Jiawei Han

Search results

• 2020

  AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types

  Dong, X. L., He, X., Kan, A., Li, X., Liang, Y., Ma, J., Xu, Y. E., Zhang, C., Zhao, T., Blanco Saldana, G., Deshpande, S., Michetti Manduca, A., Ren, J., Singh, S. P., Xiao, F., Chang, H. S., Karamanolakis, G., Mao, Y., Wang, Y., Faloutsos, C., & 2 othersMcCallum, A. & Han, J., Aug 23 2020, KDD 2020 - Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 2724-2734 11 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Taxonomies 100%

• Co-embedding network nodes and hierarchical labels with taxonomy based generative adversarial networks

  Yang, C., Zhang, J. & Han, J., Nov 2020, Proceedings - 20th IEEE International Conference on Data Mining, ICDM 2020. Plant, C., Wang, H., Cuzzocrea, A., Zaniolo, C. & Wu, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 721-730 10 p. 9338301. (Proceedings - IEEE International Conference on Data Mining, ICDM; vol. 2020-November).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Taxonomies 100%
  • Labels 80%
  • Topology 9%
  • Experiments 4%

• Collective Multi-type Entity Alignment between Knowledge Graphs

  Zhu, Q., Wei, H., Sisman, B., Zheng, D., Faloutsos, C., Dong, X. L. & Han, J., Apr 20 2020, The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020. Association for Computing Machinery, Inc, p. 2241-2252 12 p. (The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Deep learning 100%
  • Agglomeration 97%
  • Sampling 78%
  • Neural networks 67%
  • Experiments 39%

• CoRel: Seed-Guided Topical Taxonomy Construction by Concept Learning and Relation Transferring

  Huang, J., Xie, Y., Meng, Y., Zhang, Y. & Han, J., Aug 23 2020, KDD 2020 - Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 1928-1936 9 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Taxonomies 100%
  • Experiments 3%

• Discriminative Topic Mining via Category-Name Guided Text Embedding

  Meng, Y., Huang, J., Wang, G., Wang, Z., Zhang, C., Zhang, Y. & Han, J., Apr 20 2020, The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020. Association for Computing Machinery, Inc, p. 2121-2132 12 p. (The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Experiments 100%

• Embedding-Driven Multi-Dimensional Topic Mining and Text Analysis

  Meng, Y., Huang, J. & Han, J., Aug 23 2020, KDD 2020 - Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 3573-3574 2 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Text mining 93%
  • Taxonomies 56%
  • Data mining 22%
  • Economics 17%

• Empower entity set expansion via language model probing

  Zhang, Y., Shen, J., Shang, J. & Han, J., 2020, ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 8151-8160 10 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • semantics 42%
  • Semantic Classes 28%
  • Names 24%
  • Iteration 22%
  • Natural language processing systems 21%

• EVIDENCEMINER: Textual Evidence Discovery for Life Sciences

  Wang, X., Guan, Y., Liu, W., Chauhan, A., Jiang, E., Li, Q., Liem, D., Sigdel, D., Caufield, J. H., Ping, P. & Han, J., 2020, ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Proceedings of the System Demonstrations. Association for Computational Linguistics (ACL), p. 56-62 7 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Life Sciences 100%
  • life sciences 88%
  • Annotation 56%
  • Hypothesis Generation 43%
  • Search engines 41%

• Facet-aware evaluation for extractive summarization

  Mao, Y., Liu, L., Zhu, Q., Ren, X. & Han, J., 2020, ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 4941-4957 17 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Summary 37%
  • Evaluation 36%
  • evaluation 31%
  • Daily Mail 27%
  • CNN 24%

• Fine-Grained Named Entity Recognition with Distant Supervision in COVID-19 Literature

  Wang, X., Song, X., Li, B., Zhou, K., Li, Q. & Han, J., Dec 16 2020, Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020. Park, T., Cho, Y-R., Hu, X. T., Yoo, I., Woo, H. G., Wang, J., Facelli, J., Nam, S. & Kang, M. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 491-494 4 p. 9313126. (Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Coronavirus 68%
  • Supervision 56%
  • Glossaries 52%
  • Datasets 43%
  • Animal Disease Models 35%

