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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
Traditionally, full text retrieval over structure peer- to-peer network has been implemented by inverted index by keywords. However, search based on this index scheme only support literally word match, not taking into account the meaning of words. In this paper, we present a new index scheme, inverted index by
on WCN. The proposed method exploits the information provided by WCN in order to enhance relevant keyword extraction. In addition, querying the index for a given keyword has worst case complexity O(log n), as compared to usual keyword spotting algorithms which run in O(n). Experiments show promising results in keyword
Remote Electronic Document (CReED) provided an access control to all documents that will grant different privileges to each user of the system. It also utilized a keyword analyzer and result matcher that will make searching and retrieving of documents faster and easier. CReED used a scanner device and file importing tool to
In this paper, we propose a new framework to index versioned documents, and extend the keyword queries into the more general phrase queries. Our index answers a one-sided time-constrained phrase query for any phrase P in O((|P|+k)log n) time, where n is the dataset size and k is the output size. We discuss how to tune
documents based on keywords, users normally have a more abstract perception what information they require. Semantic gap, which is the disparity between user's request and query results, has been identified as a challenging issue. In this paper, we are interested in scientific document indexing for retrieval. Knowing the
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