Recently most recommender systems have been developed to recommend items or documents based on user preferences for a particular user, but they have difficulty in deriving user preferences for users who have not rated many documents. In this paper we use dynamic expert groups which are automatically formed to recommend domainspecific documents for unspecified users. The group members have dynamic authority weights depending on their performance of the ranking evaluations. Human evaluations over web pages are very effective to find relevant information in a specific domain. In addition, we have tested several effectiveness measures on rank order to determine if the current top-ranked lists recommended by experts are reliable. We show simulation results to check the possibility of dynamic expert group models for recommender systems.
|Title of host publication||Research and Advanced Technology for Digital Libraries - 5th European Conference, ECDL 2001, Proceedings|
|Editors||Panos Constantopoulos, Panos Constantopoulos, Ingeborg T. Sølvberg|
|Number of pages||12|
|Publication status||Published - 2001|
|Event||5th European Conference on Research and Advanced Technology for Digital Libraries, ECDL 2001 - Darmstadt, Germany|
Duration: 2001 Sep 4 → 2001 Sep 9
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Other||5th European Conference on Research and Advanced Technology for Digital Libraries, ECDL 2001|
|Period||01/9/4 → 01/9/9|
Bibliographical notePublisher Copyright:
© Springer-Verlag Berlin Heidelberg 2001.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)