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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2007.6
- 수록면
- 699 - 706 (8page)
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This article is an approach to improving the clustering of Web images by using high-level semantic features from text information relevant to Web images as well as low-level visual features of image itself. These high-level text features can be obtained from image URLs and file names, page titles, hyperlinks, and surrounding text. As a clustering algorithm, a self-organizing map (SOM) proposed by Kohonen is used. To evaluate the clustering efficiencies of SOMs, we propose a simple but effective measure indicating the accumulativeness of same class images and the perplexities of class distributions. Our approach is to advance the existing measures through defining and using new measures accumulativeness on the most superior clustering node and concentricity to evaluate clustering efficiencies of SOMs. The experimental results show that the high-level text features are more useful in SOM-based Web image clustering.
목차
ABSTRACT
1. INTRODUCTION
2. RELATED WORKS AND TECHNICAL BACKGROUNDS
3. SOM-BASED WEB IMAGE CLUSTERING
4. MEASURES FOR CLUSTERING EFFICIENCY
5. EXPERIMENTS AND EVALUATIONS
6. CONCLUSIONS
REFERENCES
참고문헌 (12)
참고문헌 신청
1. [학술지(정기간행물)] - Y. Rui / 1999 / Image Retrieval : Current Techniques, Promising Directions and Open Issues / Journal of Visual Communication and Image Representation 10 (4) : 39 ~ 62
2. [학술지(정기간행물)] - A.W.M. Smeulders / 2000 / Content-Based Image Retrieval at The End of The Early Years / IEEE Transactions on Pattern Analysis and Machine Intelligence 22 : 1349 ~ 1379
3. [학술지(정기간행물)] - N. Gudivada / 1995 / Content-Based Image Retrieval Systems / IEEE Computer 28 (9) : 18 ~ 22
4. [학술지(정기간행물)] - Z. Chen / 2001 / Web Mining for Web Image Retrieval / Journal of the American Society for Information Science and Technology 52 (10) : 831 ~ 839
5. [학술대회논문] - Y. Lu / 2000 / A Unified Framework for Semantics and Feature Based Relevance Feedback in Image Retrieval Systems / Proceedings of the 8th ACM international Conference on Multimedia : 31 ~ 38
2. [학술지(정기간행물)] - A.W.M. Smeulders / 2000 / Content-Based Image Retrieval at The End of The Early Years / IEEE Transactions on Pattern Analysis and Machine Intelligence 22 : 1349 ~ 1379
3. [학술지(정기간행물)] - N. Gudivada / 1995 / Content-Based Image Retrieval Systems / IEEE Computer 28 (9) : 18 ~ 22
4. [학술지(정기간행물)] - Z. Chen / 2001 / Web Mining for Web Image Retrieval / Journal of the American Society for Information Science and Technology 52 (10) : 831 ~ 839
5. [학술대회논문] - Y. Lu / 2000 / A Unified Framework for Semantics and Feature Based Relevance Feedback in Image Retrieval Systems / Proceedings of the 8th ACM international Conference on Multimedia : 31 ~ 38
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UCI(KEPA) : I410-ECN-0101-2012-004-004428127