Xin Xin

2.0k total citations
82 papers, 1.0k citations indexed

About

Xin Xin is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research. According to data from OpenAlex, Xin Xin has authored 82 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Artificial Intelligence, 44 papers in Information Systems and 18 papers in Management Science and Operations Research. Recurrent topics in Xin Xin's work include Recommender Systems and Techniques (38 papers), Topic Modeling (21 papers) and Advanced Bandit Algorithms Research (17 papers). Xin Xin is often cited by papers focused on Recommender Systems and Techniques (38 papers), Topic Modeling (21 papers) and Advanced Bandit Algorithms Research (17 papers). Xin Xin collaborates with scholars based in China, United Kingdom and United States. Xin Xin's co-authors include Joemon M. Jose, Xiangnan He, Alexandros Karatzoglou, Ioannis Arapakis, Youtao Zhang, Ping Guo, Jun Yang, Yongfeng Zhang, Yongdong Zhang and Masahiro Kaneda and has published in prestigious journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Knowledge and Data Engineering and Applied Soft Computing.

In The Last Decade

Xin Xin

76 papers receiving 986 citations

Peers

Xin Xin
Comparison fields: 5 of 81
  • Information Systems 625
  • Artificial Intelligence 593
  • Management Science and Operations Research 178
  • Computer Vision and Pattern Recognition 169
  • Computer Networks and Communications 135
Replace Zhonghai Wu with:
Zhonghai Wu China
Jianlong Tan China
Vladimir Vlassov Sweden
Rana Forsati Iran
Jiawei Zhang China
Xin Dong United States
Xun Zheng China
Shiwen Wu China
Lidan Shou China
Zhonghai Wu China View profile →
Citations per field, relative to Xin Xin
Xin Xin · 1×
Citations per year, relative to Xin Xin
Xin Xin · 1×

Countries citing papers authored by Xin Xin

Since Specialization
Citations

This map shows the geographic impact of Xin Xin'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 Xin Xin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xin Xin more than expected).

Fields of papers citing papers by Xin Xin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xin Xin. 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 Xin Xin. The network helps show where Xin Xin may publish in the future.

Co-authorship network of co-authors of Xin Xin

This figure shows the co-authorship network connecting the top 25 collaborators of Xin Xin. A scholar is included among the top collaborators of Xin Xin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xin Xin. Xin Xin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 0
3 1
4 0
5 0
6 1
7 2
8 3
9 7
10 25
11 8
12 14
13 50
14 11
15
f BGD : Learning Embeddings From Positive Unlabeled Data with BGD.
14
16 1
17
Cross-domain collaborative filtering with review text
22
18
Re-ranking voting-based answers by discarding user behavior biases
8
19 3
20 1

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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