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The Study on Web Search Results’ Clustering

Author: LiuHuaBin
Tutor: BaiSiXue
School: Nanchang University
Course: Applied Computer Technology
Keywords: Clustering algorithm Web search engines Search Results Suffix array Latent Semantic Indexing
CLC: TP391.3
Type: Master's thesis
Year: 2008
Downloads: 182
Quote: 2
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Abstract


With the continuous development of computer technology and network technology, Internet has become the world's largest repository of information. The face of a broad array of information, the user attempts by browsing the Web has become increasingly difficult to find information, retrieve information. The search engine is the main tool for people to get information from the Web search engines such as Google, Baidu, Yahoo and other search results returned by the lack of a clear structure, often return a long, mixed search results for relevant information and irrelevant information list, the user had to list results one by one to verify in order to obtain the desired information, which users search for the information you really need manufacturing difficulties. Therefore, how to allow users to more accurately and quickly by the search engines to find the information they need to become a very important research topic. Data mining technologies, and provides a new way to solve this problem. Data mining aims to extract data implied, unknown, useful, general mode or knowledge. Clustering as one of the basic methods of data mining the data inherent characteristics and distribution of the similarities and differences of the comparative data can be found, to gain a deeper understanding and awareness of the data. Using clustering techniques to deal with the search results, a more reasonable way to return search results to the user, and allows the user to easily get the information they need. In this paper, on the basis of research on Web search engines and data mining technology for the needs presented a Chinese language environment, to cluster the search results of search result clustering model and its key module implementation. The main idea of ??this model is based on the search results returned by the Web search engine as input data, first find a good descriptive readability clustering label, and then assigned to each cluster label relevant search results, after after processing search results clustering categories returned to the user, so that users can more easily find the information. In the design of the model, we refer to the two classic search results clustering algorithm - the SHOC and LINGO based on full account of the characteristics of the Chinese language in the English language to be modified, the original algorithm for English and adjustment, so that our model can get better results in the Chinese language.

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