Compression-based document length prior for language models

The inclusion of document length factors has been a major topic in the development of retrieval models. We believe that current models can be further improved by more refined estimations of the document’s scope. In this poster we present a new document length prior that uses the size of the compressed document. This new prior is introduced in the context of Language Modeling with Dirichlet smoothing. The evaluation performed on several collections shows significant improvements in effectiveness. Categories and Subject Descriptors: H.3.3 [Information Search and Retrieval]: Retrieval models General Terms: Performance, Experimentation.

• Type: Conference
• Year: 2009
• Where: SIGIR
• Authors: Javier Parapar, David E. Losada, Alvaro Barreiro
• Keywords: Document Length, Document Length Factors, Information Retrieval, Retrieval Models, SIGIR 2009