product testing.  
         [0065]    Note that since messages are continually being added to the messages database  514 , and thus the message profile database  516  is being continually updated, the server process  504  is searching through a real-time set of data and thus the requested reports will be very timely and dynamic.  
         [0066]    In step  410 , the server process  504  retrieves and aggregates messages within the message database  514  corresponding to the message profiles identified within the message profile database  516  which met the report&#39;s search criteria.  
         [0067]    In step  412 , the server process  504  generates the requested report. After step  412 , the preferred method ends.  
         [0068]    The present invention thus enables enterprises to map the scope and depth of their organizational knowledge in a very timely, repetitive, and low cost manner, which further enables enterprises to be better informed and proactive in approaching new markets and new opportunities.  
         [0069]    Processing Information from Other Sources Using the Present Invention  
         [0070]    While the present invention has been discussed with respect to the generation, transmission and response to messages, the present inventions&#39; scoring functionality is equally applicable toward processing other types of information as well. Other information includes data displayed within a current web page being viewed by the user  204 . A relevance vector could be generated from said web page data and compared to the user&#39;s  204  expertise vector generated from the client profile  210 . User&#39;s would be notified of a particular relevance of the currently viewed web page if the relevance and expertise vectors when compared yield a score which exceeds a predetermined threshold. In this way user&#39;s browsing the web could be apprised of particular web pages which may closely align with their interests and/or expertise.  
         [0071]    Other information similarly processed and scored may include: normal e-mail messages which have not been generated using the present inventions&#39; functionality; files downloaded from the central server  224  or received from some other source; or expertise information stored on a central enterprise database. Those skilled in the art will know of other information sources to which the present invention may also be successfully applied.  
         [0072]    While one or more embodiments of the present invention have been described, those skilled in the art will recognize that various modifications may be made. Variations upon and modifications to these embodiments are provided by the present invention, which is limited only by the following claims.