TY - GEN
T1 - Athena
T2 - 13th ACM International Conference on Web Search and Data Mining, WSDM 2020
AU - Liu, Junfeng
AU - Ma, Shuai
AU - Hu, Renjun
AU - Hu, Chunming
AU - Huai, Jinpeng
N1 - Publisher Copyright:
© 2020 Association for Computing Machinery.
PY - 2020/1/20
Y1 - 2020/1/20
N2 - Scholarly search systems greatly aid the deep understanding of scholarly data and facilitate the research activities of scholars for scientific studies. Though a number of such systems have been developed, most of them either support rankings of limited search of entities or provide only basic ranking metrics. These existing systems also mainly adopt RDBMSs as their storage such that the linked feature of scholarly data is not fully exploited. In this study, we design and develop a novel scholarly search system Athena. (1) It supports four types of scholarly entity searches: articles, authors, venues and affiliations, and is equipped with five ranking metrics, including three traditional metrics and two comprehensive importance ranking metrics. (2) It also provides profiling of scholarly entities. (3) It further utilizes a graph storage to directly leverage the linked feature for speeding up the processing of complex queries. We demonstrate the advantages of Athena at scholarly search, profiling, graph storage and ranking quality.
AB - Scholarly search systems greatly aid the deep understanding of scholarly data and facilitate the research activities of scholars for scientific studies. Though a number of such systems have been developed, most of them either support rankings of limited search of entities or provide only basic ranking metrics. These existing systems also mainly adopt RDBMSs as their storage such that the linked feature of scholarly data is not fully exploited. In this study, we design and develop a novel scholarly search system Athena. (1) It supports four types of scholarly entity searches: articles, authors, venues and affiliations, and is equipped with five ranking metrics, including three traditional metrics and two comprehensive importance ranking metrics. (2) It also provides profiling of scholarly entities. (3) It further utilizes a graph storage to directly leverage the linked feature for speeding up the processing of complex queries. We demonstrate the advantages of Athena at scholarly search, profiling, graph storage and ranking quality.
UR - https://www.scopus.com/pages/publications/85079558555
U2 - 10.1145/3336191.3371861
DO - 10.1145/3336191.3371861
M3 - 会议稿件
AN - SCOPUS:85079558555
T3 - WSDM 2020 - Proceedings of the 13th International Conference on Web Search and Data Mining
SP - 841
EP - 844
BT - WSDM 2020 - Proceedings of the 13th International Conference on Web Search and Data Mining
PB - Association for Computing Machinery, Inc
Y2 - 3 February 2020 through 7 February 2020
ER -