Publications

2019

  1. Meta-GNN: Metagraph Neural Network for Semi-supervised learning in Attributed Heterogeneous Information Networks. Aravind Sankar, Xinyang Zhang, Kevin Chen-Chuan Chang. In ASONAM 2019, 2019. PDF.
  2. Hierarchical Multi-Armed Bandits for Discovering Hidden Populations. Suhansanu Kumar, Heting Gao, Changyu Wang, Kevin Chen-Chuan Chang, Hari Sundaram. In ASONAM 2019, 2019. PDF.
  3. Anti-Freeze for Large and Complex Spreadsheets: Asynchronous Formula Computation. Mangesh Bendre, Tana Wattanawaroon, Kelly Mack, Kevin Chen-Chuan Chang, Aditya G. Parameswaran. In SIGMOD 2019, 2019. PDF. Bibtex.
  4. Faster, Higher, Stronger: Redesigning Spreadsheets for Scale. Mangesh Bendre, Tana Wattanawaroon, Sajjadur Rahman, Kelly Mack, Yuyang Liu, Shichu Zhu, Yu Lu, Ping-Jing Yang, Xinyan Zhou, Kevin Chen-Chuan Chang, Karrie Karahalios, Aditya G. Parameswaran. In ICDE 2019, 2019. PDF. Bibtex.
  5. Discovering Maximal Motif Cliques in Large Heterogeneous Information Networks. Jiafeng Hu, Reynold Cheng, Kevin Chen-Chuan Chang, Aravind Sankar, Yixiang Fang, Brian Y. H. Lam. In ICDE 2019, 2019. PDF. Bibtex.
  6. Nonintrusive Smartphone User Verification Using Anonymized Multimodal Data. Hong Cao and Kevin Chen-Chuan Chang. IEEE Trans. Knowl. Data Eng., 31(6):479--492, 2019. PDF. Bibtex.
  7. Metagraph-based Learning on Heterogeneous Graphs. Yuan Fang and Wenqing Lin and Vincent W. Zheng and Min Wu and Jiaqi Shi and Kevin Chen-Chuan Chang and Xiao-Li Li. IEEE Trans. Knowl. Data Eng., 2019. PDF. Bibtex.

2018

  1. Distance-Aware DAG Embedding for Proximity Search on Heterogeneous Graphs. Zemin Liu, Vincent W. Zheng, Zhou Zhao, Fanwei Zhu, Kevin Chen-Chuan Chang, Minghui Wu, Jing Ying. In AAAI 2018, 2018. PDF. Bibtex.
  2. Subgraph-Augmented Path Embedding for Semantic User Search on Heterogeneous Social Network. Zemin Liu, Vincent W. Zheng, Zhou Zhao, Hongxia Yang, Kevin Chen-Chuan Chang, Minghui Wu, Jing Ying. In WWW 2018, 2018. PDF. Bibtex.
  3. Leveraging Fine-Grained Wikipedia Categories for Entity Search. Denghao Ma, Yueguo Chen, Kevin Chen-Chuan Chang, Xiaoyong Du, Chuanfei Xu, Yi Chang. In WWW 2018, 2018. PDF. Bibtex.
  4. Towards a Holistic Integration of Spreadsheets With Databases: A Scalable Storage Engine for Presentational Data Management. Mangesh Bendre, Vipul Venkataraman, Xinyan Zhou, Kevin Chen-Chuan Chang, Aditya Parameswaran. In ICDE 2018, 2018. PDF. Bibtex.
  5. Characterizing Scalability Issues in Spreadsheet Software Using Online Forums. Kelly Mack, John Lee, Kevin Chen-Chuan Chang, Karrie Karahalios, Aditya G. Parameswaran. In CHI 2018, 2018. PDF. Bibtex.
  6. Heterogeneous Embedding Propagation for Large-Scale E-Commerce User Alignment. Vincent W. Zheng, Mo Sha, Yuchen Li, Hongxia Yang, Yuan Fang, Zhenjie Zhang, Kian-Lee Tan, Kevin Chen-Chuan Chang. In ICDM 2018, 2018. PDF. Bibtex.
  7. Deep-Web Search. Kevin Chen-Chuan Chang. In Encyclopedia of Database Systems, Second Edition, 2018. Bibtex.
  8. A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications. HongYun Cai and Vincent Wenchen Zheng and Kevin Chen-Chuan Chang. IEEE Trans. Knowl. Data Eng., 30(4):1616--1637, 2018. PDF. Bibtex.
  9. Semi-Supervised Learning Meets Factorization: Learning to Recommend With Chain Graph Model. Chaochao Chen and Kevin Chen-Chuan Chang and Qibing Li and Xiaolin Zheng. TKDD, 12(8):73:1--73:24, 2018. PDF. Bibtex.
  10. Authenticity and Credibility Aware Detection of Adverse Drug Events From Social Media. Tao Hoang and Jixue Liu and Nicole Pratt and Vincent W. Zheng and Kevin Chen-Chuan Chang and Elizabeth Roughead and Jiuyong Li. I. J. Medical Informatics, 120(9):101--115, 2018. PDF. Bibtex.

