Titlebook: Web-Age Information Management; 12th International C Haixun Wang,Shijun Li,Tieyun Qian Conference proceedings 2011 The Editor(s) (if applic

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音樂(lè)學(xué)者

Lament

General-Purpose Ontology Enrichment from the WWWpecific domain. In this paper we present an automatic statistical/semantic framework for enriching general-purpose ontologies from the World Wide Web (WWW). Using the massive amount of information encoded in texts on the web as a corpus, missing background knowledge such as concepts, instances and r

Left-Atrium

jumble

QuerySem: Deriving Query Semantics Based on Multiple Ontologieskeyword-based indexing techniques to index Web Pages. Although this approach assist users in finding information on the Web, many of the returned results are irrelevant to the user’s information needs. This is because of the “semantic-gap” between the meanings of the keywords that are used to index

frivolous

MFCluster: Mining Maximal Fault-Tolerant Constant Row Biclusters in Microarray Datasetver, due to the influence of experimental noise in the microarray dataset, using traditional biclustering methods may neglect some significative biological biclusters. In order to reduce the influence of noise and find more types of biological biclusters, we propose an algorithm, ., to mine fault-to

Directed

Getting Critical Categories of a Data Setting work on ranking query focuses on getting top-. high-score tuples from a data set, this paper focuses on getting top-. critical categories from a data set, where each category is a data item in the nominal attribute or a combination of data items from more than one nominal attribute. To describe

歡呼

Expansion Finding for Given Acronyms Using Conditional Random Fieldsthe task of finding expansions in texts for given acronym queries. We formulate the expansion finding problem as a sequence labeling task and use Conditional Random Fields to solve it. Since it is a complex task, our method tries to enhance the performance from two aspects. First,we introduce nonlin

Cleave

MFCluster: Mining Maximal Fault-Tolerant Constant Row Biclusters in Microarray Datasetver, due to the influence of experimental noise in the microarray dataset, using traditional biclustering methods may neglect some significative biological biclusters. In order to reduce the influence of noise and find more types of biological biclusters, we propose an algorithm, ., to mine fault-to