Konstantin Bauman

466 total citations
18 papers, 229 citations indexed

About

Konstantin Bauman is a scholar working on Information Systems, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Konstantin Bauman has authored 18 papers receiving a total of 229 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Information Systems, 11 papers in Artificial Intelligence and 5 papers in Signal Processing. Recurrent topics in Konstantin Bauman's work include Recommender Systems and Techniques (14 papers), Advanced Graph Neural Networks (5 papers) and Data Management and Algorithms (5 papers). Konstantin Bauman is often cited by papers focused on Recommender Systems and Techniques (14 papers), Advanced Graph Neural Networks (5 papers) and Data Management and Algorithms (5 papers). Konstantin Bauman collaborates with scholars based in United States, Israel and Italy. Konstantin Bauman's co-authors include Alexander Tuzhilin, Bing Liu, Moshe Unger, Gediminas Adomavičius, Bamshad Mobasher, Bing Liu and Francesco Ricci⋆ and has published in prestigious journals such as MIS Quarterly, Information Systems Research and ACM Transactions on Management Information Systems.

In The Last Decade

Konstantin Bauman

17 papers receiving 227 citations

Peers

Konstantin Bauman

SPS

CVPR

MSOR

Amra Delić Bosnia and Herzegovina

Fattane Zarrinkalam Canada

Raquel Martínez Spain

Leo Iaquinta Italy

Martin Saveski United States

Rim Faïz Tunisia

Marcel Genzmehr Germany

Shahpar Yakhchi Australia

Dimitrios Pierrakos Greece

Corinne Amel Zayani Tunisia

Amra Delić Bosnia and Herzegovina

Konstantin Bauman

128 ×0.8

62 ×0.4

62 ×1.6

SPS

18 ×0.9

CVPR

18 ×0.9

MSOR

Citations per year, relative to Konstantin Bauman Konstantin Bauman (= 1×) peers Amra Delić

Countries citing papers authored by Konstantin Bauman

Since Specialization

Citations

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

Fields of papers citing papers by Konstantin Bauman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Konstantin Bauman

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

All Works

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18 of 18 papers shown

Bauman, Konstantin, et al.. (2024). Does the Long Tail of Context Exist and Matter? The Case of Dialogue-based Recommender Systems. 273–278.

Adomavičius, Gediminas, Konstantin Bauman, Bamshad Mobasher, Alexander Tuzhilin, & Moshe Unger. (2024). Workshop on Context-Aware Recommender Systems (CARS) 2024. 1219–1221. 1 indexed citations

Bauman, Konstantin, Alexander Tuzhilin, & Moshe Unger. (2024). HyperCARS: Using Hyperbolic Embeddings for Generating Hierarchical Contextual Situations in Context-Aware Recommender Systems. Information Systems Research. 36(2). 871–895. 2 indexed citations

Adomavičius, Gediminas, Konstantin Bauman, Bamshad Mobasher, Alexander Tuzhilin, & Moshe Unger. (2023). Workshop on Context-Aware Recommender Systems 2023. 1234–1236. 2 indexed citations

Adomavičius, Gediminas, Konstantin Bauman, Bamshad Mobasher, et al.. (2022). CARS: Workshop on Context-Aware Recommender Systems 2022. View. 691–693. 2 indexed citations

Bauman, Konstantin & Alexander Tuzhilin. (2021). Know Thy Context: Parsing Contextual Information from User Reviews for Recommendation Purposes. Information Systems Research. 33(1). 179–202. 16 indexed citations

Bauman, Konstantin & Alexander Tuzhilin. (2021). Know thy Context: Parsing Contextual Information from User Reviews for Recommendation Purposes. SSRN Electronic Journal. 3 indexed citations

Adomavičius, Gediminas, Konstantin Bauman, Bamshad Mobasher, et al.. (2021). Workshop on Context-Aware Recommender Systems (CARS) 2021. View. 813–814. 1 indexed citations

Adomavičius, Gediminas, Konstantin Bauman, Bamshad Mobasher, et al.. (2020). Workshop on Context-Aware Recommender Systems. View. 635–637. 1 indexed citations

10.

Adomavičius, Gediminas, Konstantin Bauman, Bamshad Mobasher, et al.. (2019). Workshop on context-aware recommender systems. View. 548–549. 2 indexed citations

11.

Bauman, Konstantin & Alexander Tuzhilin. (2018). Recommending Remedial Learning Materials to Students by Filling Their Knowledge GAPS1. MIS Quarterly. 42(1). 313–332. 24 indexed citations

12.

Bauman, Konstantin, et al.. (2017). Using Social Sensors for Detecting Emergency Events. ACM Transactions on Management Information Systems. 8(2-3). 1–20. 19 indexed citations

13.

Bauman, Konstantin, Bing Liu, & Alexander Tuzhilin. (2017). Aspect Based Recommendations. 717–725. 121 indexed citations

14.

Bauman, Konstantin, Bing Liu, & Alexander Tuzhilin. (2016). Recommending items with conditions enhancing user experiences based on sentiment analysis of reviews. Conference on Recommender Systems. 1673. 19–22. 6 indexed citations

15.

Bauman, Konstantin, et al.. (2015). Virtual Power Outage Detection Using Social Sensors. The Faculty Digital Archive (New York University). 3 indexed citations

16.

Bauman, Konstantin & Alexander Tuzhilin. (2014). Discovering Contextual Information from User Reviews for Recommendation Purposes.. Conference on Recommender Systems. 2–9. 22 indexed citations

17.

Bauman, Konstantin & Alexander Tuzhilin. (2014). Recommending Learning Materials to Students by Identifying their Knowledge Gaps.. Conference on Recommender Systems. 2 indexed citations

18.

Bauman, Konstantin, et al.. (2013). Optimization of click-through rate prediction in the Yandex search engine. Automatic Documentation and Mathematical Linguistics. 47(2). 52–58. 2 indexed citations

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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