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Bee-Chung Chen
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2020 – today
- 2020
- [c36]Weiwei Guo, Xiaowei Liu, Sida Wang, Huiji Gao, Ananth Sankar, Zimeng Yang, Qi Guo, Liang Zhang, Bo Long, Bee-Chung Chen, Deepak Agarwal:
DeText: A Deep Text Ranking Framework with BERT. CIKM 2020: 2509-2516 - [i3]Weiwei Guo, Xiaowei Liu, Sida Wang, Huiji Gao, Ananth Sankar, Zimeng Yang, Qi Guo, Liang Zhang, Bo Long, Bee-Chung Chen, Deepak Agarwal:
DeText: A Deep Text Ranking Framework with BERT. CoRR abs/2008.02460 (2020)
2010 – 2019
- 2019
- [c35]Weiwei Guo, Huiji Gao, Jun Shi, Bo Long, Liang Zhang, Bee-Chung Chen, Deepak Agarwal:
Deep Natural Language Processing for Search and Recommender Systems. KDD 2019: 3199-3200 - 2018
- [r3]Bee-Chung Chen:
Spatiotemporal Personalized Recommendation of Social Media Content. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - 2017
- [c34]Guangde Chen, Bee-Chung Chen, Deepak Agarwal:
Social Incentive Optimization in Online Social Networks. WSDM 2017: 547-556 - [c33]Liangyue Li, How Jing, Hanghang Tong
, Jaewon Yang, Qi He
NEMO: Next Career Move Prediction with Contextual Embedding. WWW (Companion Volume) 2017: 505-513 - 2016
- [c32]Navneet Kapur, Nikita I. Lytkin, Bee-Chung Chen, Deepak Agarwal, Igor Perisic:
Ranking Universities Based on Career Outcomes of Graduates. KDD 2016: 137-144 - [c31]Liang Tang, Bo Long, Bee-Chung Chen, Deepak Agarwal:
An Empirical Study on Recommendation with Multiple Types of Feedback. KDD 2016: 283-292 - [c30]XianXing Zhang, Yitong Zhou, Yiming Ma, Bee-Chung Chen, Liang Zhang, Deepak Agarwal:
GLMix: Generalized Linear Mixed Models For Large-Scale Response Prediction. KDD 2016: 363-372 - 2015
- [c29]Deepak Agarwal, Bee-Chung Chen, Qi He
Personalizing LinkedIn Feed. KDD 2015: 1651-1660 - 2014
- [c28]Deepak Agarwal, Bee-Chung Chen, Rupesh Gupta, Joshua Hartman, Qi He
Activity ranking in LinkedIn feed. KDD 2014: 1603-1612 - [r2]Bee-Chung Chen:
Spatiotemporal Personalized Recommendation of Social Media Content. Encyclopedia of Social Network Analysis and Mining 2014: 2010-2018 - 2013
- [j5]Deepak Agarwal, Bee-Chung Chen, Pradheep Elango, Raghu Ramakrishnan:
Content recommendation on web portals. Commun. ACM 56(6): 92-101 (2013) - [c27]Rajiv Khanna, Liang Zhang, Deepak Agarwal, Bee-Chung Chen:
Parallel matrix factorization for binary response. IEEE BigData 2013: 430-438 - [c26]Jaewon Yang, Bee-Chung Chen, Deepak Agarwal:
Estimating sharer reputation via social data calibration. KDD 2013: 59-67 - 2012
- [c25]Deepak Agarwal, Bee-Chung Chen, Xuanhui Wang:
Multi-faceted ranking of news articles using post-read actions. CIKM 2012: 694-703 - [c24]Deepak Agarwal, Bee-Chung Chen, Pradheep Elango, Xuanhui Wang:
Personalized click shaping through lagrangian duality for online recommendation. SIGIR 2012: 485-494 - [c23]Bee-Chung Chen, Anirban Dasgupta
Vote calibration in community question-answering systems. SIGIR 2012: 781-790 - [i2]Rajiv Khanna, Liang Zhang, Deepak Agarwal, Bee-Chung Chen:
Parallel Matrix Factorization for Binary Response. CoRR abs/1203.5124 (2012) - [i1]Deepak Agarwal, Bee-Chung Chen, Xuanhui Wang:
Multi-Faceted Ranking of News Articles using Post-Read Actions. CoRR abs/1205.0591 (2012) - 2011
- [c22]Deepak Agarwal, Bee-Chung Chen, Bo Pang:
Personalized Recommendation of User Comments via Factor Models. EMNLP 2011: 571-582 - [c21]Deepak Agarwal, Bee-Chung Chen, Pradheep Elango, Xuanhui Wang:
Click shaping to optimize multiple objectives. KDD 2011: 132-140 - [c20]Bee-Chung Chen, Jian Guo, Belle L. Tseng, Jie Yang:
