NDLI: A Strategy of Semantic Information Extraction for Web Image

Content Provider	IEEE Xplore Digital Library
Author	Wenpeng Lu Ruojuan Xue Haixia Li Jianguo Wang
Copyright Year	2009
Abstract	In order to improve semantic information extraction coverage and quality of Web images, A novel approach is presented in this paper. Based on the habit of users to retrieve images, the model of representing image semantics is put forward. According to the model, a series of dictionaries are built, which include image topic, object and attribute dictionaries. Eight kinds of text are extracted as image semantic source from Web pages. Combining with semantic dictionaries, image semantic keywords can be extracted from the eight kinds of text. The strategy of extracting image semantics is better than existing technique, which is better than manual annotation in efficiency and better than automatic annotation based on content in accuracy. A performance experiment is presented which shows that high extraction coverage and quality can be achieved with this approach. The similar approaches could be applied to extract semantic information of other forms of multimedia.
Starting Page	480
Ending Page	483
File Size	328304
Page Count	4
File Format	PDF
ISBN	9780769537054
DOI	10.1109/BIFE.2009.115
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dictionaries Content based retrieval Image recognition Image retrieval Educational institutions image annotation Data mining Information technology Web images Information science Image analysis information extraction semantic dictionary Web pages image retrieval
Content Type	Text
Resource Type	Article

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