Towards an adaptive information retrieval system

Goker A., McCluskey T.

6th International Symposium on Methodologies for Intelligent Systems, ISMIS 1991, North Carolina, Amerika Birleşik Devletleri, 16 - 19 Ekim 1991, cilt.542 LNAI Part F2, ss.348-357, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 542 LNAI Part F2
  • Doi Numarası: 10.1007/3-540-54563-8_98
  • Basıldığı Şehir: North Carolina
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.348-357
  • Çanakkale Onsekiz Mart Üniversitesi Adresli: Hayır

Özet

Standard Information Retrieval Systems (IRS) can be used to retrieve information in response to specific requests, but they have no powers of adaption to particular users over repeated sessions. This paper describes a learning system which uses relevance feedback from a probabilistic IRS to incrementally evolve a context for a user, over a number of online sessions. We demonstrate the learning implementation with an example, and argue that it can help an IRS adapt to a user's specific needs, by using this context to influence document display and selection.