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Recommendation level scoring method for theme-based network user comments

A network user and recommendation technology, which is applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problem of not mining and utilizing the topic context and context, not being suitable for rapid update of network user comments, and unable to accurately judge the sentiment of comments Tendency and other issues, to achieve the effect of assisting product recommendation and information retrieval, high accuracy, and good scalability

Active Publication Date: 2015-02-04
NANJING UNIV
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AI Technical Summary

Problems solved by technology

Existing scoring methods only consider user comments themselves, do not mine and utilize the context and context of the topic, and cannot accurately judge the emotional tendency of comments; moreover, manual evaluation and marking are required, which is not suitable for the characteristics of rapid update of online user comments

Method used

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  • Recommendation level scoring method for theme-based network user comments
  • Recommendation level scoring method for theme-based network user comments
  • Recommendation level scoring method for theme-based network user comments

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Embodiment Construction

[0042] figure 1Shown is the technical framework of the topic-based recommendation scoring method for web user reviews. The input of the method is user reviews under the same topic; the output of the method is the recommendation score of the target user reviews. The method of the present invention requires an emotional thesaurus. At present, emotional thesaurus for different languages ​​have been developed and published at home and abroad (such as the HowNet thesaurus of CNKI and the Riloff thesaurus of English, etc.). The technical framework is divided into six steps: 1) Obtain user comments under the same topic in the network, and organize these comments in sentences; 2) Based on the emotional words in the sentence, complete the sentiment score for each sentence; 3) Sentence and corresponding As input, train Hidden Markov SVM model (Hmm-SVM) according to the user unit; 4) For the target comment to be rated, use the Hmm-SVM model to score each sentence in the comment; 5) For ...

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Abstract

The invention discloses a recommendation level scoring method for theme-based network user comments. The method comprises the following steps: (1) acquiring the user comments under the same theme in network and organizing the comments by taking sentences as units; (2) performing emotional scoring on the sentences based on emotional words in the sentences; (3) taking the sentences and the corresponding emotional scoring as inputs and training a hidden Markov SVM (Support Vector Machine) model according to user units; (4) scoring each sentence by using the model aiming at a target comment to be scored; (5) scoring each sentence by using the step (2) aiming at the target comment to be scored; (6) combining the scoring in the two aspects by using a weighted average method to acquire the recommendation level scoring of the target comment. According to the method, an unsupervised mode is adopted, artificial evaluation is not required by applying a public emotional word library, and the calculation cost is simple; the method is suitable for the situation of quick updating of the network comments; the theme characteristics can be mined, the emotional tendency of other user comments and the influence of the theme on the target user comment are fully considered, and the accuracy and the timeliness of scoring are improved.

Description

[0001] technical field [0002] The invention relates to a recommendation rating method for network user comments. Specifically, under a given topic, using technologies in the fields of data mining, machine learning, and natural language processing, based on a public emotional lexicon, automatically completes the evaluation in an unsupervised manner. The recommendation score of network user reviews does not require human participation. Background technique [0003] With the wide application and development of Web technology, the Internet has entered various fields of people's social life. Users carry out various activities and entertainment on the Internet, and post a large number of comments or messages through forums, blogs, Weibo, WeChat and other platforms. These comments can represent the views and opinions of network users. By analyzing the emotional tendency and recommendation degree of these network comments, it is helpful to understand information such as user atti...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F40/205G06F18/295
Inventor 许超蒋智威顾庆王晓亮陈道蓄
Owner NANJING UNIV
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