Improving Web Search for Difficult Queries

Wang, Xuanhui

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https://hdl.handle.net/2142/13600 Copy

Description

Title

Improving Web Search for Difficult Queries

Author(s)

Wang, Xuanhui

Issue Date

2009-08-14

Doctoral Committee Chair(s)

Zhai, ChengXiang

Committee Member(s)

• Han, Jiawei
• Chang, Kevin C-C.
• Kumar, Ravi

Department of Study

Computer Science

Discipline

Computer Science

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Difficult queries
• query reformulation
• result organization
• negative feedback
• topic maps

Language

en

Abstract

Search engines have now become essential tools in all aspects of our life. Although a variety of information needs can be served very successfully, there are still a lot of queries that search engines can not answer very effectively and these queries always make users feel frustrated. Since it is quite often that users encounter such ``difficult queries,'' improving Web search for these queries can bring significant benefits to users. However, the problem has so far been under-addressed. In this dissertation, I propose to systematically study this problem from different perspectives, naturally corresponding to different stages of an interactive search process. Specifically, I propose to improve search quality for difficult queries by: (1) Effective query reformulation, i.e., improving a search engine in the stage of query formulation. A query is difficult because it does not contain the right keywords or lacks discriminative keywords. A better formulation of query by addressing vocabulary mismatch or improving discrimination can lead to better results. (2) User-oriented search result organization, i.e., improving a search engine in result presentation. Ambiguous queries are difficult and often lead to search results with mixed senses. Search result organization can make search results easily accessible for users. (3) Incorporating user negative feedback, i.e., improving a search engine by learning from user interactions. When a query is extremely difficult and all the top results (e.g., top 10) are totally irrelevant, the feedback that a user can provide would be solely negative. I propose to develop effective negative relevance feedback strategies to improve the ranking accuracy of the next few pages when the user clicks on the ``Next'' button. (4) Supporting effective browsing, i.e., allowing a user to find information without queries. Browsing is a complementary mechanism to querying and is especially important for difficult queries. I propose to construct a novel multi-resolution topic map to enable effective browsing beyond hyperlinks. In summary, my dissertation is to study how to improve search engines for difficult queries along all these four directions by exploiting both global massive search logs and immediate user feedback information.

Type of Resource

text

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http://hdl.handle.net/2142/13600

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