User reputation in a comment rating environment. KDD 2011: 159-167 - [c19]Deepak Agarwal, Bee-Chung Chen, Bo Long:
Localized factor models for multi-context recommendation. KDD 2011: 609-617 - [c18]Liang Zhang, Deepak Agarwal, Bee-Chung Chen:
Generalizing matrix factorization through flexible regression priors. RecSys 2011: 13-20 - [c17]Deepak Agarwal, Bee-Chung Chen:
Latent OLAP: data cubes over latent variables. SIGMOD Conference 2011: 877-888 - [c16]Judd Antin, Elizabeth F. Churchill, Bee-Chung Chen:
Workshop on online reputation: context, privacy, and reputation management. WWW (Companion Volume) 2011: 321-322 - [r1]Kristen LeFevre, Bee-Chung Chen:
Adversarial/External Knowledge (Privacy in the Presence of). Encyclopedia of Cryptography and Security (2nd Ed.) 2011: 24-26 - 2010
- [c15]Deepak Agarwal, Bee-Chung Chen, Pradheep Elango:
Fast online learning through offline initialization for time-sensitive recommendation. KDD 2010: 703-712 - [c14]Deepak Agarwal, Bee-Chung Chen:
fLDA: matrix factorization through latent dirichlet allocation. WSDM 2010: 91-100
2000 – 2009
- 2009
- [j4]Bee-Chung Chen, Daniel Kifer, Kristen LeFevre, Ashwin Machanavajjhala:
Privacy-Preserving Data Publishing. Found. Trends Databases 2(1-2): 1-167 (2009) - [j3]Bee-Chung Chen, Raghu Ramakrishnan, Jude W. Shavlik, Pradeep Tamma:
Bellwether analysis: Searching for cost-effective query-defined predictors in large databases. ACM Trans. Knowl. Discov. Data 3(1): 5:1-5:49 (2009) - [j2]Bee-Chung Chen, Kristen LeFevre, Raghu Ramakrishnan:
Adversarial-knowledge dimensions in data privacy. VLDB J. 18(2): 429-467 (2009) - [c13]Deepak Agarwal, Bee-Chung Chen, Pradheep Elango:
Explore/Exploit Schemes for Web Content Optimization. ICDM 2009: 1-10 - [c12]Deepak Agarwal, Bee-Chung Chen:
Regression-based latent factor models. KDD 2009: 19-28 - [c11]Deepak Agarwal, Bee-Chung Chen, Pradheep Elango:
Spatio-temporal models for estimating click-through rate. WWW 2009: 21-30 - 2008
- [c10]Deepak Agarwal, Bee-Chung Chen, Pradheep Elango, Nitin Motgi, Seung-Taek Park, Raghu Ramakrishnan, Scott Roy, Joe Zachariah:
Online Models for Content Optimization. NIPS 2008: 17-24 - 2007
- [j1]Raghu Ramakrishnan, Bee-Chung Chen:
Exploratory mining in cube space. Data Min. Knowl. Discov. 15(1): 29-54 (2007) - [c9]Surajit Chaudhuri, Bee-Chung Chen, Venkatesh Ganti, Raghav Kaushik:
Example-driven design of efficient record matching queries. VLDB 2007: 327-338 - [c8]Bee-Chung Chen, Raghu Ramakrishnan, Kristen LeFevre:
Privacy Skyline: Privacy with Multidimensional Adversarial Knowledge. VLDB 2007: 770-781 - 2006
- [c7]Bee-Chung Chen, Lei Chen, Raghu Ramakrishnan, David R. Musicant:
Learning from Aggregate Views. ICDE 2006: 3 - [c6]Bee-Chung Chen, Vinod Yegneswaran, Paul Barford, Raghu Ramakrishnan:
Toward a Query Language for Network Attack Data. ICDE Workshops 2006: 28 - [c5]Lei Chen, Raghu Ramakrishnan, Paul Barford, Bee-Chung Chen, Vinod Yegneswaran:
Composite Subset Measures. VLDB 2006: 403-414 - [c4]Bee-Chung Chen, Raghu Ramakrishnan, Jude W. Shavlik, Pradeep Tamma:
Bellwether Analysis: Predicting Global Aggregates from Local Regions. VLDB 2006: 655-666 - 2005
- [c3]Bee-Chung Chen, Lei Chen, Yi Lin, Raghu Ramakrishnan:
Prediction Cubes. VLDB 2005: 982-993 - 2004
- [c2]Bee-Chung Chen, Jieh Hsiang:
A Logical Framework of Knowledge Retrieval with Fuzziness. Web Intelligence 2004: 524-528 - 2003
- [c1]Jieh Hsiang, Wen-Jun Liu, Bee-Chung Chen, Hsieh-Chang Tu:
Multidimensional interactive fine-grained image retrieval. ICME 2003: 297-300
Coauthor Index
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