SciRecSys: A Recommendation System for Scientific Publication by Discovering Keyword Relationships
Nguyen Tat Thanh University（阮爱国大学）；Yeungnam University（岭南大学）；Information Technology College（信息技术学院）；University of Information Technology（信息技术大学）；Chung-Ang University（中央大学）
英文摘要：
In this work, we propose a new approach for discovering various relationships among keywords over the scientific publications based on a Markov Chain model. It is an important problem since keywords are the basic elements for representing abstract objects such as documents, user profiles, topics and many things else. Our model is very effective since it combines four important factors in scientific publications: content, publicity, impact and randomness. Particularly, a recommendation system (called SciRecSys) has been presented to support users to efficiently find out relevant articles.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
