An application of machine learning techniques to interactive, constraint-based search

MOspace/Manakin Repository

Breadcrumbs Navigation

An application of machine learning techniques to interactive, constraint-based search

Please use this identifier to cite or link to this item: http://hdl.handle.net/10355/4324

[-] show simple item record

dc.contributor.advisor Shang, Yi, 1967- en
dc.contributor.author Harbert, Christopher W. en_US
dc.date.accessioned 2010-01-12T16:47:12Z
dc.date.available 2010-01-12T16:47:12Z
dc.date.issued 2005 en_US
dc.date.submitted 2005 Fall en
dc.identifier.other HarbertC-051706-T3565 en_US
dc.identifier.uri http://hdl.handle.net/10355/4324
dc.description The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. en_US
dc.description Title from title screen of research.pdf file viewed on (December 12, 2006) en_US
dc.description Includes bibliographical references. en_US
dc.description Thesis (M.S.) University of Missouri-Columbia 2005. en_US
dc.description Dissertations, Academic -- University of Missouri--Columbia -- Computer science. en_US
dc.description.abstract Search engine users frequently place additional constraints on search results that are not included in the user's original query. To respond to these additional constraints, search engine designers frequently add an "advanced search" page. On these pages, the user supplies a set of constraints for the result items. While this is certainly more useful, it relies on two assumptions: that the user knows these constraints prior to the search, and that the constraints are independent. This is not always the case. This work presents a method to use an existing search engine to create an interactive, constraint-based search: the Query Expansion and Refinement Process (QUERP). In addition, this work provides an example of the method as applied to the popular eBay auction site. The experimental results show that using QUERP to provide an interactive, constraint-based search has the potential to provide higher precision and recall than the original search engine. en_US
dc.language.iso en_US en_US
dc.publisher University of Missouri--Columbia en_US
dc.relation.ispartof 2005 Freely available theses (MU) en_US
dc.subject.lcsh Computer users en_US
dc.subject.lcsh Search engines en_US
dc.subject.lcsh Constraints (Artificial intelligence) en_US
dc.title An application of machine learning techniques to interactive, constraint-based search en_US
dc.type Thesis en_US
thesis.degree.discipline Computer science en_US
thesis.degree.grantor University of Missouri--Columbia en_US
thesis.degree.name M.S. en_US
thesis.degree.level Masters en_US
dc.identifier.merlin .b57313404 en_US
dc.relation.ispartofcommunity University of Missouri-Columbia. Graduate School. Theses and Dissertations. Theses. 2005 Theses


This item appears in the following Collection(s)

[-] show simple item record