Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions
20056.5k citationsGediminas Adomavičius, Alexander TuzhilinIEEE Transactions on Knowledge and Data Engineeringprofile →
Context‐Aware Recommender Systems
2011850 citationsGediminas Adomavičius, Francesco Ricci⋆ et al.profile →
Incorporating contextual information in recommender systems using a multidimensional approach
2005763 citationsGediminas Adomavičius, Alexander Tuzhilin et al.profile →
Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques
2011460 citationsGediminas Adomavičius et al.IEEE Transactions on Knowledge and Data Engineeringprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Gediminas Adomavičius
Since
Specialization
Citations
This map shows the geographic impact of Gediminas Adomavičius'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 Gediminas Adomavičius with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gediminas Adomavičius more than expected).
Fields of papers citing papers by Gediminas Adomavičius
This network shows the impact of papers produced by Gediminas Adomavičius. 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 Gediminas Adomavičius. The network helps show where Gediminas Adomavičius may publish in the future.
Co-authorship network of co-authors of Gediminas Adomavičius
This figure shows the co-authorship network connecting the top 25 collaborators of Gediminas Adomavičius.
A scholar is included among the top collaborators of Gediminas Adomavičius 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 Gediminas Adomavičius. Gediminas Adomavičius is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Adomavičius, Gediminas, et al.. (2019). The hidden side effects of recommendation systems. MIT Sloan management review. 60(2). 13–15.11 indexed citations
7.
Yang, Mochen, Yuqing Ren, & Gediminas Adomavičius. (2018). Understanding User-Generated Content and Customer Engagement on Facebook Business Pages. SSRN Electronic Journal.1 indexed citations
8.
Yang, Mochen, Gediminas Adomavičius, Gordon Burtch, & Yuqing Ren. (2017). Mind the Gap: Accounting for Measurement Error and Misclassification in Variables Generated via Data Mining. SSRN Electronic Journal.1 indexed citations
9.
Fan, Yingling, et al.. (2016). Battery-Efficient Location Change Detection for Smartphone-Based Travel Data Collection: A Wi-Fi Fingerprint Approach. Transportation Research Board 95th Annual MeetingTransportation Research Board.1 indexed citations
10.
Adomavičius, Gediminas, Jesse Bockstedt, Shawn P. Curley, & Jingjing Zhang. (2014). De-biasing user preference ratings in recommender systems completed research paper.2 indexed citations
11.
Adomavičius, Gediminas, et al.. (2014). De-biasing user preference ratings in recommender systems. Conference on Recommender Systems. 1253. 2–9.21 indexed citations
12.
Adomavičius, Gediminas, Alexander Tuzhilin, & Rong Zheng. (2011). REQUEST: A Query Language for Customizing Recommendations. SSRN Electronic Journal.1 indexed citations
13.
Adomavičius, Gediminas & Young Ok Kwon. (2011). CEUR Workshop Proceedings. Conference on Recommender Systems.166 indexed citations
14.
Adomavičius, Gediminas, et al.. (2011). 3rd workshop on context-aware recommender systems (CARS 2011). CEUR Workshop Proceedings. 791.3 indexed citations
15.
Bockstedt, Jesse, Gediminas Adomavičius, & Alok Gupta. (2010). Modeling Supply-Side Dynamics of IT Components, Products, and Infrastructure: An Empirical Analysis Using Vector Autoregression. SSRN Electronic Journal.10 indexed citations
16.
Adomavičius, Gediminas, et al.. (2008). Scalable temporal clustering for massive multidimensional data streams. 121–126.1 indexed citations
17.
Adomavičius, Gediminas, et al.. (2008). Design and Evaluation of Feedback Schemes for Multiattribute Procurement Auctions. Journal of the Association for Information Systems. 32.7 indexed citations
Adomavičius, Gediminas & Alexander Tuzhilin. (2005). Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering. 17(6). 734–749.6478 indexed citations breakdown →
20.
Adomavičius, Gediminas & Alexander Tuzhilin. (1997). Discovery of Actionable Patterns in Databases: The Action Hierarchy Approach. The Faculty Digital Archive (New York University). 111–114.32 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.