Document quality models for web ad hoc retrieval
Proceedings of the 14th ACM International Conference on Information and Knowledge Management, page 331--332. New York, NY, USA, ACM, (2005)DOI: 10.1145/1099554.1099652
Abstract
The quality of document content, which is an issue that is usually ignored for the traditional ad hoc retrieval task, is a critical issue for Web search. Web pages have a huge variation in quality relative to, for example, newswire articles. To address this problem, we propose a document quality language model approach that is incorporated into the basic query likelihood retrieval model in the form of a prior probability. Our results demonstrate that, on average, the new model is significantly better than the baseline (query likelihood model) in terms of precision at the top ranks.
