Robert M. Bell | Academic Influence

Why Is Robert M. Bell Influential?

Robert Bell is a principal member of the technical staff at AT&T Labs—Research. His research interests are survey research methods and statistical learning methods. He received a PhD in statistics from Stanford University. Bell is a member of the American Statistical Association and the Institute of Mathematical Statistics.

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Robert M. Bell's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Matrix Factorization Techniques for Recommender Systems (2009) (7738)
Advances in Collaborative Filtering (2011) (1163)
Lessons from the Netflix prize challenge (2007) (796)
Predicting the location and number of faults in large software systems (2005) (713)
Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights (2007) (571)
Modeling relationships at multiple scales to improve accuracy of large recommender systems (2007) (405)
Recommender Systems Handbook (2011) (273)
Improved Neighborhood-based Collaborative Filtering (2007) (251)
The BellKor solution to the Netflix Prize (2007) (243)
Do too many cooks spoil the broth? Using the number of developers to enhance defect prediction models (2008) (172)
The BellKor 2008 Solution to the Netflix Prize (2008) (164)
Where the bugs are (2004) (138)
Comparing the effectiveness of several modeling methods for fault prediction (2010) (123)
Looking for bugs in all the right places (2006) (108)
Rethinking the progress bar (2007) (96)
Using Developer Information as a Factor for Fault Prediction (2007) (92)
All Together Now: A Perspective on the Netflix Prize (2010) (85)
Programmer-based fault prediction (2010) (84)
Building an Effective Representation for Dynamic Networks (2005) (67)
The limited impact of individual developer data on software defect prediction (2013) (63)
Automating algorithms for the identification of fault-prone files (2007) (55)
Does measuring code change improve fault prediction? (2011) (46)
Does calling structure information improve the accuracy of fault prediction? (2009) (43)
Mining customer care dialogs for "Daily News" (2005) (31)
Measurement and analysis of OSN ad auctions (2014) (24)
We're Finding Most of the Bugs, but What are We Missing? (2010) (16)
Comparing negative binomial and recursive partitioning models for fault prediction (2008) (15)
On the use of calling structure information to improve fault prediction (2012) (9)
Locating where faults will be [software testing] (2005) (7)
A Different View of Fault Prediction (2005) (7)
Replicate, Replicate, Replicate (2011) (6)
Assessing the Impact of Using Fault Prediction in Industry (2011) (5)
Defection detection: using activity profiles to predict ISP customer vulnerability (2000) (5)
Modifying boosted trees to improve performance on task 1 of the 2006 KDD challenge cup (2006) (3)
Tuning representations of dynamic network data (2005) (1)
Parallelization of Matrix Factorization for Recommender Systems (2010) (0)
Statistical Properties of Alternating Least Squares Estimators of a Collaborative Filtering Model (2011) (0)
Recommender System Strategies Matrix Factorization Techniques for Recommender Systems (2009) (0)
On the use of calling structure information to improve fault prediction (2011) (0)
The limited impact of individual developer data on software defect prediction (2011) (0)

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