Abstract
INFOrmer is an intelligent filtering system, currently being applied to the management of USENET News articles. An individual may have one or more profiles, each representing a long-term interest of that user. The user profile is then used to measure the relevance of incoming articles and filter out irrelevant documents. A user profile may be modified as a result of relevance feedback, so that it adjusts to users' changing interests. This paper discusses the architecture of INFOrmer and covers the profile/document representation and comparison techniques adopted within the system.
| Original language | English |
|---|---|
| Pages (from-to) | 988-1006 |
| Number of pages | 19 |
| Journal | Journal of Universal Computer Science |
| Volume | 3 |
| Issue number | 8 |
| Publication status | Published - 1997 |
| Externally published | Yes |
Keywords
- Relevance feedback
- Semantic network
- Spreading activation
- Text filtering
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