Abstract
We propose a novel probabilistic retrieval model which weights terms according to their contexts in documents. The term weighting function of our model is similar to the language model and the binary independence model. The retrospective experiments (i.e., relevance information is present) illustrate the potential of our probabilistic context-based retrieval where the precision at the top 30 documents is about 43% for TREC-6 data and 52% for TREC-7 data.
Original language | English |
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Title of host publication | SIGIR 2005 - Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval |
Pages | 663-664 |
Number of pages | 2 |
DOIs | |
Publication status | Published - 1 Dec 2005 |
Event | 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005 - Salvador, Brazil Duration: 15 Aug 2005 → 19 Aug 2005 |
Conference
Conference | 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005 |
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Country/Territory | Brazil |
City | Salvador |
Period | 15/08/05 → 19/08/05 |
Keywords
- context
- retrospective experiment
ASJC Scopus subject areas
- Information Systems