2017

  1. Semantic Proximity Search on Heterogeneous Graph by Proximity Embedding. Z. Liu, V. W. Zheng, Z. Zhao, F. Zhu, K. C.-C. Chang, M. Wu, and J. Ying. In AAAI 2017, pages 154-160, 2017. PDF BibTex
  2. From Community Detection to Community Profiling. H. Cai, V. W. Zheng, F. Zhu, K. C. Chang, and Z. Huang. PVLDB, 10(7):817-828, 2017. PDF BibTex
  3. Learning Community Embedding with Community Detection and Node Embedding on Graphs. S. Cavallari, V. W. Zheng, H. Cai, K. C. Chang, and E. Cambria. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM 2017, Singapore, November 06 - 10, 2017, pages 377-386, 2017. PDF BibTex
  4. SocialLens: Searching and Browsing Communities by Content and Interaction. H. Cai, V. W. Zheng, P. Chen, F. Zhu, K. C. Chang, and Z. Huang. In 33rd IEEE International Conference on Data Engineering, ICDE 2017, San Diego, CA, USA, April 19-22, 2017, pages 1397-1398, 2017. PDF BibTex
  5. Topological Recurrent Neural Network for Diffusion Prediction. J. Wang, V. W. Zheng, Z. Liu, and K. C. Chang. In 2017 IEEE International Conference on Data Mining, ICDM 2017, New Orleans, LA, USA, November 18-21, 2017, pages 475-484, 2017. PDF BibTex
  6. Statistical Link Label Modeling for Sign Prediction: Smoothing Sparsity by Joining Local and Global Information. A. Javari, H. Qiu, E. Barzegaran, M. Jalili, and K. C. Chang. In 2017 IEEE International Conference on Data Mining, ICDM 2017, New Orleans, LA, USA, November 18-21, 2017, pages 1039-1044, 2017. PDF BibTex

2016

  1. Semantic Proximity Search on Graphs with Metagraph-based Learning. Y. Fang, W. Lin, V. W. Zheng, M. Wu, K. C.-C. Chang, and X. Li. In ICDE 2016, pages 277-288, 2016. PDF Slides BibTexCode
  2. Learning to Query: Focused Web Page Harvesting for Entity Aspects. Y. Fang, V. W. Zheng, and K. C.-C. Chang. In ICDE 2016, pages 1002-1013, 2016. PDF Slides BibTex
  3. Cold-Start Heterogeneous-Device Wireless Localization. V. W. Zheng, H. Cao, S. Gao, A. Adhikari, M. Lin, and K. C.-C. Chang. In AAAI 2016, pages 1429-1435, 2016. PDF Slides BibTex
  4. Regularizing Structured Classifier with Conditional Probabilistic Constraints for Semi-supervised Learning. V. W. Zheng and K. C.-C. Chang. In CIKM 2016, 2016. (165/935 = 17.6%). PDFBibTex Dataset Code
  5. ARISE-PIE: A People Information Integration Engine over the Web. V. Zheng, T. Hoang, P. Chen, Y. Fang, X. Yang, and K. C.-C. Chang. In CIKM 2016 Workshop on Data-Driven Talent Acquisition, 2016. PDF
  6. Detecting Signals of Detrimental Prescribing Cascades from Social Media. T. Hoang, J. Liu, N. Pratt, V. W. Zheng, K. C.-C. Chang, E. Roughead, and J. Li. Artificial Intelligence in Medicine, 71:43-56, 2016. PDF BibTex

