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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...
How to find the teaching resources according to users' demand quickly and accurately on the Internet is urgent to be solved. This paper proposes a design of pretreatment for keyword-based search over network teaching resource database based on ontology. Firstly, the teaching ontology is created according to the
Search engines on the Web have popularized the keyword-based search paradigm, while searching in databases users need to know a database schema and a query language. Keyword search techniques on the Web cannot directly be applied to databases because the data on the Internet and database are in different forms
Search engines on the Web have popularized the keyword-based search paradigm, while searching in databases users need to know a database schema and a query language. Keyword search techniques on the Web cannot directly be applied to databases because the data on the Internet and database are in different forms. So
, and which require up-front data integration. At the other extreme, existing solutions employ keyword search queries over relational databases, as well as over semistructured data, which are too imprecise to specify exactly the user's intent. To address these limitations, we propose an alternative search paradigm in order
A previously proposed keyword search paradigm produces, as a query result, a ranked list of object summaries (OSs); each OS summarizes all data held in a relational database about a particular data subject (DS). This paper further investigates the ranking of OSs and their tuples as to facilitate (1) the top-k ranking
relational database of web pages. So there are many researches focusing on the search in these relational database with keywords, compared with these researches, our algorithms are mainly based on bags using the greedy algorithms and supporting the phrase recognition by utilizing multiple dictionaries. We make a comparison
The WWW is a very large repository composed of many documents that are stored by several data sources. Web search engines allow retrieval based on keywords. Nevertheless, published documents may be incomplete, obsolete or huge. Therefore, search also might include quality criteria such as completeness, recentness
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
generation approach, it can automatically integrate biological data from different sources that support the BioPAX exchange format (e.g. KEGG, Bio- Cyc). The systems Web interface allows both simple keyword and complex query-based searches in the database. The pathway visualization component provides fast and interactive data
time. Comparing the 'like' query in the standard SQL in relational databases, which can not decide the similarity according users' interests when keywords appear in several different fields, a novel similarity evaluation is given in algorithm of the personalized recommendation. Using the method, a personalized digital
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