Julian McAuley

25.1k citations
203 papers · 11.5k indexed · 12 hit papers · h-index 38
Topics
Topic Modeling (70 papers)Recommender Systems and Techniques (62 papers)Advanced Graph Neural Networks (27 papers)
Journals
SHILAP Revista de lepidopterologíaApplied Physics LettersPLoS ONE

In The Last Decade

Julian McAuley

185 papers receiving 11.1k citations

Hit Papers

Self-Attentive Sequential Recommendation2012202620162021201820152012201320194008001.2k

Peers

Julian McAuley
Comparison fields: 5 of 162
  • Artificial Intelligence 7.2k
  • Information Systems 6.3k
  • Computer Vision and Pattern Recognition 3.0k
  • Management Science and Operations Research 1.4k
  • Statistical and Nonlinear Physics 1.4k
Replace Xiangnan He with:
Xiangnan He China
Ji-Rong Wen China
Irwin King Hong Kong
Jonathan L. Herlocker United States
Hanghang Tong United States
Aixin Sun Singapore
Xueqi Cheng China
ChengXiang Zhai United States
Francesco Ricci⋆ Italy
Peng Cui China
Julian McAuley relative to Xiangnan He China Xiangnan He's profile →
Citations per field
00.5×6.6×
Xiangnan He · 1×
Citations per year

Countries citing papers authored by Julian McAuley

Since Specialization
Citations

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

Fields of papers citing papers by Julian McAuley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Julian McAuley

This figure shows the co-authorship network connecting the top 25 collaborators of Julian McAuley. A scholar is included among the top collaborators of Julian McAuley 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 Julian McAuley. Julian McAuley 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 1
3 0
4 20
5 1
6 0
7 7
8 23
9 0
10 59
11 25
12 3
13 9
14 2
15 24
16 5
17 7
18
Justifying Recommendations using Distantly-Labeled Reviews and Fine-Grained Aspectsbreakdown →
626
19 145
20
Fusing Similarity Models with Markov Chains for Sparse Sequential Recommendationbreakdown →
401

About Julian McAuley

Julian McAuley is a scholar working on Artificial Intelligence, Health Informatics and Information Systems, having authored 203 papers that have together received 11.5k indexed citations. Recurring topics across this work include Topic Modeling (70 papers), Recommender Systems and Techniques (62 papers) and Advanced Graph Neural Networks (27 papers). The work is most often cited by research in Information Systems (6.3k citations), Artificial Intelligence (7.2k citations) and Computer Vision and Pattern Recognition (3.0k citations). Julian McAuley has collaborated with scholars based in United States, Australia and China. Frequent co-authors include Jure Leskovec, Wang-Cheng Kang, Ruining He, Anton van den Hengel, Qinfeng Shi, Jianmo Ni, Jiacheng Li, Rahul Pandey, Mengting Wan and Tibério S. Caetano. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Physics Letters and PLoS ONE.

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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