Paper Info
Title
Towards Better Understanding of Academic Search.
Abstract
Academics have relied heavily on search engines to identify and locate research manuscripts that are related to their research areas. Many of the early information retrieval sys- tems and technologies were developed while catering for li- brarians to help them sift through books and proceedings, followed by recent online academic search engines such as Google Scholar and Microsoft Academic Search. In spite of their popularity among academics and importance to academia, the usage, query behaviors, and retrieval models for aca- demic search engines have not been well studied. To this end, we study the distribution of queries that are received by an academic search engine. Furthermore, we delve deeper into academic search queries and classify them into navigational and informational queries. This work in- troduces a definition for navigational queries in academic search engines under which a query is considered naviga- tional if the user is searching for a specific paper or docu- ment. We describe multiple facets of navigational academic queries, and introduce a machine learning approach with a set of features to identify such queries.
Year
DOI
Venue
2016
10.1145/2910896.2910922
JCDL
Keywords
Field
DocType
information retrieval systems,online academic search engines,informational queries,navigational queries,machine learning approach
Web search query,Metasearch engine,World Wide Web,Search engine,Information retrieval,Query expansion,Semantic search,Computer science,Search engine optimization,Search engine indexing,Search analytics
Conference
ISSN
ISBN
Citations 
2575-7865
978-1-5090-5254-7
4
PageRank 
References 
Authors
0.38
12
3
Name
Order
Citations
PageRank
Madian Khabsa123718.81
Zhaohui Wu23121246.32
C. Lee Giles3111541549.48