원문정보
초록
영어
In this paper, we present the idea and methodologies on predicting the age span of users over microblog dataset. Given a user’s personal information such as user tags, job, education, self-description, and gender, as well as the content of his/her microblogs, we automatically classify the user’s age into one of four predefined ranges. Particularly, we extract a set of features from the given information about the user, and employ a statistic-based framework to solve this problem. The measurement shows that our proposed method incorporating selected features has an accuracy of around 71% on average over the training dataset.
목차
Abstract
1. Introduction
2. Related Work
3. The General Framework for User Age Prediction
3.1. Preprocessing
3.2. Feature Selection
3.3 Classification
4. Performance Evaluation
4.1. Dataset
4.2. Results
5. Conclusions
Acknowledgements
References
1. Introduction
2. Related Work
3. The General Framework for User Age Prediction
3.1. Preprocessing
3.2. Feature Selection
3.3 Classification
4. Performance Evaluation
4.1. Dataset
4.2. Results
5. Conclusions
Acknowledgements
References
저자정보
참고문헌
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