2015

  1. DataSpread: Unifying Databases and Spreadsheets. M. Bendre, B. Sun, D. Zhang, X. Zhou, K. C. Chang, and A. Parameswaran. PVLDB, 8(12):2000-2003, 2015. Demonstration description. PDF BibTex
  2. IntelligShop: Enabling Intelligent Shopping in Malls through Location-based Augmented Reality. A. Adhikari, V. W. Zheng, H. Cao, M. Lin, Y. Fang, and K. C.-C. Chang. In 2015 IEEE International Conference on Data Mining, ICDM 2015, pages 1604-1607, 2015. Demonstration description. PDF BibTex
  3. Mobile User Verification/Identification using Statistical Mobility Profile. M. Lin, H. Cao, V. Zheng, K. C.-C. Chang, and S. Krishnaswamy. In International Conference on Big Data and Smart Computing (BigComp 2015), pages 15-18, 2015. PDF BibTex
  4. Mobility Profiling for User Verification with Anonymized Location Data. M. Lin, H. Cao, V. Zheng, K. C.-C. Chang, and S. Krishnaswamy. In International Joint Conference on Artificial Intelligence (IJCAI 2015), pages 960-966, 2015. PDF BibTex
  5. Scheduled approximation for Personalized PageRank with Utility-based Hub Selection. F. Zhu, Y. Fang, K. C.-C. Chang, and J. Ying. The VLDB Journal, Springer Berlin Heidelberg, pages 655-679, 2015. PDF Slides BibTex Dataset Code
  6. Ushio: Analyzing News Media and Public Trends in Twitter. F. Yao, K. C. Chang, and R. H. Campbell. In 8th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2015, Limassol, Cyprus, December 7-10, 2015, pages 424-429, Dec 2015. PDF Slides BibTex

2014

  1. Unifying Learning to Rank and Domain Adaptation: Enabling Cross-Task Document Scoring. M. Zhou and K. C.-C. Chang. In KDD 2014, pages 781-790, 2014. (151/1036 = 14.6%). PDF SlidesBibTex Dataset
  2. Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically. Y. Fang, K. C.-C. Chang, and H. W. Lauw. In ICML 2014, pages 406-414, 2014. (310/1238=25%). PDF Slides BibTex
  3. User Profiling in an Ego Network: Co-profiling Attributes and Relationships. R. Li, C. Wang, and K. C.-C. Chang. In WWW 2014, pages 819-830, April 2014. (84/650 = 12.9%). PDF SlidesBibTex Dataset
  4. Privacy Risk in Anonymized Heterogeneous Information Networks. A. Zhang, X. Xie, K. Chang, C. Gunter, J. Han, and X. Wang. In EDBT 2014, pages 595-606, March 2014. (52/266 = 19.5%). PDF BibTex
  5. Towards a Social Media Analytics Platform: Event Detection and User Profiling for Twitter. M. Gupta, R. Li, and K. C.-C. Chang. In WWW 2014, pages 193-194, April 2014. Tutorial description. PDF Slides BibTex

