Wessel Kraaij
Abstract
Search engine technology builds on theoretical and empirical research results in the area of information retrieval (IR). This dissertation makes a contribution to the field of language modeling (LM) for IR, which views both queries and documents as instances of a unigram language model and defines the matching function between a query and each document as the probability that the query terms are generated by the document language model. The work described is concerned with three research issues.
Index Terms
- Variations on language modeling for information retrieval
Recommendations
Structured queries, language modeling, and relevance modeling in cross-language information retrieval
Special issue: Cross-language information retrievalTwo probabilistic approaches to cross-lingual retrieval are in wide use today, those based on probabilistic models of relevance, as exemplified by INQUERY, and those based on language modeling. INQUERY, as a query net model, allows the easy ...
Improving the effectiveness of language modeling approaches to information retrieval: bridging the theory-effectiveness gap
Improving the effectiveness of general retrieval models has been a long-standing difficult challenge in information retrieval research, yet is also a fundamentally important task, because an improved general retrieval model would benefit every search ...
Comments