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Title:Towards a characteristics-aware document search engine
Author(s):Pham, Long T
Advisor(s):Chang, Kevin C.C.
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):full text search, entity search, document retrieval, characteristics aware
Abstract:The increasing volume, heterogeneity, and redundancy of the Web create a novel challenge for search engines in which, target documents must satisfy some characteristics. It is increasingly important because there are more and more types of web pages on the Internet nowadays. Current web search engines are fundamentally incapable of addressing the user need because keywords can not express characteristics of target pages. Another alternative is to use vertical search engines, but they can only cover a few popular niches. Thus, we propose Forward Search to empower users with an engine to express not only topics but also characteristics of pages in their queries. Expected results are documents ranked by both topical and characteristic relevance. Creating Forward Search to have the focus of a vertical engine and the flexibility of web search presents many novel challenges. First, we must represent a document with novel information to support querying for characteristics. Second, we must index both keywords and named entities to quickly locate relevant pages of the target characteristics during query time. Third, we have to design a realistic method to acquire user input about the characteristics of target pages and retrieve documents ranked by both topical and characteristic relevance. Finally, since our system redefines relevance in traditional web search, we must rethink the user interface. This thesis comes with a web-based demonstration of our Forward Search at and five open-source code repositories at
Issue Date:2018-07-17
Rights Information:Copyright 2018 Long Pham
Date Available in IDEALS:2018-09-27
Date Deposited:2018-08

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