NDLI: Automatic Query Type Classification for Web Image Retrieval

Content Provider	IEEE Xplore Digital Library
Author	Keke Cai Jiajun Bu Chun Chen Peng Huang
Copyright Year	2007
Description	Author affiliation: Zhejiang Univ., Hangzhou (Keke Cai; Jiajun Bu; Chun Chen; Peng Huang)
Abstract	In this paper, a framework of query classification is proposed for text-based image retrieval. The classification process in this framework consists of three phases. In the first phase, two basic classifiers are employed to classify the image query into certain categories. They are easily implemented but have weak adaptability to various web image queries. Therefore, in the second phase, an expanded classifier is implemented to compensate for the possible incapability of the basic classifiers. In this step, the inferential relationships extracted by information flow (IF) are exploited to disclose the meaning underneath the image query, which makes the classification more accurate. In the third phase, the strengths of all three individual classifiers are leveraged together to achieve the most possible efficient classification. The experimental results prove the effectiveness of this framework in dealing with image query classification.
Starting Page	1021
Ending Page	1026
File Size	337682
Page Count	6
File Format	PDF
ISBN	0769527779
DOI	10.1109/MUE.2007.96
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-04-26
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Learning systems Image analysis Image retrieval Search engines Educational institutions Computational efficiency Internet Data mining Image classification
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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