What friends are for: collaborative intelligence analysis and search
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Authors
Wood, Christopher J.
Subjects
Intelligence Community
information retrieval
recommender systems
search engines
social networks
user profiling
Lucene
robust design
collaborative systems
information retrieval
recommender systems
search engines
social networks
user profiling
Lucene
robust design
collaborative systems
Advisors
Dimitrov, Nedialko B.
Kress, Moshe
Date of Issue
2014-06
Date
Jun-14
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
Intelligence analysts face a glut of information and limited time to identify which information is relevant. Also, they are unaware of other analysts with similar intelligence problems, preventing collaboration and often causing intelligence failure. To identify relevant information, analysts use adopted commercial search engines designed for internet-sized databases containing hyperlinked web-pages that are not effective on intelligence databases consisting of non-hyperlinked documents. This thesis outlines a model to fundamentally increase search effectiveness and collaboration by using a social network of like-minded users based on user biographies and search behavior. After entering a query, the likelihood of returning a relevant document is increased by leveraging data from other, similar users. The model goes beyond standard search engine design by presenting similar analysts for collaboration and presenting relevant documents without queries. Our framework is mathematically grounded in a Markov random field information retrieval model and recent developments in recommender systems. We build and test a prototype system on datasets from the National Institute of Standards & Technology. The test results combine with computational sensitivity analyses to show significant improvements over existing search models. The improvements are shown to be robust to high levels of human error and low similarity between users.
Type
Thesis
Description
Series/Report No
Department
Operations Research
Organization
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.