The Internet presents numerous sources of useful information nowadays. However, these resources are drowning under the dynamic Web, so accurate finding user-specific information is very difficult. In this paper we dis...The Internet presents numerous sources of useful information nowadays. However, these resources are drowning under the dynamic Web, so accurate finding user-specific information is very difficult. In this paper we discuss a Semantic Graph Web Search (SGWS) algorithm in topic-specific resource discovery on the Web. This method combines the use of hyperlinks, characteristics of Web graph and semantic term weights. We implement the algorithm to find Chinese medical information from the Internet. Our study showed that it has better precision than traditional IR (Information Retrieval) methods and traditional search engines. Key words HITS - evolution web graph - power law distribution - context analysis CLC number TP 391 - TP 393 Foundation item: Supported by the National High-Performance Computation Fund (00303)Biography: Ye Wei-guo (1970-), male, Ph. D candidate, research direction: Web information mining, network security, artificial intelligence.展开更多
文摘The Internet presents numerous sources of useful information nowadays. However, these resources are drowning under the dynamic Web, so accurate finding user-specific information is very difficult. In this paper we discuss a Semantic Graph Web Search (SGWS) algorithm in topic-specific resource discovery on the Web. This method combines the use of hyperlinks, characteristics of Web graph and semantic term weights. We implement the algorithm to find Chinese medical information from the Internet. Our study showed that it has better precision than traditional IR (Information Retrieval) methods and traditional search engines. Key words HITS - evolution web graph - power law distribution - context analysis CLC number TP 391 - TP 393 Foundation item: Supported by the National High-Performance Computation Fund (00303)Biography: Ye Wei-guo (1970-), male, Ph. D candidate, research direction: Web information mining, network security, artificial intelligence.