• Generating Representative Headlines for News Stories

  Gu, X., Mao, Y., Han, J., Liu, J., Wu, Y., Yu, C., Finnie, D., Yu, H., Zhai, J. & Zukoski, N., Apr 20 2020, The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020. Association for Computing Machinery, Inc, p. 1773-1784 12 p. (The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Labeled data 100%
  • Labels 72%
  • Redundancy 72%

• Graph Clustering with Embedding Propagation

  Yang, C., Liu, L., Liu, M., Wang, Z., Zhang, C. & Han, J., Dec 10 2020, Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. Wu, X., Jermaine, C., Xiong, L., Hu, X. T., Kotevska, O., Lu, S., Xu, W., Aluru, S., Zhai, C., Al-Masri, E., Chen, Z. & Saltz, J. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 858-867 10 p. 9378031. (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Graph 87%
  • Experiments 32%
  • Node 17%
  • Experiment 11%
  • Intuition 9%

• Guiding Corpus-based Set Expansion by Auxiliary Sets Generation and Co-Expansion

  Huang, J., Xie, Y., Meng, Y., Shen, J., Zhang, Y. & Han, J., Apr 20 2020, The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020. Association for Computing Machinery, Inc, p. 2188-2198 11 p. (The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Taxonomies 33%
  • Data mining 26%
  • Set theory 20%

• Hierarchical Topic Mining via Joint Spherical Tree and Text Embedding

  Meng, Y., Zhang, Y., Huang, J., Zheng, Y., Zhang, C. & Han, J., Aug 23 2020, KDD 2020 - Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 1908-1917 10 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Experiments 100%

• InF-VAE: A variational autoencoder framework to integrate homophily and influence in diffusion prediction

  Sankar, A., Zhang, X., Krishnan, A. & Han, J., Jan 20 2020, WSDM 2020 - Proceedings of the 13th International Conference on Web Search and Data Mining. Association for Computing Machinery, Inc, p. 510-518 9 p. (WSDM 2020 - Proceedings of the 13th International Conference on Web Search and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Network architecture 45%
  • Chemical activation 43%
  • Fusion reactions 38%
  • Neural networks 29%

• Joint Aspect-Sentiment Analysis with Minimal User Guidance

  Zhuang, H., Guo, F., Zhang, C., Liu, L. & Han, J., Jul 25 2020, SIGIR 2020 - Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, Inc, p. 1241-1250 10 p. (SIGIR 2020 - Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Sentiment analysis 100%
  • Glossaries 86%
  • Labeled data 26%
  • Joining 21%
  • Experiments 7%

• Minimally Supervised Categorization of Text with Metadata

  Zhang, Y., Meng, Y., Huang, J., Xu, F. F., Wang, X. & Han, J., Jul 25 2020, SIGIR 2020 - Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, Inc, p. 1231-1240 10 p. (SIGIR 2020 - Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Metadata 100%
  • Labels 68%

• Mining text outliers in document directories

  Fouche, E., Meng, Y., Guo, F., Zhuang, H., Bohm, K. & Han, J., Nov 2020, Proceedings - 20th IEEE International Conference on Data Mining, ICDM 2020. Plant, C., Wang, H., Cuzzocrea, A., Zaniolo, C. & Wu, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 152-161 10 p. 9338390. (Proceedings - IEEE International Conference on Data Mining, ICDM; vol. 2020-November).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Text mining 100%
  • Labels 73%
  • Experiments 15%

• Multi-document summarization with maximal marginal relevance-guided reinforcement learning

  Mao, Y., Qu, Y., Xie, Y., Ren, X. & Han, J., 2020, EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 1737-1751 15 p. (EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Reinforcement Learning 72%
  • Reinforcement learning 48%
  • Relevance 46%
  • Redundancy 40%
  • Learning 21%

• MultiSage: Empowering GCN with Contextualized Multi-Embeddings on Web-Scale Multipartite Networks

  Yang, C., Pal, A., Zhai, A., Pancha, N., Han, J., Rosenberg, C. & Leskovec, J., Aug 23 2020, KDD 2020 - Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 2434-2443 10 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Engines 100%
  • Graph structures 96%
  • Convolution 77%
  • Graphics processing unit 72%
  • Agglomeration 67%

