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Tag Ranking Algorithms and Implementations
Author: ShangShuJie
Tutor: ChenChunï¼›WangCan
School: Zhejiang University
Course: Applied Computer Technology
Keywords: Tag Sequence Mutually reinforcing relationship model Random Jump Model Interested propagation model
CLC: TP393.092
Type: Master's thesis
Year: 2010
Downloads: 170
Quote: 2
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Abstract
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Tag (TAG) is a WEB 2.0 is an important component of many famous content sharing sites such as Flickr, Delicious etc allowing users to submit additional content , while some words (TAG) do supplement , these labels contain the user 's understanding of the content it is very important semantic material can be used for retrieving the content , content recommendation , tag recommendation, interest groups such as applied research findings . But many websites existing label sort are relatively simple , some are unordered, some just the frequency of use with simple labels , so people need a better sorting algorithm to sort the label . This paper analyzes the behavior of tags based on the combination of user tagging systems , labels, content three elements , utilization graph algorithms and data mining algorithms to score the tag . In this paper, the document class or category label document sharing sites were proposed three ways to sort the label . The first method is based on the interest method of propagation model , by constructing the \The second method is based on the user and the mutually reinforcing relationship between labels using the new EigenTag algorithm to score. The third method is based on a random jump model scoring method . We constructed a label and using random graph model to jump labels to sort . We label the artificial marker sequence as the standard sort , and use NDCG standard to measure the accuracy of the algorithm . Experiments show that , compared to the original site sorting , the proposed method on the label of each sorting accuracy is greatly improved.
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