Citation recommendation with a content-sensitive deepwalk based approach

Lantian Guo, Xiaoyan Cai, Haohua Qin, Yangming Guo, Fei Li, Gang Tian

科研成果: 书/报告/会议事项章节会议稿件同行评审

14 引用 (Scopus)

摘要

Systems for recommending scientific papers mainly help researchers to find a list of references that related to the researcher's interest effectively and automatically. Many state-of-the-art technique have been used for recommendation system, however, the traditional approaches has the issues of data scarcities and cold start, and existing recommended approaches with network representation only focus on one aspect of node information and cannot leverage content information. In this paper, we proposed a Citation Recommendation method with a Content-Aware bibliographic network representation, called CR-CA, whose recommended process contains two levels: (1) At the node content level, the proposed approach calculates similarities between the target and candidate papers, selecting an initial seed set of papers; (2) At the citation network structure level, this approach exploits citation relationship between papers to study latent representation of the scientific papers based on a deep natural language method-DeepWalk. The proposed approach was tested on the AAN dataset demonstrate that this approach outperforms baseline algorithms, in the true positive rate (Recall) and normalized discounted cumulative gain (NDCG).

源语言英语
主期刊名Proceedings - 19th IEEE International Conference on Data Mining Workshops, ICDMW 2019
编辑Panagiotis Papapetrou, Xueqi Cheng, Qing He
出版商IEEE Computer Society
538-543
页数6
ISBN(电子版)9781728146034
DOI
出版状态已出版 - 11月 2019
活动19th IEEE International Conference on Data Mining Workshops, ICDMW 2019 - Beijing, 中国
期限: 8 11月 201911 11月 2019

出版系列

姓名IEEE International Conference on Data Mining Workshops, ICDMW
2019-November
ISSN(印刷版)2375-9232
ISSN(电子版)2375-9259

会议

会议19th IEEE International Conference on Data Mining Workshops, ICDMW 2019
国家/地区中国
Beijing
时期8/11/1911/11/19

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