Web-centric language models

We investigates language models for informational and navigational web search. Retrieval on the web is a task that differs substantially from ordinary ad hoc retrieval. We perform an analysis of prior probability of relevance for a wide range of non-content features, shedding further light on the importance of non-content features for web retrieval. Language models can naturally incorporate multiple document representations, as well as non-content information. For the former, we employ mixture language models based on document full-text, incoming anchor-text, and document titles. For the latter, we study a range of priors based on document length, URL structure, and link topology. We look at three types of topics—distillation, home page, and named page— as well as for a mixed query set. We find that the mixture models lead to considerable improvement of retrieval effectiveness for all topic types. The web-centric priors generally lead to further improvement of retrieval effect...

• Type: Conference
• Year: 2005
• Where: CIKM
• Authors: Jaap Kamps
• Keywords: Ad Hoc Retrieval, CIKM 2005, Language Models, Retrieval Effectiveness