Constraint-Based Ontology Induction From Online Customer Reviews

Loading...
Thumbnail Image
Penn collection
Operations, Information and Decisions Papers
Degree type
Discipline
Subject
concept learning
knowledge acquisition
ontology
text analysis
text mining
Other Biochemistry, Biophysics, and Structural Biology
Other Education
Other Life Sciences
Technology and Innovation
Funder
Grant number
License
Copyright date
Distributor
Related resources
Author
Lee, Thomas
Contributor
Abstract

We present an unsupervised, domain-independent technique for inducing a product-specific ontology of product features based upon online customer reviews. We frame ontology induction as a logical assignment problem and solve it with a bounds consistency constrained logic program. Using shallow natural language processing techniques, reviews are parsed into phrase sequences where each phrase refers to a single concept. Traditional document clustering techniques are adapted to collect phrases into initial concepts. We generate a token graph for each initial concept cluster and find a maximal clique to define the corresponding logical set of concept sub-elements. The logic program assigns tokens to clique sub-elements. We apply the technique to several thousand digital camera customer reviews and evaluate the results by comparing them to the ontologies represented by several prominent online buying guides. Because our results are drawn directly from customer comments, differences between our automatically induced product features and those in extant guides may reflect opportunities for better managing customer-producer relationships rather than errors in the process.

Advisor
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Publication date
2007-05-01
Journal title
Group Decision and Negotiation
Volume number
Issue number
Publisher
Publisher DOI
Journal Issue
Comments
Recommended citation
Collection