Long Xia

21 papers receiving 588 citations

Peers

Long Xia
Comparison fields: 5 of 73
  • Management Science and Operations Research 230
  • Information Systems 364
  • Health Informatics 20
  • Artificial Intelligence 309
  • Computer Science Applications 39
Replace Yingqiang Ge with:
Yingqiang Ge United States
Sahin Cem Geyik United States
Prashant Vats India
Yu Lei Hong Kong
Zuohui Fu United States
Aditya Kumar Gupta India
Alexandre Viejo Spain
Chaoyue Niu China
Sergio Mart́ınez Spain
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Citations per year

Countries citing papers authored by Long Xia

Since Specialization
Citations

This map shows the geographic impact of Long Xia's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Long Xia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Long Xia more than expected).

Fields of papers citing papers by Long Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Long Xia. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Long Xia. The network helps show where Long Xia may publish in the future.

Co-authors

The 25 scholars most cited alongside Long Xia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Long Xia Line = papers co-authored together Long Xia links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019159
2 202097
3 202087
4 202255
5 202032
6 201830
7 202127
8 202221
9 201918
10 202215
11 202114
12 202111
13 201710
14
Model-Based Reinforcement Learning for Whole-Chain Recommendations.
20198
15
VTIR at the NTCIR-12 2016 Lifelog Semantic Access Task.
20167
16 20246
17 20224
18 20194
19
Reinforcement Learning for Online Information Seeking
20182
20 20241

About Long Xia

Long Xia is a scholar working on Information Systems, Management Science and Operations Research, Artificial Intelligence, Computer Science Applications and Sociology and Political Science, having authored 22 papers that have together received 609 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (10 papers), Advanced Bandit Algorithms Research (9 papers), Advanced Graph Neural Networks (3 papers), Digital Marketing and Social Media (3 papers), Mobile Crowdsensing and Crowdsourcing (3 papers), Topic Modeling (2 papers), Biomedical Text Mining and Ontologies (2 papers) and Pharmacovigilance and Adverse Drug Reactions (2 papers). The work is most often cited by research in Management Science and Operations Research (230 citations), Information Systems (364 citations), Health Informatics (20 citations), Artificial Intelligence (309 citations) and Computer Science Applications (39 citations). Long Xia has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Lixin Zou, Dawei Yin, Weidong Liu, Zhuoye Ding, Jiaxing Song, Shaozhang Niu, Jimmy Xiangji Huang, Pengfei Wang, Wayne Xin Zhao and Dawei Yin. Their work appears in journals such as Decision Support Systems, Journal of Management Information Systems, Tourism Management, International Journal of Information Management and Journal of Craniofacial Surgery.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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