Learning Based Web Query ProcessingYanlei Diao
Computer Science Department
Hong Kong U. of Science & Technology
Learning Based Web Query Processing
FACT: A Prototype System
Preliminary System Evaluation
Demonstration Searching the WebWant to find a piece of information on the Web?Huge Size HeterogeneityLack of
Changing Search EnginesMaintain indices, keyword input, match input keywords with indices, return relevant documents.
Large hit lists with low precision. Users find relevant documents by browsing.
URLs but not the required information are returned. Users read the pages for the required information. Web Information RetrievalIR: Vector-space model, search and browse capabilities
Web IR: Web navigation, indexing, query languages, query-document matching, output ranking, user relevance feedback
Recent Improvement: Hierarchical classification, better presentation of results, hypertext study, metasearching... Web IR for Query ProcessingProblems
A list of URLs or documents is returned. Users browse a lot to find information.
It asks users for precise query requirements, which is hard for casual users.
It lacks a well-defined underlying model. Vector-space model does not convey as much as Hypertext.
Large hit lists with low precision, rely on input queries ...