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Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/www2008/paper/707> ?p ?o. }

• 707 creator bhaskar-mehta.
• 707 creator manish-gupta.
• 707 creator saurabh-nangia.
• 707 type InProceedings.
• 707 label "Detecting Image Spam using Visual Features and Near Duplicate Detection".
• 707 sameAs 707.
• 707 abstract "Email spam is a much studied topic. Though current email spam detecting software has been winning the war against text based email spam, new advances in spam generation have posed a new challenge: image-based spam. Image based spam is email which contains embedded images which contain the spam messages, but in binary format. In this paper, we study the traits of image spam to propose two solutions for detecting image-based spam, while drawing a comparison with the existing techniques. The first solution, which uses the visual features for classification, offers an accuracy of about 98%, i.e. an improvement of at least 6% compared to the existing solutions. SVMs (Support Vector Machines) are used to train classifiers using judiciously decided color, texture and shape features. The second solution offers a novel approach for near duplication detection in images. It involves clustering of image GMMs (Gaussian Mixture Models) based on Agglomerative Information Bottleneck (AIB) principle, using Jensen-Shannon (JS) divergence as the distance measure.".
• 707 hasAuthorList authorList.
• 707 hasTopic World_Wide_Web.
• 707 isPartOf proceedings.
• 707 keyword "data mining".
• 707 keyword "email spam".
• 707 keyword "image analysis".
• 707 keyword "machine learning".
• 707 keyword "security".
• 707 title "Detecting Image Spam using Visual Features and Near Duplicate Detection".