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A Design And Implement Of Internet Intelligence Mining System About Semantic-based Information Extraction

Posted on:2011-11-11Degree:MasterType:Thesis
Country:ChinaCandidate:C H HuangFull Text:PDF
GTID:2178360302474674Subject:Computer application technology
Abstract/Summary:PDF Full Text Request
With development of Internet, web has become the biggest open data resource in the world. People can achieve information from web, connect others by web and share their resource on web and so on. But the web resource database are such large that how to get the information satisfied with user's demand quickly and exactly is an urgent problem. To solve this problem, a new technology named "Web Data Mining" was introduced in information retrieval domain, and it was paid much attention by investigators with the development of web. Web data mining is built on the base of information retrieval, data mining and knowledge management, and achieve implied knowledge and pattern by analyzing large number of web documents, so that it can improve information retrieval and decision making.This paper analyze the recent investigated content and progressivity in the domain of wed data mining, then design and realize a web information mining on semantic-based information extraction. The concrete content includes as follow:1. Implement and analyze some subsystem modules, such as web pages crawling, main contents extraction from web pages, natural language processing and key words extraction.2. Put forward and implement a semantic relational graph construction model, which employ graph to express semantic relationship in non-structured text data.3. Realize a frequent subgraph mining algorithm, which is different with DFS and BFS algorithms, and is more efficient than them. This paper employ the algorithm for mining frequent semantic subgraph, then get some objective results.4. Inventing a RDF searching algorithm on Linked Data, which is used to explain frequent subgraph, then get the results with relationship label.
Keywords/Search Tags:Web Data Mining, clawing program, natural language processing, frequent subgraph mining, semantic relation graph, Linked Data
PDF Full Text Request
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