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In this demo paper, we present a new data service composition sequence generation approach to solve the ad-hoc data query problem in EDMIS. Our approach allows end users to input some keywords, and then the data services related are found and the Top-K data services composition sequences are generated as output.
There exit model errors in the constructed Horizontally reversible plough (HRP) structure through Interference check technique (ICT). This is basically due to missing parts and geometric interference and, hence, has significantly adverse effects in improving HRP. In this paper an improved design to refine the three dimensional (3D) model of HRP is implemented by using Virtual assembly technology (VAT)...
Data services have almost become a standard way for data publishing and sharing on the web. Lack of well-defined machine readable model hinders its spreading. In this paper, we devote ourselves to modeling and discovery of data services. We use RDF model to describe the data scheme and semantics of the data services. Then we define a simplified SPARQL query to retrieve the satisfactory data services...
Service-oriented situational data integration provides end-users an opportunity to integrate Internet-based data sources by composing data services, thereby satisfying users' immediate and personalized demands. Correlated query of multiple sources is a common way of data integration. Because it is difficult for users to select and compose services manually, an approach is proposed in this paper to...
As a free online encyclopedia with a large-scale of knowledge coverage, rich semantic information and quick update speed, Wikipedia brings new ideas to measure semantic correlation. In this paper, we present a new method for measuring the semantic correlation between words by mining rich semantic information that exists in Wikipedia. Unlike the previous methods that calculate semantic relatedness...
This paper proposes a grammar-based unsupervised method to automatically mine the Chinese volitive words, which are the important clues of intention and desiration in literal content, such as “can”, “must”, “rather than”, etc. Besides, the paper introduces a scheme of manually tagging volitive words from large-scale Chinese blogs. And the tagged blogs are adopted as corpus to evaluate our unsupervised...
This paper proposes a knowledge retrieval model combining knowledge search with data mining technologies. In this model, data mining is integrated into the whole retrieval procedure of query optimizing, searching, results analyzing, and resources constructing. It realizes knowledge retrieval by various approaches, different levels, and multi-modes, and significantly improves knowledge retrieval level...
Most of text association pattern mining techniques transform texts into flat bags of words representation, which does not preserve sufficient semantics for the purpose of knowledge discovery. So the depth and accuracy of mining are not satisfying. In order to solve this problem, a novel ontology-based semantic association pattern mining model is proposed. The suggested model applies semantic role...
Text mining is an effective means of acquiring potentially useful knowledge from text document. However, traditional text mining cannot achieve high accuracy, because it cannot effectively make use of the semantic information of the text. Ontology provides theoretical basis and technical support for semantic information representation and organization. This paper introduces and analyzes text mining...
A text classification model based on Latent Semantic Analysis and Improved Hyper-sphere Support Vector Machine, is proposed in order to improve the accuracy and efficiency of text classification. Latent Semantic Analysis is used in this model for feature extraction, eliminating the text representation errors caused by synonyms and polysemes, and reducing the dimension of text vector. At the same time,...
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