Title :
Semantic Annotation and Search for Deep Web Services
Author :
Chun, Soon Ae ; Warner, Janice
Author_Institution :
Coll. of Staten Island, City Univ. of New York, Staten Island, NY
Abstract :
In this paper, we recognize the shortcomings of the current search engines that do not index and search the deep Web. We present requirements of a deep Web service search engine, that will lead to the query objects in the deep data sources. In order to realize the DWS search engine, we propose semantic metadata and annotation of deep Web services (DWS), a reasoning component to assess the relevance of DWS for searching the deep Web contents, using likelihood of occurrence of data sources that contain the query terms, and present a method of ranking the DWSs. The deep Web service annotation considers not only the service descriptions like any Web services, but also has the frequency distribution, clustering and semantic prediction functions that may guide the search for DWSs.
Keywords :
Web services; inference mechanisms; meta data; query processing; sampling methods; search engines; DWS search engine; Web service descriptor; deep Web service; deep data source; frequency distribution; query object; reasoning component; sampling method; semantic annotation; semantic metadata; semantic prediction function; Content based retrieval; Data mining; Educational institutions; Frequency; Information retrieval; Lakes; Performance analysis; Search engines; Semantic Web; Web services; Deep Web services; Semantic annotation crawler; frequency annotation; spatial and temporal annotation;
Conference_Titel :
E-Commerce Technology and the Fifth IEEE Conference on Enterprise Computing, E-Commerce and E-Services, 2008 10th IEEE Conference on
Conference_Location :
Washington, DC
Print_ISBN :
978-0-7695-3340-7
DOI :
10.1109/CECandEEE.2008.141