2013

  1. Towards Social Data Platform: Automatic Topic-focused Monitor for Twitter Stream. R. Li, S. Wang, and K. C.-C. Chang. PVLDB, 6(14):1966-1977, 2013. In VLDB 2014. (Approx 17%). PDFSlides BibTex Dataset
  2. Enabling Entity-Centric Document Filtering by Meta-Feature-based Feature Mapping. M. Zhou and K. C.-C. Chang. In CIKM 2013, pages 119-128, 2013. (143/848 = 16.8%). PDF Slides BibTexDataset
  3. Incremental and Accuracy-Aware Personalized PageRank through Scheduled Approximation. F. Zhu, Y. Fang, K. C.-C. Chang, and J. Ying. PVLDB, 6(6):481-492, 2013. In VLDB 2013. (Approx 17%). PDF Slides BibTex Dataset Code
  4. RoundTripRank: Graph-based Proximity with Importance and Specificity. Y. Fang, K. C.-C. Chang, and H. W. Lauw. In ICDE 2013, pages 613-624, 2013. (92/460 = 20%). PDF Slides BibTexDataset
  5. Learning to Rank from Distant Supervision: Exploiting Noisy Redundancy for Relational Entity Search. M. Zhou, H. Wang, and K. C.-C. Chang. In ICDE 2013, pages 829-840, 2013. (92/460 = 20%). PDF Slides BibTex

2012

  1. Multiple Location Profiling for Users and Relationships from Social Network and Content. R. Li, S. Wang, and K. C.-C. Chang. PVLDB, 5(11):1603-1614, 2012. In VLDB 2012. (134/659=20.3%). PDF Slides BibTex Dataset
  2. Towards Social User Profiling: Unified and Discriminative Influence Model for Inferring Home Locations. R. Li, S. Wang, H. Deng, R. Wang, and K. C.-C. Chang. In KDD 2012, pages 1023-1031, 2012. (Approx 15%). PDF Slides BibTex Dataset
  3. Confidence-Aware Graph Regularization with Heterogeneous Pairwise Features. Y. Fang, B.-J. P. Hsu, and K. C.-C. Chang. In SIGIR 2012, pages 951-960, 2012. PDF Slides BibTex
  4. TEDAS: a Twitter Based Event Detection and Analysis System. R. Li, K. H. Lei, R. Khadiwala, and K. C.-C. Chang. In ICDE 2012, pages 1273-1276, 2012. Demonstration description. PDF

2011

  1. Searching Patterns for Relation Extraction over the Web: Rediscovering the Pattern-Relation Duality. Y. Fang and K. C.-C. Chang. In WSDM 2011, pages 825-834, 2011. (83/372=22%). PDFBibTex

2010

  1. Towards Rich Query Interpretation: Walking Back and Forth for Mining Query Templates. G. Agarwal, G. Kabra, and K. C.-C. Chang. In WWW 2010, pages 1-10, 2010. (104/743=14%). PDFSlides BibTex
  2. Beyond Pages: Supporting Efficient, Scalable Entity Search. T. Cheng and K. C.-C. Chang. In EDBT 2010, pages 15-26, 2010. (54/307=18%). PDF Slides BibTex
  3. Data-oriented Content Query System: Searching for Data into Text on the Web. M. Zhou, T. Cheng, and K. C.-C. Chang. In WSDM 2010, pages 121-130, 2010. (45/290=15.5%). PDF SlidesBibTex
  4. DoCQS: a prototype system for supporting data-oriented content query. M. Zhou, T. Cheng, and K. C.-C. Chang. In SIGMOD 2010, pages 1211-1214, 2010. Demonstration description. PDF
  5. Object Search: Supporting Structured Queries in Web Search Engines. K. Pham, N. Rizzolo, K. Small, K. C.-C. Chang, and D. Roth. In NAACL-HLT Workshop on Semantic Search, Los Angeles, June 2010. PDF

2009

  1. Deep-Web Search. K. C.-C. Chang. In Encyclopedia of Database Systems, pages 784-788. Springer, 2009.
  2. AIDE: ad-hoc intents detection engine over query logs. Y. Jiang, H.-T. Yang, K. C.-C. Chang, and Y.-S. Chen. In SIGMOD 2009, pages 1091-1094, 2009. Demonstration description. PDF

