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With the advent of Web 2.0, RESTful web services are becoming increasingly popular to emphasize the web as platform. There are already many RESTful web services and the number of services is increasing rapidly. Thus, it can be difficult to find specific services using keyword based retrieval. To solve this problem, a
be either a keyword list as in traditional search methods or a query in complex form containing various restrictions to the search, is first processed by a query parser which then finds qualified RDF triples in domain ontologies. Web documents relevant to the requested concepts and individuals specified in these triples
In this paper, we present a method we implemented to help a user index documents (and, in particular, learning objects) according to a given set of concepts (terms referring to domains or topics). The user first associates keywords to the concepts. Our method uses such associations to suggest simple rules for indexing
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
This paper describes a new approach of enhancing textual document search and retrieval. The approach tries to take advantage of structured query languages in search and retrieval. For this purpose the semantic model of the document is created. The semantic model of the document is an ontology-like structured semantic annotation of the document that can support structured querying. This paper discusses...
the current Web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. So this paper present a algorithm of Chinese text classification on semantic Web. After getting keywords from the Web text, we get rid of ambiguity of the keywords. Then we get the semantic
In order to overcome the defects of traditional-method filtering which based on keywords, the OWL text filtering is presented in the semantic Web environment, which makes information filtering, has been raised to the level of semantics. Through distinguishing the information between the title and text, and then
domain special ontology, grammatical knowledge of text could be acquired easily, and the latter is more determinate than the former. In the area of Information Retrieval, it is not enough to search information only based on keywords. Under this situation should we consider some web application can employ grammatical
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.