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Enriching the Representative of Document Using IRF

Author: ChengShaoMei
Tutor: ChenShengShuang
School: Wuhan University of Technology
Course: Applied Mathematics
Keywords: Data Mining Documents on behalf of Keyword Library Management Web2.0
CLC: TP391.1
Type: Master's thesis
Year: 2010
Downloads: 8
Quote: 0
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Abstract


Web text mining is to find the text contained in the content and meaning of the process, the explosive growth of Web information sources at the same time, e-book data in the database is also a fast rate has widened. E-book management, the main task is to make the user quickly and accurately have to find a satisfactory documentation. Although the information in each document in a different interpretation of the document weights theme, but the user must be the desired query words are most relevant documents, so without loss of documents based on the information on behalf of choosing the right words will undoubtedly enhance the document document retrieval and classification results. But previous methods optimize document represents the word appear in the article focused on optimizing translation, ignoring the correlation between documents. User input only exact match keywords, the search system will return documents containing the keywords. Keywords are relatively strong academic words and few in number, for a beginner, he is difficult to find the exact query words, it can not quickly find a satisfactory answer. In order to break this bottleneck, reducing the query doors Lam, this paper introduces IRF (Iterative Reinforce-ment Framework) model, but the model the experimental background is delicious website, which take advantage of the core concept of Web2.0, so log on to the site's user interest on their own website or article with the semantic enrichment of entry as the label. These labels are the same keywords as the document can be subject indexing of books, but the difference is that these labels by the freedom and equality of the participants work together to build websites, not just the author, these labels will undoubtedly enrich the semantic information of the document , and the label is a link related documents semantic bridge changed in the past between the independent status of the document. Firstly TRIDF IRF model algorithm to calculate the initial document on behalf of the word, and then iterate produce other documents related to the document in the relevant entries, so greatly enriched the document on behalf of words, increasing the document retrieval range. To get better results, this article will introduce the concept of Web2.0 technologies in library management and is based on the assumption that explain their point of view. Stage of the book recommended to the user retrieval system is only a few documents similar to the document, is a relatively static retrieval systems, the user and the user can not obtain a good interaction between. A user of the document reading experience that can not be effectively save more not share this caused great waste of resources. This article will introduce the concept of Web2.0 is the core library management, the establishment of an interactive platform between users, so that users can not only use the tagging content and sites of interest and can record their own reading experience, etc., so that other users can By reading the experiences of others to determine the effect of the article, effectively saving time.

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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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