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This paper proposes a novel two-stage image classification framework that aims to improve the performance of content-based image classification by utilizing context information of web-based images. A new TF*IDF weighting scheme is proposed to extract discriminant textual features from HTML surrounding texts. Both content-based and context-based classifiers are built by applying multiple correspondence analysis (MCA). Experiments on web-based images from Microsoft Research Asia (MSRA-MM) dataset show that the proposed framework achieves promising results.<\/p>","DOI":"10.4018\/jmdem.2011070103","type":"journal-article","created":{"date-parts":[[2011,10,19]],"date-time":"2011-10-19T16:41:45Z","timestamp":1319042505000},"page":"34-51","source":"Crossref","is-referenced-by-count":14,"title":["Utilizing Context Information to Enhance Content-Based Image Classification"],"prefix":"10.4018","volume":"2","author":[{"given":"Qiusha","family":"Zhu","sequence":"first","affiliation":[{"name":"University of Miami, USA"}]},{"given":"Lin","family":"Lin","sequence":"additional","affiliation":[{"name":"University of Miami, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0902-0844","authenticated-orcid":true,"given":"Mei-Ling","family":"Shyu","sequence":"additional","affiliation":[{"name":"University of Miami, USA"}]},{"given":"Dianting","family":"Liu","sequence":"additional","affiliation":[{"name":"University of Miami, USA"}]}],"member":"2432","reference":[{"key":"jmdem.2011070103-0","unstructured":"Cai, D., He, X., Ma, W.-Y., Wen, J., & Zhang, H. 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