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From: sorensen@csvax1.ucc.ie
Subject: CFP Wks. Pract. Appl. Information Filtering
Message-ID: <Dr363J.Ao9@curia.ucc.ie>
Sender: usenet@curia.ucc.ie
Reply-To: sorensen@csvax1.ucc.ie
Organization: Computer Science Dept. University College, Cork, Ireland.
Date: Wed, 8 May 1996 12:16:31 GMT
Lines: 115

               [Apologies for any cross-posting]

                          Call for Papers

      Workshop on Practical Applications of Information Filtering
      
                  to be held in conjunction with

 First International Conference on Practical Aspects of Knowledge Management 
                               (PAKM)

                         Basel, Switzerland

                        October 30-31, 1996


Information filtering is an aspect of knowledge management which has been the 
focus of concerted research in recent times. This has arisen because of the 
increasing volumes of electronically stored information being made available. 
Unlike information retrieval or data mining, both of which address problems 
associated with static document databases, filtering applies to transiently 
occurring information on a computer network. The basic aim of information 
filtering is to route through to a user those source documents deemed relevant 
to his/her needs, possibly ranking them by estimated relevance; documents 
deemed not to be relevant are filtered out. Estimation of relevance is carried 
out by comparing a user profile - embodying knowledge of a users ongoing
interests - with incoming documents in an information stream. It may be 
expected that, as a users interests change or evolve, the corresponding user
profile is adjusted accordingly. 

Example user scenarios in which information filtering would be an appropriate 
tool might include the following:

- A journalist in a newsroom may be following developments of a certain 
  story - or particular aspects of a story - over a prolonged time period. 
  As such, he/she may wish to have relevant newswire articles filtered 
  through. Also, as certain aspects of the story begin to assume 
  importance to the journalist, the nature of articles received might be 
  expected to change.

- A financial institution trades stock internationally. Beside the normal 
  world-wide monitoring of stock exchanges, it also needs to have knowledge 
  of world events which might affect stock prices: weather conditions in a 
  particular location; earthquakes; military coups; government changes or 
  collapses; interest rate changes. Toward this end, the institution may 
  employ people to monitor the API and FT newswires, pertinent USENET 
  Newsgroups, etc. 

- The manager of the Information Systems division of a company needs to 
  keep up to date regarding the relative benefits of a competing range of 
  software and hardware products. To do this, he/she wishes to monitor 
  computer mailing lists and USENET News to locate articles containing 
  meaningful comparisons. As with the other cases, the important issue is 
  that only relevant articles are presented, with irrelevant contributions 
  screened out, i.e., filtering takes place on the incoming information. 
  Also, as the manager's needs change (e.g. a hardware purchase is made or 
  a software product is eliminated from further consideration), the nature 
  of information being routed through should automatically adapt.


PAPERS:
The purpose of this workshop is to examine currently available practical 
applications of information filtering, to assess the impact of the technology, 
to evaluate its successes and failures and to appraise its future utility as 
a practical application of knowledge management. Papers are invited on any 
aspect of information filtering, but emphasis will be placed on real-world 
systems and approaches. It is thus desirable that the paper be linked to some 
specific user scenario, such as one of those listed above. A non-exhaustive 
list of topics is included below:

*  Applications of Filtering             *  Filter System Architectures
*  Profile / Document Representation     *  Profile / Document Comparison
*  Profile Adaptation                    *  Profile Optimisation
*  User Interfaces                       *  User Modelling
*  Evaluation Techniques                 *  Multimedia/Hypermedia Filtering

Paper Submission Details:
Paper Length:                  5000 words maximum
Submission Date:               June 28, 1996
Notification of Acceptance:    August 1, 1996
Final Papers Due:              September 15, 1996


DEMONSTRATIONS:
Software demonstrations related to the workshop topics are also encouraged. 
These may or may not be associated with a paper being presented. Conference 
organisers will provide a room where such demonstrations can be given during 
lunch breaks and at other times. Lunch, exhibitions and demonstrations will 
take place in the same or adjacent rooms.

Submission deadlines for software demonstrations are as for papers, given 
above.


PARTICIPATION:
Beside being open to people presenting papers and demonstrating systems, the 
workshop will be open to practitioners interested in concretely applying 
information filtering strategies. Workshop participants presenting a paper 
will, however, qualify for a reduced conference fee. Refer to the main 
conference's general information (URL below) for participation details.


ORGANISERS:
Alan Smeaton                            Humphrey Sorensen
School of Computer Applications,        Computer Science Department,
Dublin City University,                 University College,
Dublin 9,                               Cork,
Ireland.                                Ireland.
Alan.Smeaton@CompApp.DCU.IE             sorensen@odyssey.ucc.ie



   Web Information on PAKM Conference:
       http://expasy.hcuge.ch/sgaico/html/pakm.html

