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Gender -based classification of text mining

Author: BaiLiJuan
Tutor: ZuoXiangBin
School: Harbin Institute of Technology
Course: Management Science and Engineering
Keywords: Text Classification Gender differences Behavior Analysis Attribute word extraction Sex Dictionary
CLC: TP391.1
Type: Master's thesis
Year: 2011
Downloads: 57
Quote: 0
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Abstract


The emergence and development of network technology to people 's lives has undergone enormous changes , but also to the original mode of life , business models and modes of communication have brought more change patterns , people can through various forms of communication tools to achieve real-time communication . Then this non-verbal mode of communication with the existence of the same language environment gender differences , whether through communication content sex and then summed up the network environment or context of this non-verbal male and female -specific vocabulary . Users of different gender differences in the network environment includes not only the attitude of the computer users as well as the intended use also includes various other online shopping brings differences include risk awareness , service, quality assessment , recommendation mechanism. More importantly, this non -face to face communication mode of communication can be hidden in a more significant difference in the performance , including the use of words , tone expression and emotion expression , etc. In order to verify the network communication mode, the gender differences in language use in the study of selected articles and stock car forum Tianya Content as research data to hypothesis testing approach to validate the user posting behavior , found that users of different gender behavioral differences exist . Using several text classification algorithm for review content classification results prove the contents can be reviewed to identify gender classification classification classification algorithm better efficiency , and through association rule mining algorithm found that different users of the product attributes gender concerns are different, as related to the formulation of marketing strategies of manufacturers to provide a reference , the last word similarity is calculated using the combination of feature extraction methods such as mutual information and build men and women dictionary.

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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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