• Near-imperceptible neural linguistic steganography via self-adjusting arithmetic coding

  Shen, J., Ji, H. & Han, J., 2020, EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 303-313 11 p. (EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Arithmetic Coding 100%
  • Steganography 96%
  • Linguistics 62%
  • Cover 31%
  • Substitution reactions 27%

• NetTaxo: Automated Topic Taxonomy Construction from Text-Rich Network

  Shang, J., Zhang, X., Liu, L., Li, S. & Han, J., Apr 20 2020, The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020. Association for Computing Machinery, Inc, p. 1908-1919 12 p. (The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Taxonomies 100%
  • Metadata 18%
  • Data mining 15%
  • Experiments 6%

• Neural Concept Map Generation for Effective Document Classification with Interpretable Structured Summarization

  Yang, C., Zhang, J., Wang, H., Li, B. & Han, J., Jul 25 2020, SIGIR 2020 - Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, Inc, p. 1629-1632 4 p. (SIGIR 2020 - Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Neural networks 100%
  • Experiments 19%

• Octet: Online Catalog Taxonomy Enrichment with Self-Supervision

  Mao, Y., Zhao, T., Kan, A., Zhang, C., Dong, X. L., Faloutsos, C. & Han, J., Aug 23 2020, KDD 2020 - Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 2247-2257 11 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Taxonomies 100%
  • Labeling 7%
  • Personnel 5%
  • Neural networks 4%
  • Experiments 2%

• Pattern-enhanced Named Entity Recognition with Distant Supervision

  Wang, X., Guan, Y., Zhang, Y., Li, Q. & Han, J., Dec 10 2020, Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. Wu, X., Jermaine, C., Xiong, L., Hu, X. T., Kotevska, O., Lu, S., Xu, W., Aluru, S., Zhai, C., Al-Masri, E., Chen, Z. & Saltz, J. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 818-827 10 p. 9378052. (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Supervision 56%
  • Glossaries 31%
  • Annotation 25%
  • Labeling 21%
  • Deep Learning 12%

• Relation learning on social networks with multi-modal graph edge variational autoencoders

  Yang, C., Zhang, J., Wang, H., Li, S., Kim, M., Walker, M., Xiao, Y. & Han, J., Jan 20 2020, WSDM 2020 - Proceedings of the 13th International Conference on Web Search and Data Mining. Association for Computing Machinery, Inc, p. 699-707 9 p. (WSDM 2020 - Proceedings of the 13th International Conference on Web Search and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Labels 31%
  • Experiments 13%

• Reliability-aware dynamic feature composition for name tagging

  Lin, Y., Liu, L., Ji, H., Yu, D. & Han, J., 2020, ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 165-174 10 p. (ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Tagging 100%
  • Chemical analysis 47%
  • Names 43%
  • genre 27%
  • Word Frequency 23%

• SynSetExpan: An iterative framework for joint entity set expansion and synonym discovery

  Shen, J., Qiu, W., Shang, J., Vanni, M., Ren, X. & Han, J., 2020, EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 8292-8307 16 p. (EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Framework 100%
  • Semantics 49%
  • Natural language processing systems 42%
  • Crowdsourcing 41%
  • Training 30%

• TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network

  Shen, J., Shen, Z., Xiong, C., Wang, C., Wang, K. & Han, J., Apr 20 2020, The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020. Association for Computing Machinery, Inc, p. 486-497 12 p. (The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Taxonomies 100%
  • Neural networks 57%
  • Anchors 28%
  • Search engines 9%
  • Labels 8%

• Text classification using label names only: A language model self-training approach

  Meng, Y., Zhang, Y., Huang, J., Xiong, C., Ji, H., Zhang, C. & Han, J., 2020, EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 9006-9017 12 p. (EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Training 61%
  • Labels 49%
  • Learning 21%
  • Document Classification 21%
  • Model 19%

• Textual Evidence Mining via Spherical Heterogeneous Information Network Embedding

