원문정보
초록
영어
It is necessary to have blogging technology which automatically figures out context information from the user in order to provide efficient micro blogging service for users in the social network service (SNS) environment. This paper proposes a context-based micro blogging service which considers the situations and emotions of users. To achieve this, a preprocessing method has been modeled based on users’ location and time context by using a granular tree, and Naive Bayes Classification has been adopted to assess a user’s behavior on the basis of a modeling context. In addition, a questionnaire has been administered to gain information about a user’s emotion in different situations and which considers location by using the Analytic Hierarchy Process (AHP). Based on this, a blog-able single sentence generation and auto blogging have been performed. The evaluation result of blogging a sentence and user’s emotional information shows 85.4% and 82.6% of accuracy, respectively; therefore, the proposed context modeling method for auto blogging is both efficient and effective.
목차
1. Introduction
2. Related Researches
2.1. Granular Computing
2.2. Naïve Bayes Classification
2.3. AHP
3. Micro Auto Blogging System
3.1. Context Collecting
3.2. Preprocessing and Combining of Contexts
4. User Schedule and Behavioral Reasoning
4.1. Schedule Reasoning
4.2. User Behavior Reasoning
5. Emotional Reasoning
5.1. Emotional Expression Language and Context Information
5.2. Emotionally Expressive Languages and Context Matching
5.3. Analysis on the Relative Importance of Various Contexts Affecting Changes OfEmotion
6. Sentence Generation
7. Experiments and Evaluation
8. Conclusion
Acknowledgements
References