Pengjie Ren

5.2k citations
98 papers · 2.7k indexed · 1 hit paper · h-index 25
Topics
Topic Modeling (56 papers)Natural Language Processing Techniques (33 papers)Recommender Systems and Techniques (30 papers)

In The Last Decade

Pengjie Ren

88 papers receiving 2.6k citations

Hit Papers

Neural Attentive Session-based Recommendation20172026202020232017250500750

Peers

Pengjie Ren
Comparison fields: 5 of 95
  • Artificial Intelligence 2.0k
  • Information Systems 1.8k
  • Computer Vision and Pattern Recognition 511
  • Management Science and Operations Research 464
  • Computer Networks and Communications 191
Replace Zhumin Chen with:
Zhumin Chen China
Zhaochun Ren China
Ruiming Tang China
Xiuqiang He China
Weizhi Ma China
Alex Beutel United States
Alejandro Bellogín Spain
Zeno Gantner Germany
Ruobing Xie China
Pengjie Ren relative to Zhumin Chen China Zhumin Chen's profile →
Citations per field
00.5×1.5×
Zhumin Chen · 1×
Citations per year

Countries citing papers authored by Pengjie Ren

Since Specialization
Citations

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

Fields of papers citing papers by Pengjie Ren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengjie Ren

This figure shows the co-authorship network connecting the top 25 collaborators of Pengjie Ren. A scholar is included among the top collaborators of Pengjie Ren 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 Pengjie Ren. Pengjie Ren 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
#WorkIndexed citations
1 0
2 0
3 0
4 2
5 0
6 12
7 0
8 2
9 4
10 2
11 8
12 1
13 2
14 1
15 32
16 15
17 11
18 2
19 89
20
A Redundancy-Aware Sentence Regression Framework for Extractive Summarization
31

About Pengjie Ren

Pengjie Ren is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research, having authored 98 papers that have together received 2.7k indexed citations. Recurring topics across this work include Topic Modeling (56 papers), Natural Language Processing Techniques (33 papers) and Recommender Systems and Techniques (30 papers). The work is most often cited by research in Information Systems (1.8k citations), Artificial Intelligence (2.0k citations) and Management Science and Operations Research (464 citations). Pengjie Ren has collaborated with scholars based in China, Netherlands and United States. Frequent co-authors include Zhumin Chen, Zhaochun Ren, Jun Ma, Maarten de Rijke, Tao Lian, Jing Li, Yujie Lin, Qintong Li, Jing Li and Furu Wei. Their work appears in journals such as Geophysical Research Letters, Science Advances and Artificial Intelligence.

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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