  Wang, X., Zhang, Y., Chauhan, A., Li, Q. & Han, J., Dec 10 2020, Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. Wu, X., Jermaine, C., Xiong, L., Hu, X. T., Kotevska, O., Lu, S., Xu, W., Aluru, S., Zhai, C., Al-Masri, E., Chen, Z. & Saltz, J. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 828-837 10 p. 9377958. (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Information Networks 100%
  • Query 24%
  • Experiments 14%
  • Knowledge Resources 8%
  • Supervision 7%

• Understanding the difficulty of training transformers

  Liu, L., Liu, X., Gao, J., Chen, W. & Han, J., 2020, EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 5747-5763 17 p. (EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Training 80%
  • Initialization 31%
  • Model 24%
  • Scheduler 18%
  • Learning Rate 17%

• Unsupervised attributed multiplex network embedding

  Park, C., Kim, D., Han, J. & Yu, H., 2020, AAAI 2020 - 34th AAAI Conference on Artificial Intelligence. American Association for Artificial Intelligence (AAAI) Press, p. 5371-5378 8 p. (AAAI 2020 - 34th AAAI Conference on Artificial Intelligence).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Discriminators 100%
  • Labels 68%
  • Experiments 28%

• Unsupervised Differentiable Multi-aspect Network Embedding

  Park, C., Yang, C., Zhu, Q., Kim, D., Yu, H. & Han, J., Aug 23 2020, KDD 2020 - Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 1435-1445 11 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Experiments 17%

• User-Guided Clustering in Heterogeneous Information Networks via Motif-Based Comprehensive Transcription

  Shi, Y., He, X., Zhang, N., Yang, C. & Han, J., 2020, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Proceedings. Brefeld, U., Fromont, E., Hotho, A., Knobbe, A., Maathuis, M. & Robardet, C. (eds.). Springer, p. 361-377 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11906 LNAI).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Transcription 100%
  • Tensors 73%
  • Clustering 70%
  • Higher Order 32%
  • Complex networks 25%

• Weakly-supervised aspect-based sentiment analysis via joint aspect-sentiment topic embedding

  Huang, J., Meng, Y., Guo, F., Ji, H. & Han, J., 2020, EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 6989-6999 11 p. (EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Sentiment analysis 57%
  • Review 37%
  • Training 36%
  • Performance Analysis 21%
  • Polarity 21%

• When do GNNs work: Understanding and improving neighborhood aggregation

  Xie, Y., Li, S., Yang, C., Wong, R. C. W. & Han, J., 2020, Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020. Bessiere, C. (ed.). International Joint Conferences on Artificial Intelligence, p. 1303-1309 7 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 2021-January).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Agglomeration 100%
  • Neural networks 69%
  • Experiments 10%
• 2019

  Arabic named entity recognition: Whatworks and what's next

  Liu, L., Shang, J. & Han, J., 2019, ACL 2019 - 4th Arabic Natural Language Processing Workshop, WANLP 2019 - Proceedings of the Workshop. Association for Computational Linguistics (ACL), p. 60-67 8 p. (ACL 2019 - 4th Arabic Natural Language Processing Workshop, WANLP 2019 - Proceedings of the Workshop).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Test Scores 66%
  • engineering 55%
  • Module 48%
  • Labeling 48%
  • learning 46%

• Aspect-based sentiment analysis with minimal guidance

  Zhuang, H., Hanratty, T. & Han, J., 2019, SIAM International Conference on Data Mining, SDM 2019. Society for Industrial and Applied Mathematics Publications, p. 253-261 9 p. (SIAM International Conference on Data Mining, SDM 2019).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Sentiment analysis 100%
  • Labeled data 35%
  • Experiments 10%

• Biomedical event extraction based on knowledge-driven tree-LSTM

  Li, D., Huang, L., Ji, H. & Han, J., 2019, Long and Short Papers. Association for Computational Linguistics (ACL), p. 1421-1430 10 p. (NAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference; vol. 1).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Long short-term memory 100%
  • Short-term Memory 73%
  • knowledge 55%
  • event 48%
  • Background Knowledge 37%

• Constrained sequence-to-sequence semitic root extraction for enriching word embeddings

