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Design and Implementation based on three-dimensional classification model semantic search

Author: GaoJieWang
Tutor: Zuo
School: University of Electronic Science and Technology
Course: Computer Software and Theory
Keywords: Semantic Search Naive Bayes Text Classification Three-dimensional classification
CLC: TP391.1
Type: Master's thesis
Year: 2011
Downloads: 29
Quote: 0
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Abstract


With the rapid development and popularization of the Internet, the information age into the open. The information era has brought great convenience to people's learning and work people exchange information and share the Internet will become a platform. However, the Internet's inherent dynamic, heterogeneous disorder makes it difficult to quickly and accurately find the information they want resources. Problem exists for the Internet, the founder of the Internet Tim Berners-lee in 1999 proposed the idea of ??the semantic web. Have a good definition of the semantic web resources, will enable people to better information exchange and collaboration. With the continuous advancement of the ideas of the Semantic Web, people have gradually realized the importance of Semantic Web-based information search, put forward a new information retrieval methods - semantic search. More traditional information retrieval-way navigation, semantic search, information retrieval, semantic level can improve information retrieval recall and precision, is to meet the demand of the people for the next generation of search technology. Scholars since the proposed semantic search has invested a lot of research, made a lot of achievements. However, because of the massive and widespread of network resources, access to information resources for semantic search efficiency was not satisfied. On this basis, the subject classification ideology introduced into the field of semantic search, design a semantic search model based on three-dimensional classification. By the sources of information, storage and sorting process in order to improve the semantic search recall and precision. The main subject of research content and advanced the following points: First, the topic Bayesian rough set combination, to achieve a text classification method based on weighted naive Bayes source of information classification process . Page text classification, and feature extraction, so that the feature library has category information. This topic using a bottom-up ontology concept selection method to determine the selection of ontology concept classification feature based repositories, according to the level of category weights, which reduces the difficulty of ontology concepts selected. This topic based on the above studies, design a three-dimensional classification model, the sources of information, storage and display of the classification process to improve information retrieval recall and precision rate. The topic of semantic search engines has conducted in-depth research, to design a three-dimensional classification model semantic search, and the model of the module design and implementation, combined with the experiment demonstrated the feasibility of the model.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Text Processing
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