MEMBERS

中心成員
  • 姓名 :

    高宏宇

  • 職稱 :

    教授 Professor

  • 所屬實驗室 :

    金融科技核心技術開發

  • 系所名稱 :

    資訊工程學系

  • 個人資料網頁 :

    點此進入

  • 學術成大 :

    點此進入

  • 洽談合作信箱 :

    hykao@mail.ncku.edu.tw

關於

研究領域

  • Information Retrieval / Extraction
  • Machine Learning / AI
  • Big / Web Data Mining
  • Bioinformatics

 

近期計畫

  • 科技部-公共衛生及健康醫療應用之物聯網數據智慧加值技術
  • 科技部-以強化自然語言理解為基礎之文本摘要生成
  • 科技部-產學合作計畫-深度學習於自動文件摘要之技術研究
  • 教育部-醫病訊息決策分析與對話語料建構系統競賽
  • 產學合作-EQB答案推薦演算法研究
  • 產學合作-Based Document Summarization and Sentiment-aware QA System
  • 產學合作-自動化科學文件之化學信息擷取工具ChemDataExtractor解析委託
近期開課

開課名稱:資料分析與學習基石

開課系所:資訊系

課綱連結

 

近五年著作

[期刊]

  1. H.-D. Huang, H.-Y. Kao, "C-3PO: Click-sequence-aware DeeP Neural Network (DNN)-based Pop-uPs Recommendation,“ Soft Computing, Volume 23, Issue 22, pp 11793–11799, November 2019.

 

  1. G.-B. Chen and H.-Y. Kao, "Re-organized Topic Modeling for Micro-blogging Data, “ Intelligent Data Analysis, 21, S1, p. S55-S70, 2017.

 

  1. S.-L. Wang, Y.-C. Tsai, T.-P. Hong, H.-Y. Kao, "k^{-}-anonymization of multiple shortest paths, " Soft Computing, 1-12, doi:10.1007/s00500-016-2032-2, 2016.

 

  1. H.-C. Lee, Y.-Y. Hsu, and H.-Y. Kao, "AuDis: an automatic CRF-enhanced disease normalization in biomedical text, " Database Vol. 2016: article ID baw091; doi:10.1093/database/baw091, 2016.

 

  1. H.-J. Dai, C.-H. Wei, H.-Y. Kao, R.-L. Liu, R. T.-H. Tsai, Z. Lu, "Text Mining for Translational Bioinformatics, "BioMed Research International, 2015.

 

  1. G.-B. Chen and H.-Y. Kao, "Word Co-occurrence Augmented Topic Model in Short Text, " International Journal of Computational Linguistics & Chinese Language Processing, Vol. 20, No. 2, December 2015.

 

  1. C.-H. Wei, H.-Y. Kao, and Zhiyong Lu, “GNormPlus: An Integrative Approach for Tagging Genes, Gene Families, and Protein Domains,” BioMed Research International, vol. 2015, Article ID 918710, 7 pages, 2015.

 

  1. Y.-Y. Hsu and H.-Y. Kao, "Curatable Named-entity Recognition using Semantic Relations, " IEEE/ACM Transactions on Computational Biology and Bioinformatics (IEEE TCBB), Vol. 12, Issue 4, July-Aug. 2015.

 

[會議論文]

  1. K.-C. Yang, and H.-Y. Kao, "Generalize Sentence Representation with Self-Inference", Proc. of the thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), NY, USA, Feb. 7-12, 2020.

 

  1. T. Niven, and H.-Y. Kao, "Probing Neural Network Comprehension of Natural Language Arguments," Proc. of the 57th Annual Meeting of the Association for Computational Linguistics (ACL-2019), Florence, Italy, July 28 - August 2, 2019.

 

  1. T. Niven, and H.-Y. Kao, "Detecting Argumentative Discourse Units with Linguistic Alignment," 6th Workshop on Argument Mining, in conjunction with 57st Annual Meeting of the Association for Computational Linguistics (ACL-2019), Florence, Italy, July 29-August. 2, 2019.

 

  1. K.-C. Yang, T. Niven, T.-H. Chou and H.-Y. Kao, "Fill the GAP: Exploiting BERT for pronoun resolution", First Workshop on Gender Bias for Natural Language Processing, in conjunction with 57st Annual Meeting of the Association for Computational Linguistics (ACL-2019), Florence, Italy, July 29-August. 2, 2019.

