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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
? Doesn't it understand it now? Google is very good at correcting typing mistakes, figuring out what I “meant” when I miss-typed a query or suggesting keyword to expand our search query. In this paper we redefine the idea of searching optimised information on the web using Capture-Recapture method. This paper
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
The representation and organization of learning objects should provide the user with easy access to the information in which he or she is interested. Traditionally information retrieval systems support keyword-based searching where the search engine returns a set of documents (or links to the documents). In the
A new semantic search scheme for XML data is proposed. The semantics of both XML documents and the query are enriched by domain ontology annotation. Also, the additional information provided by the structure of XML documents is considered by adding node path index, semantic keyword index and element tag index to
Nowadays, with the appearance of more and more web services, it has been one of the key points that how to find the target service quickly and precisely. Traditional methods of web service discovery are only based on the keyword matching, but it's very difficult to realize more detailed and intelligent services, and
Existing approaches to ontology retrieval solely base on keyword matching and return a lengthy list of relevant ontologies which may not satisfy user requirements. Users, therefore, are not equipped with expressive means to structurally and semantically describe their ontology needs. To tackle this problem, this paper
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...
they do well for keyword search strings such as "ocean'08 conference information", they are quite inadequate for searching against structured data such as "time- series ocean surface temperature or salinity levels in the Gulf of Mexico". Traditional search engines deploy various complex algorithms, take into account the
library of XML documents which need to be ranked so they satisfy both the keyword and the tree structure constraints. This is a position paper which proposes combining existing vector space models (for keyword match) with tree isomorphism codes (for structural match).
currently, the World Wide Web is a medium for storing and sharing data. Search based on keyword matching and content classified are two methods of the traditional search, however, their performance of processing exponential growth data is unsatisfactory. The concept of the Semantic Web, which was proposed to solve the
This paper discusses a approach of Chinese text classification on semantic Web. It is given one classified technology based on the semantic concept established on the "How-net" . It extracts keywords from text, analyses the full text using the keywords concept, and then the integrates to classify by categories of
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
Most of the search engines search for keywords to answer the queries from users. The search engines usually search web pages for the required information. However they filter the pages from searching unnecessary pages by using advanced algorithms. These search engines can answer topic wise queries efficiently and
prototype, it showed that this kind of search engine, based on apparel semantic tree, was more efficient apparently than full-text search engine when searching with multi-keywords.
Because of ignoring the semantic information inside the keywords, the traditional searching engine based on the key words has low recall and precision. Aiming at this, some semantic retrieval system design ideas and the retrieval process are proposed in this paper.The key technologies-related in semantic retrieval
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