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The development and maintenance of domain knowledge based system need a lot of manual operations, and with the increasing amount of contents in the system, it is more and more difficult to find the relevant information. The keyword based search usually can not return the accurate result. To solve these problems, this
Under grid environment, a resource discovery mechanism could dramatically affect both performance and efficiency of the system. Currently, however, since most models of grid discovery are centralized, keyword based matching ones, outcomes of discovery could seldom cater customers' needs. This paper puts forward a grid
generate and calculate the associated relations and their strengths between documents within a domain. Each document is represented by a bag of words and their weights. We first build domain knowledge background based on the association rules at keyword level, and then we apply those association rules to generate and
Currently, Web of Things is based on keyword matching which is not beneficial to the development regarding Web of Things. Accordingly, "Semantic Web of Things" is proposed. As far as Semantic Web of Things concerned, the information of things should be represented as ontology-based semantic annotation
when the sentence is analyzed. The goal is to put each noun and verb of the sentence on the right place on the tree. Taking this information into account, it is possible to solve the ambiguity problem for the query keywords and create the indicative summaries taking into account query words, and semantically related
The rise of semantic Web attracts more attention to the information retrieval method. In this paper we firstly discuss the traditional network search and semantic information retrieval. Then in accordance with keywords statistic, we propose a stochastic search based on EA and semantic Web. Moreover, with the
and semantics could be analyzed and matched. Semantic Web Prefetching is a technique that tries to analyze the semantics of the keywords provided by the user or the content of the web page. This paper is an effort to provide the state-of-the-art survey of various Semantic Web Prefetching Techniques.
Traditionally information retrieval consists mainly of determining which documents of a collection contain the keywords in the user query. However, a growing number of tasks, especially those related to Semantic Web technologies and applications rely on accurately measuring the similarity between documents and online
With the dramatic increasing number of available Web services, how to locate the right services is becoming a big challenge in pervasive environments. The Web services discovery mechanism of UDDI based on keywords and simple classification can not meet the current needs. A semantic distance between ontology concepts
eDonkey has become the most reliable and popular P2P file sharing software with largest users. But currently it is still a problem that how to find resources you need exactly and quickly. The traditional searching method which is based on keywords cannot fulfill the needs of people. The effective and promising method
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