USER MODELS AND FILTERING AGENTS FOR IMPROVED INTERNET INFORMATION-RETRIEVAL

Over the past few years, the amount of electronic information availabl e through the Internet has increased dramatically. Unfortunately, the search tools currently available for retrieving and filtering informat ion in this space are not effective in balancing relevance and compreh ensiveness. This paper analyzes the results of experiments in which HT ML, documents are searched with user models and software agents used a s intermediaries to the search. Simple user models are first combined with search specifications (or 'User Needs'), to define an Enhanced Us er Need. Then Uniform Resource Agents are constructed to filter inform ation based on the EUN parameters. The results of searches using diffe rent agents are then compared to those obtained through a comparable s imple keyword search, and it is shown that a user searching a pool of existing agents can obtain better search results than by conducting a traditional keyword search. This work thus demonstrates that the use o f user models and information filtering agents do improve search resul ts and may be used to improve Internet information retrieval.