With the development of the Internet, the World Wide Web has become an invaluable information source for most organizations. However, most documents available from the Web are in HTML form which is originally designed...With the development of the Internet, the World Wide Web has become an invaluable information source for most organizations. However, most documents available from the Web are in HTML form which is originally designed for document formatting with little consideration of its contents. Effectively extracting data from such documents remains a nontrivial task. In this paper, we present a schema-guided approach to extracting data from HTML pages. Under the approach, the user defines a schema specifying what to be extracted and provides sample mappings between the schema and the HTML page. The system will induce the mapping rules and generate a wrapper that takes the HTML page as input and produces the required data in the form of XML conforming to the user-defined schema. A prototype system implementing the approach has been developed. The preliminary experiments indicate that the proposed semi-automatic approach is not only easy to use but also able to produce a wrapper that extracts required data from inputted pages with high accuracy.展开更多
In this paper, a system is presented where documents are no longer identified bytheir file names. Instead, a document is represented by its semantics in terms of descriptor andcontent vector. The descriptor of a docum...In this paper, a system is presented where documents are no longer identified bytheir file names. Instead, a document is represented by its semantics in terms of descriptor andcontent vector. The descriptor of a document consists of a set of attributes, such as date of creation,its type, its size, annotations, etc. The content vector of a document consists of a set of termsextracted from the document. In this paper, a semantic document management system XBASEis designed and implemented based on the semantics and the functions of three main modules,X-Loader, X-Explorer and X-Query.展开更多
In this paper, we report our success in building efficient scalable classifiers by exploring the capabilities of modern relational database management systems(RDBMS).In addition to high classification accuracy, the un...In this paper, we report our success in building efficient scalable classifiers by exploring the capabilities of modern relational database management systems(RDBMS).In addition to high classification accuracy, the unique features of theapproach include its high training speed, linear scalability, and simplicity in implementation. More importantly,the major computation required in the approachcan be implemented using standard functions provided by the modern relational DBMS.Besides, with the effective rule pruning strategy, the algorithm proposed inthis paper can produce a compact set of classification rules. The results of experiments conducted for performance evaluation and analysis are presented.展开更多
文摘With the development of the Internet, the World Wide Web has become an invaluable information source for most organizations. However, most documents available from the Web are in HTML form which is originally designed for document formatting with little consideration of its contents. Effectively extracting data from such documents remains a nontrivial task. In this paper, we present a schema-guided approach to extracting data from HTML pages. Under the approach, the user defines a schema specifying what to be extracted and provides sample mappings between the schema and the HTML page. The system will induce the mapping rules and generate a wrapper that takes the HTML page as input and produces the required data in the form of XML conforming to the user-defined schema. A prototype system implementing the approach has been developed. The preliminary experiments indicate that the proposed semi-automatic approach is not only easy to use but also able to produce a wrapper that extracts required data from inputted pages with high accuracy.
文摘In this paper, a system is presented where documents are no longer identified bytheir file names. Instead, a document is represented by its semantics in terms of descriptor andcontent vector. The descriptor of a document consists of a set of attributes, such as date of creation,its type, its size, annotations, etc. The content vector of a document consists of a set of termsextracted from the document. In this paper, a semantic document management system XBASEis designed and implemented based on the semantics and the functions of three main modules,X-Loader, X-Explorer and X-Query.
文摘In this paper, we report our success in building efficient scalable classifiers by exploring the capabilities of modern relational database management systems(RDBMS).In addition to high classification accuracy, the unique features of theapproach include its high training speed, linear scalability, and simplicity in implementation. More importantly,the major computation required in the approachcan be implemented using standard functions provided by the modern relational DBMS.Besides, with the effective rule pruning strategy, the algorithm proposed inthis paper can produce a compact set of classification rules. The results of experiments conducted for performance evaluation and analysis are presented.
