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Query-by-keywords is the most popular manner to search for data in this computing age. However, most work was proposed for searching centralized relational databases. This paper investigates how keyword search is to be deployed in relational database-enabled peer-to-peer systems. Unlike centralized system, the key
(P2P) computing model has fueled the autonomous data sharing over the Internet in a more flexible fashion. Needless to say, XML data retrieval in P2P systems has become attractive to professionals in both research and industrial communities. In this paper, we propose a Bloom-Filter based keyword search framework for XML
Recent research has shown that keyword search is a friendly and potentially effective way to retrieve information of interest over relational databases. Existing work has generally focused on implementing keyword search in centralized databases. This paper addresses keyword search over distributed databases. We adopts
In this paper, we propose an automatic clustering method to find synonymous terms including cross-language keywords from Chinese and English thesis documents. First, Chinese and English keyword pairs were collected from an existing database. Then, the system calculates the support and confidence values of the keyword
In this paper we focus on building keyword search service over unstructured Peer-to-Peer (P2P) networks. Current state-of-the-art keyword search approaches for unstructured P2P systems are either blind or informed. Blind search methods such as flooding in Gnutella generate a large of redundant cloned messages and
multilingual information where backend will be English database and front-end uses local languages like Hindi, Marathi or Gujrathi. Our system provides an interface to enter a keyword in local language, the keyword will be parsed, query will be formed and display the result in local language. We had developed an efficient
We present an index structure to support the approximate keyword search in text databases. In an approximate keyword search query, the user presents a query word Q and a tolerance value k (kges0), and wishes to find all documents in the database that contain the query word Q or any other word in the vocabulary that
Keyword-based web search engine uses text to reflect users' query intentions. However, it is hard to descript user's intention with simple text terms accurately, and besides of this, it is also hard to make the association between the text terms and images precisely. As a result, the keyword-based image search engine
content of a given XML document, making the best use of XML structure. Search metrics take account of the similarity in tag names, tag values, and the structure of tags. After a search, the system displays the ranked results in the order of aggregate similarity. Three methods of query are provided: keyword search which is
Nowadays, Internet users are familiar with the Web searching process; and searching is the most common task performed on the Web. However, the web search is especially difficult for beginners when they try to utilize a keyword query language. Subsequently, beginners usually try to find information with ambiguous
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