2008

  1. Integrating Web Query Results: Holistic Schema Matching. S.-L. Chuang and K. C.-C. Chang. In CIKM 2008, pages 33-42, 2008. (132/772=17%). PDF Slides BibTex
  2. Probabilistic top-k and ranking-aggregate queries. M. A. Soliman, I. F. Ilyas, and K. C.-C. Chang. ACM Trans. Database Syst., 33(3), 2008. PDF
  3. Trustworthy keyword search for compliance storage. S. Mitra, M. Winslett, W. W. Hsu, and K. C.-C. Chang. VLDB J., 17(2):225-242, 2008. PDF

2007

  1. EntityRank: Searching Entities Directly and Holistically. T. Cheng, X. Yan, and K. C.-C. Chang. In Proceedings of the 33rd Very Large Data Bases Conference (VLDB 2007), pages 387-398, Vienna, Austria, September 2007. (91/538=16.9%). PDF Slides BibTex
  2. Context-Aware Wrapping: Synchronized Data Extraction. S.-L. Chuang, K. C.-C. Chang, and C. Zhai. In Proceedings of the 33rd Very Large Data Bases Conference (VLDB 2007), pages 699-710, Vienna, Austria, September 2007. (91/538=16.9%). PDF Slides BibTex
  3. Supporting Ranking and Clustering as Generalized Order-By and Group-By. C. Li, M. Wang, L. Lim, H. Wang, and K. C.-C. Chang. In Proceedings of the 2007 ACM SIGMOD Conference (SIGMOD 2007), pages 127-138, Beijing, China, June 2007. (70/480=14.6%). PDF Slides
  4. Progressive and Selective Merge: Computing Top-K with Ad-hoc Ranking Functions. D. Xin, J. Han, and K. C.-C. Chang. In Proceedings of the 2007 ACM SIGMOD Conference (SIGMOD 2007), pages 103-114, Beijing, China, June 2007. (70/480=14.6%). PDF Slides
  5. Entity Search Engine: Towards Agile Best-Effort Information Integration over the Web. T. Cheng and K. C.-C. Chang. In Proceedings of the Third Conference on Innovative Data Systems Research (CIDR 2007), pages 108-113, Asilomar, Ca., January 2007. Extended System Demo Description. PDF Slides BibTex
  6. Top-k Query Processing in Uncertain Databases. M. A. Soliman, I. F. Ilyas, and K. C.-C. Chang. In Proceedings of the 23rd International Conference on Data Engineering (ICDE 2007), pages 896-905, Istanbul, Turkey, April 2007. (122/659=18%). PDF
  7. Collaborative Wrapping: A Turbo Framework for Web Data Extraction. S.-L. Chiang, K. C.-C. Chang, and C. Zhai. In Proceedings of the 23rd International Conference on Data Engineering (ICDE 2007), pages 1261-1262, Istanbul, Turkey, April 2007. (Poster Paper; 182/659=27%). PDF
  8. Accessing the Deep Web: A Survey. B. He, M. Patel, Z. Zhang, and K. C.-C. Chang. Communications of the ACM, 50(5):94-101, May 2007. PDF
  9. Optimizing Top-k Queries for Middleware Access: A Unified Cost-based Approach. S.-W. Hwang and K. C.-C. Chang. ACM Transactions on Database Systems (TODS), 32(1):5, March 2007. PDF
  10. Probe Minimization by Schedule Optimization: Supporting Top-k Queries with Expensive Predicates. S.-W. Hwang and K. C.-C. Chang. IEEE Transactions on Knowledge and Data Engineering (TKDE), 19(5):646-662, May 2007. PDF
  11. Supporting Entity Search: a Large-Scale Prototype Search Engi1ne. T. Cheng, X. Yang, and K. C.-C. Chang. In Proceedings of the 2007 ACM SIGMOD Conference (SIGMOD 2007), pages 1144-1146, Beijing, China, June 2007. Demonstration description. (35/107 = 32%). PDF
  12. URank: Top-k Query Processing for Uncertain Databases. M. Sliman, I. Ilyas, and K. C.-C. Chang. In Proceedings of the 2007 ACM SIGMOD Conference (SIGMOD 2007), pages 1082-1084, Beijing, China, June 2007. Demonstration description. (35/107 = 32%). PDF
  13. Dewex: A Search Engine for Exploring the Deep Web. G. Kabra, Z. Zhang, and K. C.-C. Chang. In Proceedings of the 23rd International Conference on Data Engineering (ICDE 2007), pages 1511-1512, Istanbul, Turkey, April 2007. Demonstration description. PDF

