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In a real world, it is often in a group setting that sensitive information has to be stored in databases of a server. Although personal information does not need to be stored in a server, the secret information shared by group members is likely to be stored there. The shared sensitive information requires more security and privacy protection. To our best knowledge, there is no paper which deals with...
investigation about the improvements in the accuracy of a search system provided by network analysis techniques supporting the discovery of relations among the items stored in the repository. For this reason, we have developed the SEEN prototype, a keyword search tool exploiting network analysis. SEEN has been evaluated against a
The feature extraction is the most key technology of text categorization. The word is used as the feature in the traditional text classification, and its effect for the text classification is evidence. The feature extraction method using base phrase and keyword changes the feature extraction of Chinese text from
propose a novel algorithm for keyword search in XML documents based on maximum repetitive unit. The basic idea of the algorithm is as follows. Firstly, extract the duplicate structures of XML documents as repetitive units. Then find out which units contain all the query keywords. The results returned are a number of
In this paper, we address the issue of how to overview the knowledge of a given query keyword. We especially focus on concerns of those who search for Web pages with a given query keyword, and study how to efficiently overview the whole list of Web search information needs of a given query keyword. First, we collect
Based on the analysis of the insufficiencies of the present Chinese matching algorithms, by examining the characteristics of approximately duplicate records, this paper proposes a method of duplicate record cleaning based on a reformative keywords matching algorithm. Experiments show that this method improves Recall
Evaluation of the Deep Web data sources must be based on the data in the Web databases, then how to select the most representative keywords as a query word to obtain a large number of uniformly distributed data is a major difficulty, this paper proposed a Deep Web database sampling method based on high correlation
In order to improve searching results of Web pages and enhancing Web crawling operation, the Web page clustering based on searching keywords is proposed in this paper, which firstly employed matching degree between Web pages and searching keywords to decide the sequence of showing pages of searching results. Then
Text keywords at different semantic levels have different semantic representation abilities. Although words have been organized by semantic dictionaries (e.g. WordNet) with exact semantics, the dictionaries can not be constructed automatically by machine and there are still many words which are not included in the
keywords. In GrC, let us call it granular representation, we include the knowledge. More precisely, a document is not only represented by its keywords, but also by its granules. Here by a granule we mean a keyword association, which is a set of frequent co-occurring near by keywords. For a trivial example, the association
In this paper, we address the issue of how to overview the knowledge ofa given query keyword. We especially focus on concerns of those whosearch for Web pages with a given query keyword, and study how toefficiently overview the whole list of Web search information needs of agiven query keyword. First, we collect Web
Keyword-based search exploits the exact match between the index terms of a query and documents. Thus, some documents, although they are relevant to the given query, may not be returned to users unless the documents include the index terms of the query. Some search engines use the authority of documents, which is
An automatic document classifier system based on ontology and the naive Bayes classifier is proposed in this paper. The main concept is to first establish a keyword synonymous table by experts for narrowing down the range and getting the consistency of keywords. The formal concept analysis is then used for
Web service discovery is a mechanism which facilitates an access to the Web service descriptions. UDDI facilitates the discovery based on the service functionality through keyword and category matching. Such discovery techniques do not consider the semantics and user context as they are too syntactic in nature. In
number of users with diverse characteristics and needs. Currently, many research projects or practical applications have emerged which only support single keyword search, and few of them support semantic retrieval. In this paper, we propose a model of ontology-based semantic information retrieval systems according to hybrid
The motivation behind sub-topic or topic specific keyword discovery through Web pages is helping a user, who is insufficient in knowledge and experience about a topic, to find important concepts without much effort. Intuitively, a Web user would start searching the Web via querying search engines, visiting some pages
being unlike the keyword-based system that ignores the semantic relationships between words. Applying the proposed IR system to the given domain can make the managers of mobile communication companies retrieve the customers' complaints information more precisely and hence make decisions more reasonably
This paper identifies and defines the knowledge library application (KLA) class. KLAs are an important class of information resource/knowledge management applications. It will be clear from the definition that KLAs are highly relevant to both the commercial and academic worlds and existing techniques such as keyword
To support understanding of news, we propose a novel TEC model (Topic-Event Causal relation model) and describe the method to construct a Causal Network in the TEC model. The model includes two types of keywords to represent casual relations: topic keywords, which describe topics, and event keywords, which describe
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