Matches in ScholarlyData for { ?s ?p ?o. }
- 694 keyword "mutual reinforcement".
- 694 keyword "opinion mining".
- 694 keyword "opinion word".
- 694 keyword "product feature".
- 694 title "Hidden Sentiment Association in Chinese Web Opinion Mining".
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- item-5 hasContent xian-wu.
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- item-6 hasContent xiaoxun-zhang.
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- 706 creator arpita-ghosh.
- 706 creator mohammad-mahdian.
- 706 type InProceedings.
- 706 label "Externalities in Online Advertising".
- 706 sameAs 706.
- 706 abstract "Most models for online advertising assume that an advertiser's value from winning an ad auction, which depends on the clickthrough rate or conversion rate of the advertisement, is independent of other advertisements served alongside it in the same session. This ignores an important {\em externality effect}: as the advertising audience has a limited attention span, a high-quality ad on a page can detract attention from other ads on the same page. That is, the utility to a winner in such an auction also depends on the set of other winners. In this paper, we introduce the problem of modeling externalities in online advertising, and study the winner determination problem in these models. Our models are based on choice models on the audience side. We show that in the most general case, the winner determination problem is hard even to approximate. However, we give an approximation algorithm for this problem with an approximation factor that is logarithmic in the ratio of the maximum to the minimum bid. Furthermore, we show that there are some interesting special cases, such as the case where the audience preferences are single peaked, where the problem can be solved exactly in polynomial time. For all these algorithms, we prove that the winner determination algorithm can be combined with VCG-style payments to yield truthful mechanisms.".
- 706 hasAuthorList authorList.
- 706 hasTopic World_Wide_Web.
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- 706 keyword "auctions".
- 706 keyword "computational hardness".
- 706 keyword "externalities".
- 706 keyword "online advertising".
- 706 keyword "winner determination problem".
- 706 title "Externalities in Online Advertising".
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- item-1 hasContent arpita-ghosh.
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- 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.
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- 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".
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- item-1 hasContent bhaskar-mehta.
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