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The growth of the Semantic Web has seen a rapid increase in the amount of Semantic Web data. Meanwhile, the demand for access to Semantic Web data without detailed knowledge of RDF query languages is increasing. In this paper, an approach which can return ranked answers to keyword query without the help of data schema
more accurately and simply. RDF is a language for representing metadata. An enormous number of keywords on the semantic Web are very important to make practical applications of the semantic Web because most users prefer to search with keywords. In this paper, we classify queries with keyword conditions into three patterns
With the rapid increase of XML documents on the web, how to index, store and retrieve these documents has become a very popular and valuable problem. At present, there are two normal ways of retrieving XML documents. One is structure-based retrieval; the other is keyword-based retrieval. However, XML keyword search is
Metacat to improve metadata search in multiple ways: (i) by expanding standard keyword searches with ontology term hierarchies; (ii) by allowing keyword searches to be applied to annotations in addition to traditional meta-data; and (iii) by allowing more structured searches over annotations via ontology terms. We describe
popularity and co-occurrence data. We describe a prototype that leverages the Wikipedia category structure to allow a user to semantically navigate pages from the Delicious social bookmarking service. In our system a user can perform an ordinary keyword search and browse relevant pages but is also given the ability to broaden
The proliferation of Web services demands for a discovery mechanism to find advertisements that satisfy the requests more accurately. OWL-S provides a capability-based description and logic inference mechanism for semantically matching. UDDI provides a registry of businesses and Web services, but its keyword search
confusion of information, disguise, and invalidation of correlation weighing when current text mining techniques based on keyword search are employed to conduct technology forecasting. In this paper, we present a three-layer model of smart technology forecasting based on text mining consisting of the collection layer, the
Various researchers have recognized that ontology based retrieval is one of the best in terms of precision and recall for semantic search engine. However, they did not specify explicitly any scheme/ algorithm for ontology based indexing and retrieval. This motivates us to conceive a proposal that includes (a) suggesting indexing algorithm to effectively maintain ontologies, (b) suggesting retrieving...
Linked Open Data (LOD) is becoming an essential part of the Semantic Web. Although LOD has amassed large quantities of structured data from diverse, openly available data sources, there is still a lack of user-friendly interfaces and mechanisms for exploring this huge resource. In this paper we highlight two critical issues related to the exploration of the semantic LOD pool by end users. We introduce...
XML has become an important format for exchange data. Ranking of XML search results directly relates to XML information retrieval performance. Most of the existing ranking models consider words statistical characteristics in the XML document, but they do not consider position of the node a word belongs to. That is to say, all of nodes in XML document have the equal importance. However, different node...
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