 

  1. G.-L. Li, Y.-Y. Lin, and H.-Y. Kao, "Latent Aspect Mining for Short and Unrated Reviews, "Proc. of the International Conference on Innovative Computing and Management Science (ICMS-2019), Osaka, Japan, July 19-22, 2019. (Best Paper Award)

 

  1. K.-C. Yang, T. Niven, H.-Y. Kao, "Fake News Detection as Natural Language Inference, "Proc. of the 12th ACM International Conference on Web Search and Data Mining (WSDM-2019)(in Fake News Classification Challenge, WSDM Cup 2019), Melbourne, Australia, February 11–15, 2019.

 

  1. H.-D. Huang, H.-Y. Kao, "R2-D2: Color-inspired Convolutional Neural Network (CNN)-based Android Malware Detections, "Proc. of the 2018 IEEE BigData 2018, Seattle, WA, USA. Dec 10-13. 2018.

 

  1. H.-C. Lee and H.-Y. Kao, "CDRnN: a high performance Chemical-Disease Recognizer in biomedical literature, "Proc. of 2017 IEEE International Conference on Bioinformatics & Biomedicine (BIBM-2017), Nov. 11-16, 2017.

 

  1. Y.-C. Chen, Z.-Y. Liu, H.-Y. Kao, "IKM at SemEval-2017 Task 8: Convolutional Neural Networks for stance detection and rumor verification, "Proc. of International Workshop on Semantic Evaluation 2017 (SemEval 2017), in conjunction with 55st Annual Meeting of the Association for Computational Linguistics (ACL 2017), July 30-August. 4, 2017.

 

  1. G. Tumenbayar and H.-Y. Kao, "Topic Suggestion by Bayesian Network Enhanced Tag Inference in Community Question Answering, " Proc. of the 2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI-2016), November 25-27, 2016.

 

  1. H.-C. Lee, Y.-Y. Hsu, H.-Y. Kao, "An enhanced CRF-based system for disease name entity recognition and normalization on BioCreative V DNER Task, " Proc. of the Fifth BioCreative Challenge Evaluation Workshop, 2015.

 

  1. S.-T. Huang, P.-S. Li, H.-Y. Kao, "Identification of item features in microblogging data, "Proc. of the 2015 Conference on Technologies and Applications of Artificial Intelligence (TAAI-2015), November 20-22, 2015.

 

  1. J.-D. Chen and H.-Y. Kao, "LDA Based Semi-supervised Learning from Streaming Short Text, " Proc. of the 2nd IEEE International Conference on Data Science and Advanced Analytics (DSAA-2015), Oct. 19-21, 2015.

 

  1. G.-B. Chen and H.-Y. Kao, "Re-organized Topic Modeling for Micro-blogging Data, " Proc. of the 5th ASE International Conference on Big Data (BigData 2015), Oct 7-9, 2015.

 

  1. Y.-C. Tsai, S.-L. Wang, T.-P. Hong, H.-Y. Kao, "Extending [K 1, K 2] Anonymization of Shortest Paths for Social Networks, " Proc. of the 2015 International Conference on Multidisciplinary Social Networks Research, 2015.

 

  1. Y.-C. Chen and H.-Y. Kao, "One-Class Recommendation System with PU learning, " Proc. of 6th International Workshop on Social Recommender Systems (SRS 2015), in conjunction with 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), Aug. 10, 2015.

 

產學成果

1.中鼎工程股份有限公司

EQB答案推薦演算法研究,統包工程技術提升與作業流程改善;藉由學術機構的研究能量,開發文件內容之影像辨識技術,應用於工程報價階段的估價自動化,以期縮減估價人力,提 升企業競爭力。協助中鼎自業主邀標書(Invitation To Bid 以下簡稱 ITB)中擷取適當資訊自動產生設計基準(Engineering Quality Baseline 以下簡稱 EQB)之技術進行概念性驗證研究

 

2.凱鈿行動科技股份有限公司

深度學習於自動文件摘要之技術研究,希望利用機器學習技術建構自然語言理解模組,同時截取與生成重要段落並產生符合原意、語法與邏輯的摘要, 進而配合業界的行動裝置閱讀與標注系統,利用文本特徵工程與語句概念嵌入(Embedding)產生語句的表示並計算之間的支持關係,接著進行重要段落截取並透過注意力模型機制(Attention)進行摘要生成部分來進行自動摘要的產生

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