TY - GEN
T1 - What Were People Searching For? A Query Log Analysis of An Academic Search Engine
AU - Rohatgi, Shaurya
AU - Giles, C. Lee
AU - Wu, Jian
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Academic search engines have served the research community for years, yet there is little work done on understanding the taxonomy of query semantics. In this work, we present our findings of analyzing the query log of an academic search engine in the past four years. We study the distribution of query intents to understand the information requested by users. We classify query strings by topics using shallow and latent features captured using a customized word embedding model. To this end, we create a dataset that has scientific keywords and titles labeled with fields of study. This dataset is later used to train a classifier that discriminates query logs by topics. Our work will help to train better learning-based ranking functions that improve user experiences for an academic search engine. In addition, we anonymize our 14, 759, 852 query logs and make them available to the research community for further exploration.
AB - Academic search engines have served the research community for years, yet there is little work done on understanding the taxonomy of query semantics. In this work, we present our findings of analyzing the query log of an academic search engine in the past four years. We study the distribution of query intents to understand the information requested by users. We classify query strings by topics using shallow and latent features captured using a customized word embedding model. To this end, we create a dataset that has scientific keywords and titles labeled with fields of study. This dataset is later used to train a classifier that discriminates query logs by topics. Our work will help to train better learning-based ranking functions that improve user experiences for an academic search engine. In addition, we anonymize our 14, 759, 852 query logs and make them available to the research community for further exploration.
UR - http://www.scopus.com/inward/record.url?scp=85124179555&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85124179555&partnerID=8YFLogxK
U2 - 10.1109/JCDL52503.2021.00062
DO - 10.1109/JCDL52503.2021.00062
M3 - Conference contribution
AN - SCOPUS:85124179555
T3 - Proceedings of the ACM/IEEE Joint Conference on Digital Libraries
SP - 342
EP - 343
BT - Proceedings - 2021 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2021
A2 - Downie, J. Stephen
A2 - McKay, Dana
A2 - Suleman, Hussein
A2 - Nichols, David M.
A2 - Poursardar, Faryaneh
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st ACM/IEEE Joint Conference on Digital Libraries, JCDL 2021
Y2 - 27 September 2021 through 30 September 2021
ER -