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Due to the trend of diversification of media in social network, the deep learning of multimedia data is becoming more and more important. This paper analyzes the special tag information of image, audio and video data on the internet, and proposes an effective recognition method of multimedia data for social network. The method will provide a lot of data for the multimedia content analysis of social...
Information on the World Wide Web is congested with large amounts of news contents. Recommendation, filtering, and summarization of Web news have received much attention in Web intelligence, aiming to find interesting news and summarize concise content for users. In this paper, we present our research on developing the Personalized News Filtering and Summarization system (PNFS). An embedded learning...
Keyphrase extraction is a fundamental research task in natural language processing and text mining. A limitation of previous keyphrase extraction methods based on semantic analysis is that the acquisition of the semantic features within phrases is restricted by the constructed thesaurus and language. An approach to the acquisition of the semantic features within phrases from a single document is proposed...
The news filtering and summarization (NFAS) system can automatically recognize Web news pages, retrieve each news page's title and news content, and extract key phrases. This extraction method substantially outperforms methods based on term frequency and lexical chains.
This paper presents a new keyword extraction algorithm for Chinese news Web pages using lexical chains and word co-occurrence combined with frequency features, cohesion features, and corelation features. A lexical chain is an external performance consistency by semantically related words of a text, and is the representation of the semantic content of a portion of the text. Word co-occurrence distribution...
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