Iman Kamehkhosh

575 citations
9 papers · 297 indexed · h-index 8
Topics
Recommender Systems and Techniques (7 papers)Music and Audio Processing (7 papers)Music Technology and Sound Studies (6 papers)
Journals
User Modeling and User-Adapted InteractionConference on Recommender Systems
Partner nations
GermanyAustriaFrance

In The Last Decade

Iman Kamehkhosh

9 papers receiving 286 citations

Peers

Iman Kamehkhosh
Comparison fields: 5 of 46
  • Information Systems 210
  • Signal Processing 97
  • Artificial Intelligence 95
  • Management Science and Operations Research 94
  • Computer Vision and Pattern Recognition 93
Replace Tamas Jambor with:
Tamas Jambor United Kingdom
Benedikt Loepp Germany
Erion Çano Italy
Diane Hu United States
Yoon Ho Cho South Korea
Marcelo Garcia Manzato Brazil
Rahul Pandey United States
Keping Yang China
Jinmook Kim United States
Cosimo Palmisano Italy
Iman Kamehkhosh relative to Tamas Jambor United Kingdom Tamas Jambor's profile →
Citations per field
00.5×3.6×
Tamas Jambor · 1×
Citations per year

Countries citing papers authored by Iman Kamehkhosh

Since Specialization
Citations

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

Fields of papers citing papers by Iman Kamehkhosh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Iman Kamehkhosh

This figure shows the co-authorship network connecting the top 25 collaborators of Iman Kamehkhosh. A scholar is included among the top collaborators of Iman Kamehkhosh 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 Iman Kamehkhosh. Iman Kamehkhosh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
#WorkIndexed citations
1 34
2 18
3
A Comparison of Frequent Pattern Techniques and a Deep Learning Method for Session-Based Recommendation.
13
4 20
5 23
6
Personalized Next-Track Music Recommendation with Multi-dimensional Long-Term Preference Signals.
5
7 34
8 139
9
Analyzing the Characteristics of Shared Playlists for Music Recommendation
11

About Iman Kamehkhosh

Iman Kamehkhosh is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Information Systems, having authored 9 papers that have together received 297 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (7 papers), Music and Audio Processing (7 papers) and Music Technology and Sound Studies (6 papers). The work is most often cited by research in Information Systems (210 citations), Signal Processing (97 citations) and Management Science and Operations Research (94 citations). Iman Kamehkhosh has collaborated with scholars based in Germany, Austria and France. Frequent co-authors include Dietmar Jannach, Lukas Lerche, Michael Jugovac, Geoffray Bonnin and Malte Ludewig. Their work appears in journals such as User Modeling and User-Adapted Interaction and Conference on Recommender Systems.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026