2006

  1. Supporting Ad-hoc Ranking Aggregates. C. Li, K. C.-C. Chang, and I. F. Ilyas. In Proceedings of the 2006 ACM SIGMOD Conference (SIGMOD 2006), pages 61-72, Chicago, June 2006. (58/446=13%). PDF Slides
  2. Boolean + Ranking: Querying a Database by K-Constrained Optimization. Z. Zhang, S. Hwang, K. C.-C. Chang, M. Wang, C. Lang, and Y. Chang. In Proceedings of the 2006 ACM SIGMOD Conference (SIGMOD 2006), pages 359-370, Chicago, June 2006. (58/446=13%). PDF Slides
  3. Automatic Complex Schema Matching across Web Query Interfaces: A Correlation Mining Approach. B. He and K. C.-C. Chang. ACM Transactions on Database Systems (TODS), 31(1):346-395, March 2006. PDF
  4. Accessing the Web: From Search to Integration. K. C.-C. Chang and J. Cho. In Proceedings of the 2006 ACM SIGMOD Conference (SIGMOD 2006), pages 804-805, Chicago, June 2006. Tutorial description. PDF Slides

2005

  1. Light-weight Domain-based Form Assistant: Querying Web Databases On the Fly. Z. Zhang, B. He, and K. C.-C. Chang. In Proceedings of the 31st Very Large Data Bases Conference (VLDB 2005), pages 97-108, Trondheim, Norway, August 2005. (32/195=16%). PDF Slides
  2. Making Holistic Schema Matching Robust: An Ensemble Approach. B. He and K. C.-C. Chang. In Proceedings of the 2005 ACM SIGKDD Conference (KDD 2005), pages 429-438, Chicago, Illinois, August 2005. (14/75=19%). PDF Slides
  3. RankSQL: Query Algebra and Optimization for Relational Top-k Queries. C. Li, K. C.-C. Chang, I. F. Ilyas, and S. Song. In Proceedings of the 2005 ACM SIGMOD Conference (SIGMOD 2005), pages 131-142, Baltimore, Maryland, June 2005. (66/431=15%). PDF Slides
  4. Toward Large Scale Integration: Building a MetaQuerier over Databases on the Web. K. C.-C. Chang, B. He, and Z. Zhang. In Proceedings of the Second Conference on Innovative Data Systems Research (CIDR 2005), pages 44-55, Asilomar, Ca., January 2005. (26/86=30%). PDF Slides
  5. RankFP: A Framework for Supporting Rank Formulation and Processing. H. Yu, S. Hwang, and K. C.-C. Chang. In Proceedings of the 21st International Conference on Data Engineering (ICDE 2005), pages 514-515, Tokyo, Japan, April 2005. (Poster Paper; 100/521=19%). PDF Slides
  6. Optimizing Access Cost for Top-k Queries over Web Sources: A Unified Cost-based Approach. S. Hwang and K. C.-C. Chang. In Proceedings of the 21st International Conference on Data Engineering (ICDE 2005), pages 188-189, Tokyo, Japan, April 2005. (Poster Paper; 100/521=19%). PDF Slides
  7. RankSQL: Supporting Ranking Queries in Relational Database Management Systems. C. Li, M. A. Soliman, K. C.-C. Chang, and I. F. Ilyas. In Proceedings of the 31st Very Large Data Bases Conference (VLDB 2005), pages 1342-1345, Trondheim, Norway, August 2005. Demonstration description. (29/69 = 42%). PDF
  8. MetaQuerier: Querying Structured Web Sources On-the-fly. B. He, Z. Zhang, and K. C.-C. Chang. In Proceedings of the 2005 ACM SIGMOD Conference (SIGMOD 2005), pages 927-929, Baltimore, Maryland, June 2005. Demonstration description. (24/71 = 34%). PDF
  9. Towards Building a MetaQuerier: Extracting and Matching Web Query Interfaces. B. He, Z. Zhang, and K. C.-C. Chang. In Proceedings of the 21st International Conference on Data Engineering (ICDE 2005), pages 1098-1099, Tokyo, Japan, April 2005. Demonstration description. PDF
  10. Query Routing: Finding Ways in the Maze of the Deep Web. G. Kabra, C. Li, and K. C.-C. Chang. In Proceedings of the ICDE International Workshop on Challenges in Web Information Retrieval and Integration (ICDE-WIRI 2005), Tokyo, Japan, April 2005. (14/47=30%). PDF

2004

  1. Organizing Structured Web Sources by Query Schemas: A Clustering Approach. B. He, T. Tao, and K. C.-C. Chang. In Proceedings of the 13th Conference on Information and Knowledge Management (CIKM 2004), pages 22-31, Washington, D.C., November 2004. (59/303=19%). PDF Slides
  2. Optimal Multimodal Fusion for Multimedia Data Analysis. Y. Wu, E. Y. Chang, K. C.-C. Chang, and J. R. Smith. In Proceedings of the 12th ACM International Conference on Multimedia (MM 2004), pages 572-579, New York, October 2004. (56/330=17%).
  3. Discovering Complex Matchings across Web Query Interfaces: A Correlation Mining Approach. B. He, K. C.-C. Chang, and J. Han. In Proceedings of the 2004 ACM SIGKDD Conference (KDD 2004), pages 148-157, Seattle, Wa., August 2004. (40/337=12%). PDF Slides
  4. Understanding Web Query Interfaces: Best-Effort Parsing with Hidden Syntax. Z. Zhang, B. He, and K. C.-C. Chang. In Proceedings of the 2004 ACM SIGMOD Conference (SIGMOD 2004), pages 117-118, Paris, France, June 2004. (69/431=16%). PDF Slides
  5. Mining Semantics for Large Scale Integration on the Web: Evidences, Insights, and Challenges. K. C.-C. Chang, B. He, and Z. Zhang. SIGKDD Explorations, 6(2):67-76, December 2004. PDF
  6. Editorial: Special Issue on Web Content Mining. B. Liu and K. C.-C. Chang. SIGKDD Explorations, 6(2):1-4, December 2004. PDF
  7. A Holistic Paradigm for Large Scale Schema Matching. B. He and K. C.-C. Chang. SIGMOD Record, 33(4):20-25, December 2004. Invited paper. PDF
  8. Structured Databases on the Web: Observations and Implications. K. C.-C. Chang, B. He, C. Li, M. Patel, and Z. Zhang. SIGMOD Record, 33(3):61-70, September 2004. PDF
  9. PEBL: Web Page Classification without Negative Examples. H. Yu, J. Han, and K. C.-C. Chang. IEEE Transactions on Knowledge and Data Engineering, 16(1):70-81, January 2004. Special Section on Mining and Searching the Web. PDF
  10. Towards Building a MetaQuerier: Extracting and Matching Web Query Interfaces. B. He, Z. Zhang, and K. C.-C. Chang. In NSF Information and Data Management (IDM) Workshop 2004, Boston, Massachussetts, October 2004. Demonstration description.
  11. Knocking the Door to the Deep Web: Integrating Web Query Interfaces. B. He, Z. Zhang, and K. C.-C. Chang. In Proceedings of the 2004 ACM SIGMOD Conference (SIGMOD 2004), pages 913-914, Paris, France, June 2004. Demonstration description. PDF
  12. MetaQuerier over the Deep Web: Shallow Integration across Holistic Sources. K. C.-C. Chang, B. He, and Z. Zhang. In Proceedings of the VLDB Workshop on Information Integration on the Web (VLDB-IIWeb 2004), Toronto, Canada, August 2004. (20/42=48%). PDF
  13. On-the-fly Constraint Mapping across Web Query Interfaces. Z. Zhang, B. He, and K. C.-C. Chang. In Proceedings of the VLDB Workshop on Information Integration on the Web (VLDB-IIWeb 2004), Toronto, Canada, August 2004. (20/42=48%). PDF
  14. Mining Complex Matchings across Web Query Interfaces. B. He, K. C.-C. Chang, and J. Han. In Proceedings of the 9th ACM SIGMOD Workshop on Research Issues on Data Mining and Knowledge Discovery (SIGMOD-DMKD 2004), pages 3-10, Paris, France, June 2004. (8/34=24%). PDF
  15. Clustering Structured Web Sources: A Schema-Based, Model-Differentiation Approach.. B. He, T. Tao, and K. C.-C. Chang. In EDBT Workshops (EDBT-ClustWeb 2004), pages 536-546, Crete, Greece, March 2004. (9/15=60%). PDF

2003

  1. Statistical Schema Matching across Web Query Interfaces. B. He and K. C.-C. Chang. In Proceedings of the 2003 ACM SIGMOD Conference (SIGMOD 2003), pages 217-228, San Diego, California, June 2003. (52/342=15%). PDF Slides
  2. Knocking the Doors to the Deep Web: Understanding Web Query Interfaces. Z. Zhang, B. He, and K. C.-C. Chang. In NSF Information and Data Management (IDM) Workshop 2003, Seattle, Washington, September 2003. Demonstration description.

2002

  1. Heterogeneous Learner for Web Page Classification. H. Yu, K. C.-C. Chang, and J. Han. In Proceedings of the 2002 IEEE International Conference on Data Mining (ICDM 2002), pages 538-545, Maebashi, Japan, December 2002. (72/369=20%). PDF
  2. PEBL: Positive Example Based Learning for Web Page Classification Using SVM. H. Yu, J. Han, and K. C.-C. Chang. In Proceedings of the 2002 ACM SIGKDD Conference (KDD 2002), pages 239-248, Edmonton, Alberta, Canada, July 2002. (44/308=14%). PDF
  3. Minimal Probing: Supporting Expensive Predicates for Top-k Queries. K. C.-C. Chang and S.-W. Hwang. In Proceedings of the 2002 ACM SIGMOD Conference (SIGMOD 2002), pages 346-357, Madison, Wisconsin, June 2002. (42/239=18%). PDF Slides
  4. Data Mining for Web Intelligence. J. Han and K. C.-C. Chang. IEEE Computer, IEEE Computer Society, Washington, D.C., 35(11):64-70, November 2002. PDF
  5. Database Research at the University of Illinois at Urbana-Champaign. M. Winslett, K. C.-C. Chang, A. Doan, J. Han, C. Zhai, and Y. Zhou. SIGMOD Record, 31(3):97-102, September 2002. PDF

2001

  1. NBDL: A CIS Framework for NSDL. J. Futrelle, K. C.-C. Chang, and S.-S. Chen. In Proceedings of the First ACM/IEEE Joint Conference on Digital Libraries (JCDL 2001), pages 124-125, Roanoke, Virginia, June 2001. PDF
  2. Approximate Query Mapping: Accounting for Translation Closeness. K. C.-C. Chang and H. Garcia-Molina. The VLDB Journal, VLDB Foundation, Saratoga, Calif., 10(2-3):155-181, September 2001. PDF