Earticle

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

키워드

저자

• Lizhou Zheng [ School of Computer Science and Technology University of Science and Technology of China, 230027, Hefei, China ]
• Kaifan Yang [ School of Computer Science and Technology University of Science and Technology of China, 230027, Hefei, China ]
• Yongbo Yu [ School of Computer Science and Technology University of Science and Technology of China, 230027, Hefei, China ]
• Peiquan Jin [ School of Computer Science and Technology University of Science and Technology of China, 230027, Hefei, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605