Glance, N.S., Arregui, D., Dardenne, M. Making Recommender Systems Work for Organizations. Proceedings of PAAM'99 (London UK, April 1999).  Home/Search   Document Details and Download   Summary   Related Articles   Check

.... include components that facilitate the formation and the sustainability of social structures (groups and communities) trust and reputation or collaborative activities such as: 1) group formation systems (directories, matching services) 2) recommender opinion systems, reputation systems [17][18], social activity visualization [19] which contribute to the transparency and therefore to the social motivation, the adoption of share values and the construction of trust; 3) coordination systems (negotiation systems, conflict resolution systems, group decision systems, voting systems) which ....

Glance, N., Arregui, D., and Dardenne M., "Making Recommender Systems Work for Organizations". In Proceedings of PAAM'99, London April 1999.

....Buddy systems like ICQ or the AOL Instant Messenger provide detailed awareness information [3] Online communities provide a place to communicate, awareness and a rich functionality for storing and retrieving (community) information. Recommender systems like Movie Critic , Knowledge Pump [4, 5] or Jester [6] do matchmaking on the basis of user profiles and then provide recommendations based on ratings of other community members. Other systems like Referral Web [7] and Yenta [8, 9] focus on expert finding and explicit matchmaking. The problem with all these systems is, that they do not ....

N. S. Glance, D. Arregui, and M. Dardenne, "Making recommender systems work for organizations," in Proc. Intl. Conf. on Practical Application of Intelligent Agents and Multi-Agents (PAAM), Apr. 1999.

....and that users are likely to be interested in only some of them. By considering each domain separately, the matrix (reviewed documents users) tends to become more dense, and the confidence measure associated to the prediction increases. Such approach is used, for example in the Knowledge Pump [3, 4] and in the GroupLens [6] systems. Hybrid systems. In hybrid systems, the collaborative approach based on neighbor identification is complemented by content based analysis. This approach leverages the fact that content analysis can be performed on every document, independently of the number of ....

....at supporting the low cost provision of recommendations, ratings and comments by users, and to make the recommendation activity more directly and clearly beneficial to the user. This approach is based on the consideration that the provision of recommendations can be considered as a common good [3, 4, 5, 14], likely to be happily consumed, but unlikely to be happily maintained and nursed. Some ergonomic approaches to alleviate the common good problem are presented below. Immediate perceived benefit. The act of recommending can be considered either as being primarily an altruistic activity, or as an ....

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N. Glance, D. Arregui, M. Dardenne "Making Recommender Systems Work for Organizations", Proceedings of PAAM'99, 1999.

....hierarchy by all the users is just like allowing a stranger to organize your desktop (Maarek et. al, 1996) Most people would not accept to relinquish control of their bookmarks to others. When using systems that impose the use of a uniquehierarchy by all users, such as the case of Knowledge Pump (Glance et al. 1999) and Pharos (Bouthors et. al, 1999) users will be obliged to maintain two different bookmaring systems, a personal one and a group oriented one. This clear separation of cooperative tools and individual tools that do the same task, is one factor that leads to collaborative applications failure ....

Glance, N., Arregui, D., and Dardenne M. (1999) Making Recommender Systems Work for Organizations. In Proceedings of PAAM'99, London April 1999.

....medium. Buddy systems like ICQ or the AOL Instant Messenger provide detailed awareness information. Online communities provide a place to communicate, awareness and a rich functionality for storing and retrieving (community) information. Recommender systems like MovieCritic # , Knowledge Pump (Glance, Arregui, Dardenne 1998; 1999) or Jester (Goldberg et al. 1999) do matchmaking on the basis of a user profile and then provide recommendations based on ratings of other community members. Other systems like Referral Web (Kautz, Selman, Shah 1997) and Yenta (Foner 1997; 1999) are focused towards expert finding and explicit ....

....it determines what information may be helpful for the user to perform the current task. The knowledge pump sends a request for this information to different information sources including the communities. The functionality of a knowledge pump is shown by the example of the Xerox Knowledge Pump in (Glance, Arregui, Dardenne 1998; 1999). # Foundation for Intelligent Physical Agents; for more information see http: www.fipa.org # For the semantics and pragmatics part agent communication languages usually make use of speech act concepts. 4.3 Community Agency The main task of a community agency is to support information ....

Glance, N. S.; Arregui, D.; and Dardenne, M. (1999). Making recommender systems work for organizations. In Proc. Intl. Conf. on Practical Application of Intelligent Agents and Multi-Agents (PAAM).

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N. Glance, D. Arregui, and M. Dardenne. Making recommender systems work for organizations. In Proceedings of PAAM'99, London, UK, April 19-21, 1999.

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Glance, N., Arregui, D. and Dardenne M., "Making recommender systems work for organizations," in Proceedings of PAAM99 (London, UK, April 1999.

....systems. In all of these cases, the document collections provide an implicit way of associating content with users and potentially with communities of users. The most useful document collections in the context of this approach are those provided by community recommender systems [3,4] which attach user ids, community categorizations, and user ratings to documents. This allows the most sophisticated forms of the user and community profiling techniques described below. Ideally, a community based relevance feedback system based on the architecture described would ....

Glance, N., Arregui, D. and Dardenne, M. Making Recommender Systems Work for Organizations. In Proceedings of PAAM'99 , London, UK, April 1999.

....query, using primarily statistical techniques to match WWW pages to queries. More recent work has taken advantage of collaborative user behavior, user ratings and or document hyperlinks to deduce the quality of a WWW page deemed relevant to a given user s query (e.g. Delgaldo, Ishii and Ura 1998; Glance, Arregui, Dardenne 1999; Kleinberg 1998; Page 1997) The next step is to address users fundamental problem: how to help them specify their information need accurately and in such a way that the search engine can best answer their need. A recent analysis of online searches in a library setting has found that almost ....

....greatly. As a result, these methods are viewed critically by on line search systems (Fitzpatrick and Dent 1997) In a similar vein, Nichols, Twidale and Paice 1997) propose to complement search results with data items from other users search sessions that are similar to the session in progress. (Glance et al. 1999) propose that search results be re ranked against a community profile, which is itself incrementally constructed on the basis of relevance feedback provided by its members over time. Other research work has focused on collaborative judgments on the quality of WWW pages. For example, Jon Kleinberg ....

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Glance, N., Arregui, D. and Dardenne, D. 1999. Making recommender systems work for organizations. In Proceedings of PAAM'99, London, England.

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Glance, N.S., Arregui, D., Dardenne, M. Making Recommender Systems Work for Organizations. Proceedings of PAAM'99 (London UK, April 1999).

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N. Glance, D. Arregui, M. Dardenne. Making Recommender Systems Work for Organizations. In Proceedings of PAAM'99, 1999.

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Glance N., Arregui D. and Dardenne M.: Making Recommender Systems Work for Organizations, in Proceedings of PAAM'99 (London UK, April 1999).

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# Glance, N., Arregui, D., and Dardenne M. (1999) Making Recommender Systems Work for Organizations. In Proceedings of PAAM'99, London April 1999.

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