  El-Kishky, A., Fu, X., Addawood, A., Sobh, N., Voss, C. & Han, J., 2019, ACL 2019 - 4th Arabic Natural Language Processing Workshop, WANLP 2019 - Proceedings of the Workshop. Association for Computational Linguistics (ACL), p. 88-96 9 p. (ACL 2019 - 4th Arabic Natural Language Processing Workshop, WANLP 2019 - Proceedings of the Workshop).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Natural Language Processing (NLP) 100%
  • Language Families 86%
  • Decomposition 84%
  • Word Formation 82%
  • Regular 58%

• Constructing and mining heterogeneous information networks from massive text

  Shang, J., Shen, J., Liu, L. & Han, J., Jul 25 2019, KDD 2019 - Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 3191-3192 2 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Data mining 100%

• CrossWeigh: Training named entity tagger from imperfect annotations

  Wang, Z., Shang, J., Liu, L., Lu, L., Liu, J. & Han, J., 2019, EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference. Association for Computational Linguistics, p. 5154-5163 10 p. (EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Annotation 69%
  • Training 52%
  • Labels 30%
  • Model 14%
  • Fold 13%

• Cube2net: Efficient query-specific network construction with data cube organization

  Yang, C. & Han, J., Nov 2019, Proceedings - 19th IEEE International Conference on Data Mining Workshops, ICDMW 2019. Papapetrou, P., Cheng, X. & He, Q. (eds.). IEEE Computer Society, p. 1088-1089 2 p. 8955528. (IEEE International Conference on Data Mining Workshops, ICDMW; vol. 2019-November).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Reinforcement learning 100%
  • Large dataset 54%
  • Complex networks 51%
  • Pipelines 38%
  • Experiments 17%

• Discovering hypernymy in text-rich heterogeneous information network by exploiting context granularity

  Shi, Y., Shen, J., Li, Y., Zhang, N., He, X., Lou, Z., Zhu, Q., Walker, M., Kim, M. & Han, J., Nov 3 2019, CIKM 2019 - Proceedings of the 28th ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, p. 599-608 10 p. (International Conference on Information and Knowledge Management, Proceedings).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Information Networks 100%
  • Quality Signal 18%
  • Supervision 14%
  • Taxonomy 13%
  • Node 13%

• Distantly Supervised Biomedical Named Entity Recognition with Dictionary Expansion

  Wang, X., Zhang, Y., Li, Q., Ren, X., Shang, J. & Han, J., Nov 2019, Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019. Yoo, I., Bi, J. & Hu, X. T. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 496-503 8 p. 8983212. (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • dictionary 53%
  • Glossaries 48%
  • Corpus 22%
  • Supervised Machine Learning 13%
  • Datasets 13%

• GeoAttn: Localization of social media messages via attentional memory network

  Li, S., Zhang, C., Lei, D., Li, J. & Han, J., 2019, SIAM International Conference on Data Mining, SDM 2019. Society for Industrial and Applied Mathematics Publications, p. 64-72 9 p. (SIAM International Conference on Data Mining, SDM 2019).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Data storage equipment 100%
  • Metadata 23%
  • Experiments 8%

• Hierarchical text classification with reinforced label assignment

  Mao, Y., Tian, J., Han, J. & Ren, X., 2019, EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference. Association for Computational Linguistics, p. 445-455 11 p. (EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Training 61%
  • Assignment 53%
  • Labels 49%
  • Reinforcement Learning 21%
  • Encoder 19%

• HiGitClass: Keyword-driven hierarchical classification of github repositories

  Zhang, Y., Xu, F. F., Li, S., Meng, Y., Wang, X., Li, Q. & Han, J., Nov 2019, Proceedings - 19th IEEE International Conference on Data Mining, ICDM 2019. Wang, J., Shim, K. & Wu, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 876-885 10 p. 8970799. (Proceedings - IEEE International Conference on Data Mining, ICDM; vol. 2019-November).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Labels 100%

• Integrating local context and global cohesiveness for open information extraction

  Zhu, Q., Ren, X., Shang, J., Zhang, Y., El-Kishky, A. & Han, J., Jan 30 2019, WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining. Association for Computing Machinery, Inc, p. 42-50 9 p. (WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Experiments 23%