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Concept-based patent image retrieval

Paper ID Volume ID Publish Year Pages File Format Full-Text
37961 45642 2012 12 PDF Available
Title
Concept-based patent image retrieval
Abstract

Recently, the intellectual property and information retrieval communities have shown increasing interest in patent image retrieval, which could further enhance the current practices of patent search. In this context, this article presents an approach for automatically extracting concept information describing the patent image content to support searchers during patent retrieval tasks. The proposed approach is based on a supervised machine learning framework, which relies upon image and text analysis techniques. Specifically, we extract textual and visual low-level features from patent images and train detectors, which are capable of identifying global concepts in patent figures. To evaluate this approach we have selected a dataset from the footwear domain and trained the concept detectors with different feature combinations. The results of the experiments show that the combination of textual and visual information of patent images demonstrates the best performance outperforming both single visual and textual features results. The outcome of this experiment provides a first evidence that concept detection can be applied in the domain of patent image retrieval and could be integrated in existing real world applications to support patent searching.

► Enhancement of patent information retrieval. ► Automatic extraction of concept information from patent images. ► Extraction of visual low-level features from patent images. ► Establishing that concept detection can be applied to support patent searching.

Keywords
Concepts; Visual; Textual; Patent; Classification; Content-based search; Retrieval; Drawings; Image; Search engine; Hybrid
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Publisher
Database: Elsevier - ScienceDirect
Journal: World Patent Information - Volume 34, Issue 4, December 2012, Pages 292–303
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us