微博用戶個性化標簽提取技術研究
[Abstract]:Weibo user tags can reflect the characteristics of users, user preferences and other information, and user tags to the user advertising recommendation, user clustering, user search and so on have a certain potential value. In this paper, the personality of Weibo user personalized tag contains two meanings, one is that the tag can reflect the personalized characteristics of the user, the other is that the tag itself contains the corresponding personalized features. Tags reflect the degree of personalized features of the user this paper compares with the tags extracted by the user manually. The personalized features contained in the tags refer to the further classification of the tags. Make the user's tags with common attributes, to facilitate the user to find, clustering, and so on. In this paper, we find out that there are three basic types of tags in user self-removal tags, which are called basic label, classified label, concern label, and then the characteristics of each basic type tag are studied respectively. According to the characteristics of each basic type label, the corresponding extraction method is designed, and then according to the relationship between the three basic type tags, how to integrate the three labels together to get a better response to the personalized features of the user tags. Therefore, in this paper, there are seven kinds of tag extraction methods involved in the process of user personalized tag extraction, three of which are based on tags, the other four are mixed tags between these three basic types of tags. Except for the existing TextRank algorithm which is used to extract the basic label in the basic type tag, the other six label extraction methods are all proposed in this paper. Through the final verification experiment, it is found that the mixed tag extraction effect of the three basic types of tags is the best. Therefore, the user tag extraction method studied in this paper has improved the effect of user personalized tag extraction. In addition, after further classifying the extracted user personalized tags, this paper makes Weibo user tags with more common information, which also brings certain benefits to user clustering, user classification, user search, and so on. Make user label's application scope more extensive.
【學位授予單位】:哈爾濱工程大學
【學位級別】:碩士
【學位授予年份】:2016
【分類號】:TP393.092;TP311.13
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