TY - GEN
T1 - Massive scientific paper mining
T2 - 12th China National Conference on Chinese Computational Linguistics, CCL 2013 and 1st International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2013
AU - Zhou, Yang
AU - Ji, Shufan
AU - Xu, Ke
PY - 2013
Y1 - 2013
N2 - With dramatic increasing of scientific research papers, scientific paper mining systems have become more popular for efficient paper retrieval and analysis. However, existing keyword based search engines, language or topic model based mining systems cannot provide customized queries according to various user requirements. Hence, in this paper, we are motivated to propose a novel TAIL (Time-Author-Institute-Literature) model to capture the relationships among literature, authors, institutes and time stamps. Based on the TAIL model, we implement the Massive Scientific Paper Mining (MSPM) system and set up a B/S (Browser/Server) structure for web services. The evaluation results on large real data show that our MSPM system could deliver desirable mining results, providing valuable data supports for scientific research cooperations.
AB - With dramatic increasing of scientific research papers, scientific paper mining systems have become more popular for efficient paper retrieval and analysis. However, existing keyword based search engines, language or topic model based mining systems cannot provide customized queries according to various user requirements. Hence, in this paper, we are motivated to propose a novel TAIL (Time-Author-Institute-Literature) model to capture the relationships among literature, authors, institutes and time stamps. Based on the TAIL model, we implement the Massive Scientific Paper Mining (MSPM) system and set up a B/S (Browser/Server) structure for web services. The evaluation results on large real data show that our MSPM system could deliver desirable mining results, providing valuable data supports for scientific research cooperations.
UR - https://www.scopus.com/pages/publications/84893117979
U2 - 10.1007/978-3-642-41491-6_32
DO - 10.1007/978-3-642-41491-6_32
M3 - 会议稿件
AN - SCOPUS:84893117979
SN - 9783642414909
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 343
EP - 352
BT - Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data - 12th China National Conference, CCL 2013 and First Int. Symposium, NLP-NABD 2013, Proc.
Y2 - 10 October 2013 through 12 October 2013
ER -