@inproceedings{5d0bac9a1efb47e0b1dbbbc3695c4df9,
title = "Based on citation diversity to explore influential papers for interdisciplinarity",
abstract = "Interdisciplinary scientific research (IDR) has been obtained more and more attention in recent years. This paper studies the problem of which papers are important for IDR. According to the citation relationships among papers, we focus on the influential papers where novel methods or idea are proposed and these new methods are used in different research areas. A two-stage approach is given to find influential papers for interdisciplinarity based on citation diversity. Firstly, the topic distribution of each paper is estimated by training Latent Dirichlet Allocation (LDA) topic model on the papers repository. Then the diversity of cited papers and citing papers are designed to measure the paper's influence. The effectiveness of the proposed approach is demonstrated through the extensive experiments on a real dataset and a synthetic dataset.",
keywords = "Diversity, Interdisciplinarity, Topic model",
author = "Keqiang Wang and Chaofeng Sha and Xiaoling Wang and Aoying Zhou",
year = "2014",
doi = "10.1007/978-3-319-11116-2\_30",
language = "英语",
isbn = "9783319111155",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "343--354",
booktitle = "Web Technologies and Applications - 16th Asia-Pacific Web Conference, APWeb 2014, Proceedings",
address = "德国",
note = "16th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2014 ; Conference date: 05-09-2014 Through 07-09-2014",
}