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Matches in ScholarlyData for { ?s ?p ?o. }

• authorList hasLastItem item-2.
• item-1 type ListItem.
• item-1 hasContent adrian-popescu.
• item-1 next item-2.
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• item-2 hasContent gregory-grefenstette.
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• 173 type InProceedings.
• 173 label "Link Based Small Sample Learning for Web Spam Detection".
• 173 sameAs 173.
• 173 abstract "Robust statistical learning based web spam detection sys- tem often requires large amounts of labeled training data. However, labeled samples are more difficult, expensive and time consuming to obtain than unlabeled ones. This pa- per proposed link based semi-supervised learning algorithms to boost the performance of a classifier, which integrates the traditional Self-training with the topological dependency based link learning. The experiments with a few labeled samples on standard WEBSPAM-UK2006 benchmark showed that the algorithms are effective.".
• 173 hasAuthorList authorList.
• 173 isPartOf proceedings.
• 173 keyword "Poster Session".
• 173 title "Link Based Small Sample Learning for Web Spam Detection".
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• item-1 hasContent guang-gang-geng.
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• item-2 type ListItem.
• item-2 hasContent qiudan-li.
• item-2 next item-3.
• item-2 previous item-1.
• item-3 type ListItem.
• item-3 hasContent xinchang-zhang.
• item-3 previous item-2.
• 174 type InProceedings.
• 174 label "Detecting Image Spam Using Local Invariant Features and Pyramid Match Kernel".
• 174 sameAs 174.
• 174 abstract "Image spam is a new obfuscating method which spammers invented to more effectively bypass conventional text based spam filters. In this paper, we extract local invariant features of images and run a one-class SVM classifier which uses the pyramid match kernel as the kernel function to detect image spam. Experimental results demonstrate that our algorithm is effective for fighting image spam.".
• 174 hasAuthorList authorList.
• 174 isPartOf proceedings.
• 174 keyword "Poster Session".
• 174 title "Detecting Image Spam Using Local Invariant Features and Pyramid Match Kernel".
• authorList type List.
• authorList hasFirstItem item-1.
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• authorList hasItem item-5.
• authorList hasLastItem item-5.
• item-1 type ListItem.
• item-1 hasContent haiqiang-zuo.
• item-1 next item-2.
• item-2 type ListItem.
• item-2 hasContent weiming-hu.
• item-2 next item-3.
• item-2 previous item-1.
• item-3 type ListItem.
• item-3 hasContent ou-wu.
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• item-4 type ListItem.
• item-4 hasContent yunfei-chen.
• item-4 next item-5.
• item-4 previous item-3.
• item-5 type ListItem.
• item-5 hasContent guan-luo.
• item-5 previous item-4.
• 175 type InProceedings.
• 175 label "Web Image Retrieval ReRanking with Multi-view Clustering".
• 175 sameAs 175.
• 175 abstract "General image retrieval is often carried out by a text-based search engine, such as Google Image Search. In this case, natural language queries are used as input to the search engine. Usually, the user queries are quite ambiguous and the returned results are not well-organized as the ranking often done by the popularity of an image. In order to address these problems, we propose to use both textual and visual contents of retrieved images to reRank web retrieved results. In particular, a machine learning technique, a multi-view clustering algorithm is proposed to reorganize the original results provided by the text-based search engine. Preliminary results validate the effectiveness of the proposed framework.".
• 175 hasAuthorList authorList.
• 175 isPartOf proceedings.
• 175 keyword "Poster Session".
• 175 title "Web Image Retrieval ReRanking with Multi-view Clustering".
• authorList type List.
• authorList hasFirstItem item-1.
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• authorList hasItem item-3.
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• authorList hasItem item-5.
• authorList hasLastItem item-5.
• item-1 type ListItem.
• item-1 hasContent mingmin-chi.
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• item-2 type ListItem.
• item-2 hasContent peiwu-zhang.
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• item-3 type ListItem.
• item-3 hasContent yingbin-zhao.
• item-3 next item-4.
• item-3 previous item-2.
• item-4 type ListItem.
• item-4 hasContent rui-feng.
• item-4 next item-5.
• item-4 previous item-3.
• item-5 type ListItem.
• item-5 hasContent xiangyang-xue.
• item-5 previous item-4.
• 176 type InProceedings.

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