Learning to reformulate long queries

Long search queries are useful because they let the users specify their search criteria in more detail. However, the user often receives poor results in response to the long queries from today's Information Retrieval systems. For the document to be returned as a relevant result, the system requires every query term to appear in the document. This makes the search task especially challenging for those users who lack the domain knowledge or have limited search experience. They face the difficulty of selecting the exact keywords to carry out their search. The goal of our research is to help bridge that gap so that the search engine can help novice users formulate queries in a vocabulary that appears in the index of the relevant documents. We present a machine learning approach to automatically summarize long search queries, using word specific features that capture the discriminative ability of particular words for a search task. Instead of using hand-labeled training data, we automatically evaluate a search query using a query score specific to the task. We evaluate our approach using the task of searching for related academic articles.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2010

Author dc:creator

• Gupta, Neha, S.M. Massachusetts Institute of Technology

Advisor dc:contributor.advisor

• Tommi Jaakkola.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/60164

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/60164