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Fingerprint Fingerprint is based on mining the text of the expert's scholarly documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

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Research Output

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 proceedingConference contribution

Open Access
  • CrossWeigh: Training named entity tagger from imperfect annotations

    Wang, Z., Shang, J., Liu, L., Lu, L., Liu, J. & Han, J., Jan 1 2020, 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 proceedingConference contribution

  • Deep multiplex graph infomax: Attentive multiplex network embedding using global information

    Park, C., Han, J. & Yu, H., Jun 7 2020, In : Knowledge-Based Systems. 197, 105861.

    Research output: Contribution to journalArticle

  • 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 proceedingConference contribution

    Open Access
  • Efficient contextualized representation: Language model pruning for sequence labeling

    Liu, L., Ren, X., Shang, J., Gu, X., Peng, J. & Han, J., Jan 1 2020, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. Riloff, E., Chiang, D., Hockenmaier, J. & Tsujii, J. (eds.). Association for Computational Linguistics, p. 1215-1225 11 p. (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution