Publications


  • Z. Yao*, X. Li, J. Gao, B. Sadler,  H. Sun, “Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning,” To appear in the AAAI Conference on Artificial Intelligence 2019 (AAAI’19, acceptance rate: 16.2%). Earlier on arXiv, 2018 [papercode]
  • L. Chen, Z. Guan, W. Zhao, W. Zhao, X. Wang, Z. Zhao, H. Sun, “Answer Identification from Product Reviews for User Questions by Multi-task Attentive Networks,” To appear in the AAAI Conference on Artificial Intelligence 2019 (AAAI’19, acceptance rate: 16.2%).
  • J. Peddamail*, Z. Yao*, Z. Wang*, H. Sun, “A Comprehensive Study of StaQC for Deep Code Summarization,” SIGKDD Deep Learning Day 2018. [paperslides] (SPOTLIGHT)
  • Z. Yao*, D. S. Weld, W.P. Chen, H. Sun, “StaQC: A Systematically Mined Question-Code Dataset from Stack Overflow,” The Web Conference (former WWW Conference) 2018 (WWW’18, acceptance rate: 14.8%). [papercode]
  • Y. Su, H. Liu, S. Yavuz, I. Gur, H. Sun, X. Yan, “Global Relation Embedding for Relation Extraction,” In Proc. of the Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018 (NAACL-HLT’18). [papercode]
  • J. Zhao*, Y. Su, Z. Guan, H. Sun, “An End-to-End Deep Framework for Answer Triggering with a Novel Group-Level Objective,” Empirical Methods in Natural Language Processing 2017 (EMNLP’17). [papercode]
  • Y. Li, N. Du, C. Liu, Y. Xie, W. Fan, Q. Li, J. Gao, H. Sun, “Reliable Medical Diagnosis from Crowdsourcing: Discover Trustworthy Answers from Non-Experts,” ACM Int. Conf. on Web Search and Data Mining 2017 (WSDM’17). [paper]
  • C. Liu, H. Sun, N. Du, S. Tan, H. Fei, W. Fan, T. Yang, H. Wu, Y. Li, C. Zhang, “Augmented LSTM Framework to Construct Medical Self-diagnosis Android,” IEEE Int. Conf. on Data Mining 2016 (ICDM’16). [paper]
  • Y. Su, H. Sun, B. Sadler, M. Srivatsa, I. Gur, Z. Yan, X. Yan, “On Generating Characteristic-rich Question Sets for QA Evaluation ,” Empirical Methods in Natural Language Processing 2016 (EMNLP’16). [paperappendixNew Question-Answer Set (with rich characteristics to train more advanced QA systems)]
  • H. Sun, H. Ma, X. He, W. Yih, Y. Su, X. Yan, “Table Cell Search for Question Answering,” The 25th Int. World Wide Web Conference (WWW’16). [paper]
  • Y. Li, S. Tan, H. Sun, J. Han, D. Roth, X. Yan, “Entity Disambiguation with Linkless Knowledge Bases,” The 25th Int. World Wide Web Conference (WWW’16). [paper]
  • F. Han, S. Tan, H. Sun, X. Yan, M. Srivatsa, D. Cai, “Distributed Representations of Expertise,” SIAM Int. Conf. on Data Mining 2016 (SDM’16). [paper]
  • H. Sun, H. Ma, W. Yih, C. Tsai, J. Liu, M. Chang, “Open Domain Question Answering via Semantic Enrichment,” The 24th Int. World Wide Web Conference (WWW’15, acceptance rate: 14.1%). [paper]
  • Y. Su, S. Yang, H. Sun, M. Srivatsa , S. Kase, M. Vanni, X. Yan, “Exploiting Relevance Feedback in Knowledge Graph Search”, Proc. of the 21st Int. Conf. on Knowledge Discovery and Data Mining (KDD’15, acceptance rate: 19.4%). [paper]
  • Z. Guan, S. Yang, H. Sun, M. Srivatsa, X. Yan, “Fine-Grained Knowledge Sharing in Collaborative Environments ,” Transactions on Knowledge and Data Engineering (TKDE 2015). [paper]
  • H. Sun, M. Srivatsa, S. Tan, Y. Li, L. Kaplan, S. Tao, X. Yan, “Analyzing Expert Behaviors in Collaborative Networks,” Proc. of the 20th Int. Conf. on Knowledge Discovery and Data Mining (KDD’14, acceptance rate: 14.6%). [paperslidesposterSource Code]
  • S. Yang, Y. Wu, H. Sun, X. Yan, “Schemaless and Structureless Graph Querying,” Proc. of Int. Conf. on Very Large Data Bases (VLDB’14).[paperposter]
  • S. Yang, Y. Xie, Y. Wu, T. Wu, H. Sun, J. Wu, X. Yan, “SLQ: A User-friendly Graph Querying System,” Proc. of Int. Conf. on Management of Data (SIGMOD’14, Demo Track).
  • H. Sun, M. Srivatsa, L. Kaplan, X. Yan, “Analyzing Expert Behaviors in Collaborative Networks,” International School and Conference on Network Science 2014 (NetSci’14).
  • N. Li, H. Sun, K. Chipman, J. George, X. Yan,“A Probabilistic Approach to Uncovering Attributed Graph Anomalies,” SIAM Int. Conf. on Data Mining 2014 (SDM’14, acceptance rate: 15.4%).[paper]
  • H. Sun, A. Morales, X. Yan,“Synthetic Review Spamming and Defense,” Proc. of the 19th Int. Conf. on Knowledge Discovery and Data Mining(KDD’13, acceptance rate: 17%). [paperposterDemo]
  • S. Tan, Y. Li, H. Sun, Z. Guan, X. Yan, J. Bu, C. Chen, X.He. “Interpreting the Public Sentiment Variations on Twitter”, Transactions on Knowledge and Data Engineering (TKDE 2014).[paper]
  • H. Sun, G. Miao, X. Yan, “Noise-Resistant Bicluster Recognition,” IEEE Int. Conf. on Data Mining 2013 (ICDM’13, Oral presentation, acceptance rate: 11.6%).[paper] [slides][homepage] [A talk related to deep learning literature and techniques in this paper]
  • A. Morales, H. Sun, X. Yan,“Synthetic Review Spamming and Defense,” Proc. Of the 22nd International World Wide Web Conference (WWW’13, Companion Volume).
  • H. Sun, G. Miao, X. Yan, “Noise-Resistant Bicluster Recognition,” the 17th Annual International Conference on Research in Computational Molecular Biology (RECOMB’13, Poster).