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Information retrieval: a view from the Chinese IR community |
Zhumin CHEN1, Xueqi CHENG2, Shoubin DONG3, Zhicheng DOU4, Jiafeng GUO2( ), Xuanjing HUANG5, Yanyan LAN2( ), Chenliang LI6, Ru LI7, Tie-Yan LIU8, Yiqun LIU9( ), Jun MA1, Bing QIN10, Mingwen WANG11, Jirong WEN4, Jun XU4, Min ZHANG9, Peng ZHANG12, Qi ZHANG5 |
1. School of Computer Science and Technology, Shandong University, Jinan 250100, China 2. Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China 3. School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, China 4. School of Information, Renmin University of China, Beijing 100872, China 5. School of Computer Science, Fudan University, Shanghai 200433, China 6. School of Cyber Science and Engineering,Wuhan University,Wuhan 430072, China 7. School of Big Data, Shanxi University, Taiyuan 200433, China 8. Microsoft Research Asia, Beijing 100080, China 9. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China 10. School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China 11. School of Computer Information and Engineering, Jiangxi Normal University, Nanchang 330022, China 12. School of Computer Science and Technology, Tianjin University, Tianjin 300072, China |
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Abstract During a two-day strategic workshop in February 2018, 22 information retrieval researchers met to discuss the future challenges and opportunities within the field. The outcome is a list of potential research directions, project ideas, and challenges. This report describes themajor conclusionswe have obtained during the workshop. A key result is that we need to open our mind to embrace a broader IR field by rethink the definition of information, retrieval, user, system, and evaluation of IR. By providing detailed discussions on these topics, this report is expected to inspire our IR researchers in both academia and industry, and help the future growth of the IR research community.
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Keywords
information retrieval
redefinition
information
scope of retrieval
retrieval models
users
system architecture
evaluation
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Corresponding Author(s):
Jiafeng GUO,Yanyan LAN,Yiqun LIU
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Just Accepted Date: 27 December 2019
Issue Date: 24 September 2020
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