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There are a lot benefits to enable intelligent agent understanding the information from semantic web. It enhances the efficiency of information usage and at the same time, suffices the need of users. Semantic documents contain adequate semantic information which helps understanding. However, discrepancy between ontology which is an interpreter of semantic(More)
Many people use the web as the main information source in their daily lives. However, most web pages contain non-information components, such as site bars, footers and ads, etc., which make it complicated to extract text from the original HTML documents. Because of the high human intervention and the low results extraction quality, although the web text(More)
To meet requirements of personal query, a personal query framework including personal ontology and role ontology is proposed based on preference ontology. The two-tier structure of the preference semantic formalization shows the differences and commonness of the background knowledge among different users. It is possible to generate personal ontology and(More)
Effect of three inorganic electrolytes (LiCl, NaCl, and MgCl2) and four organic electrolytes, viz. tetraalkylammonium bromides ((CH3)4NBr, (C2H5)4NBr, (C3H7)4NBr, and (C4H9)4NBr) on the aggregation behavior of the anionic halogen-free surface active ionic liquid, 1-butyl-3-methylimidazolium dodecylsulfate ([C4mim][C12SO4]), in aqueous solution was studied(More)
In view of inevitable redundancies in local data sources in heterogeneous information integration systems, a multi-copy join optimization method (MuCoJo for short) based on a genetic algorithm is proposed. MuCoJo can choose appropriate redundant copies of the tables to participate a joint query and optimizes the join order of it. By using the redundant(More)
Semantic similarity between concepts is a fundamental problem and plays an important role in many applications of artificial intelligence, knowledge sharing and Web mining. In this paper, a new measure based on semantic ontology database WordNet is proposed which combines information content-based measure and the edge-counting techniques to measure semantic(More)
Chinese text classification is always challenging, especially when data are high dimensional and sparse. In this paper, we are interested in the way of text representation and dimension reduction in Chinese text classification. First, we introduces a topic model - Latent Dirichlet Allocation(LDA), which is uses LDA model as a dimension reduction method.(More)
In the study of gestational hypertension, most of studies focused on whether a risk factor is associated with gestational hypertension. However, according to the clinical experience, it is important to know the effects of risk factors on women's blood pressure during pregnancy. Thus, we examined the effects of known risk factors (age, hematocrit, etc.) over(More)