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based spam topic detection strategy through keyword extraction. In particular, spam topic is detected by using the topic model of multiple features with the keywords of clues, which integrate the corresponding feature of News, BBS and Blog. We get the min cost of 0.282 through TDT4 evaluating corpus and the satisfaction of
This paper presents a keyword extraction technique that can be used for tracking topics over time. In our work, keywords are a set of significant words in an article that gives high-level description of its contents to readers. Identifying keywords from a large amount of on-line news data is very useful in that it can
This paper focuses mainly on meta information on the comment stream of a peculiar message from SNS (social network services). Owing to the extreme-level popularity of SNS, there may be a increase in the comments at a high rate immediately after a social message is posted. The application model for Meta information watch word channel is a procedure to screen the client exercises in interpersonal organizations,...
email content only to build keyword corpus, together with some text processing to handle obfuscation technique. The algorithm was evaluated using the CSDMC2010 SPAM corpus dataset that contained 4327 emails in the training dataset and 4292 emails in the testing dataset. The experimental results show that the proposed
The rapid increase in the size of digital image and video collections is urging for the development of efficient browsing and search tools that skip the subjective task of keyword indexing, paving the way for the ambitious and challenging idea of content based description of imagery. With this goal in mind the
Content-based filters (e.g. Keyword filters, heuristics filters, statistical learning filters, pattern recognition neural networks, and so on) use tokens, which are found during message content analysis, to separate spam from legitimate messages. The effectiveness of these token-based filters is due to the presence of
A method of multi-text fusion computation is discussed in this paper which extracts the common features automatically by using text fusion. When search the information in a special domain, the keywords are picked out by using relative sample muster fusion, keywords' flexible control is realized by regulating the
news and social media, extract events related to food hazards, and then organize the data in a structured format for easy consumption. We define an information template for food hazard event based on data from the Korean Ministry of Food and Drug Safety (MFDS), and use the template to aggregate informative keywords from
Genre classification for musical documents is conventionally based on keywords, statistical features or low-level acoustic features. Such features are either lack of in-depth information of music content or incomprehensible for music professionals. This paper proposed a classification scheme based on the correlation
Managing and searching facsimiles automatically is the key point to achieve OA (Office Automation). At present, there is a lack of method to establish index of fax, which is the basis of searches. Focus on official business faxes, this paper proposes an approach to create index of fax, using logo, stamp and keywords
With the rapid development of technology of multimedia, the traditional information retrieval techniques based on keywords are not sufficient, content - based image retrieval (CBIR) has been an active research topic. A new content based image retrieval method using the feature analysis of edge extraction and median
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