Statistical Language Models for Information Retrieval systematically and critically reviews the existing work in applying statistical language models to information retrieval, summarizes their contributions, and points out outstanding challenges. Statistical language models have recently been successfully applied to many information retrieval problems. A great deal of recent work has shown that statistical language models not only lead to superior empirical performance, but also facilitate parameter tuning and open up possibilities for modeling non-traditional retrieval problems. In general, statistical language models provide a principled way of modeling various kinds of retrieval problems.
Tho book reviews the development of this language modeling approach. It surveys a wide range of retrieval models based on language modeling and attempts to make connections between this new family of models and traditional retrieval models. It summarizes the progress made so far in these models and point out remaining challenges to be solved to further increase their impact. It is written for readers who already have some basic knowledge about information retrieval. Some knowledge of probability and statistics such as the maximum likelihood estimator is helpful, but not a prerequisite to understanding the high-level discussion.
- ISBN13 9781601981868
- Publish Date 30 November 2008 (first published 1 January 2008)
- Publish Status Active
- Publish Country US
- Imprint now publishers Inc
- Format Paperback
- Pages 92
- Language English
- URL https://nowpublishers.com/article/Details/INR-008