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Knowledge-based data mining and classification algorithms require of systems that are able to extract textual attributes contained in raw text documents, and map them to structured knowledge sources (e.g. ontologies) so that they can be semantically analyzed. The system presented in this paper performs this tasks in an automatic way, relying on a predefined ontology which states the concepts in this...
Since the emergence of BLOG, it not only represents a new network technology, but also means the beginning of a new life style. How to utilize and mine the BLOG content which contains hidden sentiment and real-time update is a big challenge in the data-mining domain. As most of the existing method for network text's topic mining is achieved through clustering text's topic and label which are labeled...
With the rapid development of Internet technology, it is more convenient for people to communicate with each other at any time, public opinion is created on Internet and influences people's daily life deeply, for example the decision-making of government, organization and person. Network online comments which carry public opinion become a hotspot for researching during these years. In this paper,...
With the rapid growth of web data, people sometime need semantic similar information in order to obtain a clear outline of their interests, so recommendation is needed to provide relevant information to users' queries. In this paper, we propose a method to recommend semantic similar movies and stars to users' queries, styles and stories. The system measures the similarities between movies according...
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