Page 62 - 2017 Brochure
P. 62
研究員
古倫維 Lun-Wei Ku
Assistant Research Fellow
Ph.D., Computer Science, National Taiwan University
Tel: +886-2-2788-3799 ext. 1808 Fax: +886-2-2782-4814
Email: lwku@iis.sinica.edu.tw
http://www.lunweiku.com
• AFNLP Executive Committee Members-at-Large (MAL), (2016-present)
• Information Officer, ACL-SIGHAN (2016-present)
• Secretary-General, Association for Computational Linguistics and Chinese Language Processing (2015-present)
• Assistant Research Fellow, Institute of Information Science, Academia Sinica (2012-present)
• Assistant Professor, Computer Science and Information Engineering, National Yunlin University of Science and Technology (2011-2012)
• Ph.D., Department of Computer Science and Information Engineering, National Taiwan University (2003-2009)
• M.S., Department of Computer Science and Information Engineering, National Taiwan University (1998-2000)
Research Description apps on hand-held devices. We have implicitly but successfully
constructed the largest private conversation dataset and now are
My research interests lie in the field of sentiment analysis and working to overcome challenges in applying related technologies.
opinion mining, which is a subarea of natural language processing. Social Media Sentiment and Recommendation: To classify the user
I am especially interested in its interplay with human-computer and post stance for generating recommendations in social media
interaction (HCI) and computer assisted language learning (CALL), channels, we develop techniques which jointly label user and post
as wells as its application in social media analytics. I have devoted stance. We propose a state-of-the-art deep learning model for
myself to sentiment analysis for over a decade and developed the social stance classification and a novel but powerful deep neural
most popular Chinese sentiment analysis toolkit CSentipackage, network which learns multi-relational graph embeddings to capture
which is free for research purposes. social dynamics.
Knowledge Utilization and Representation: We can decently
I love to work actively in my research community, and some of manage knowledge by predicting relation links and inferring via
my representative professional international activities include: links of entities. Methods that consider both local contextual
Area Chair in ACL 2017, CCL 2016, NLPCC 2016, ACL 2015, and information and global knowledge have been proposed to improve
EMNLP 2015. Additionally, I am currently organizing the promising performance. We plan to develop deep text and dialog generation
SocialNLP workshop twice a year at different top conferences. models to represent knowledge using natural languages, where
chatbot is one of the example applications.
Recently, I have been interested in deep language understanding to
bring the benefits of affective computing to people’s lives. Related Opinion Dependency Relations for Opinion Analysis”, In Proceedings
research includes: of the 5th International Joint Conference on Natural Language
Processing (IJCNLP), pages 345-353, November 2011.
Emotion Detection and HCI: We develop technologies for emotion 7. Seki, Yohei, Ku, Lun-Wei, Sun, Le, Chen, Hsin-Hsi and Kando,
detection in short messages and deliver them to end users via Noriko, “Overview of Multilingual Opinion Analysis Task at
NTCIR-8: A Step Toward Cross Lingual Opinion Analysis,” In
Publications Proceedings of the 8th NTCIR Workshop Meeting on Evaluation of
Information Access Technologies: Information Retrieval, Question
1. Chieh-Yang Huang, Mei-Hua Chen and Lun-Wei Ku, “Towards Answering, and Cross-Lingual Information Access (NTCIR), pages
a Better Learning of Near-Synonyms: Automatically Suggesting 209-220, June 2010.
Example Sentences via Filling in the Blank,” In Proceedings of the 8. Ku, Lun-Wei, Ho, Xiu-Wei and Chen, Hsin-Hsi, “Opinion Mining and
26th International World Wide Web Conference (WWW 2017), Digital Relationship Discovery Using CopeOpi Opinion Analysis System”,
Learning Track. Journal of American Society for Information Science and Technology,
volume 60, number 7, pages 1486-1503, July 2009.
2. Wei-Fan Chen and Lun-Wei Ku, “UTCNN: a Deep Learning Model of 9. Ku, Lun-Wei, Huang, Ting-Hao and Chen, Hsin-Hsi, “Using
Stance Classification on Social Media Text,” In Proceedings of the 26th Morphological and Syntactic Structures for Chinese Opinion Analysis”,
International Conference on Computational Linguistics (COLING 2016). In Proceedings of Conference on Empirical Methods in Natural
Language Processing (EMNLP), pages 1260-1269, August 2009.
3. Wei-Fan Chen, Mei-Hua Chen, Ming-Lung Chen, and Lun-Wei Ku, “A 10. Ku, Lun-Wei and Chen, Hsin-Hsi, “Mining Opinions from the Web:
Computer-Assistance Learning System for Emotional Wording,” IEEE Beyond Relevance Retrieval”, Journal of American Society for
Transactions on Knowledge and Data Engineering (TKDE), volume Information Science and Technology, volume 58, number 12, pages
28, number 5, pages 1093-1104, May 2016. 1838-1850, August 2007, Special Issue on Mining Web Resources for
Enhancing Information Retrieval
4. Lun-Wei Ku, Shafqat Mumtaz Virk and Yann-Huei Lee, “A Dual-
Layer Semantic Role Labeling System,” In Proceedings of the 53th
Annual Meeting of the Association for Computational Linguistics
& The 7th International Joint Conference on Natural Language
Processing of The Asian Federation of Natural Language Processing
(ACL-IJCNLP 2015, System Demonstration), pages 49-54, July 2015.
5. Ku, Lun-Wei, Sun, Cheng-Wei, and Hsueh, Ya-Hsin, “Demonstration
of IlluMe: Creating Ambient According to Instant Message Logs”, In
Proceedings of the System Demonstrations, 50th Annual Meeting of
Association for Computational Linguistics (ACL), pages 97-102, July
2012,
6. Ku, Lun-Wei, Ting-Hao Kenneth Huang, Hsin-Hsi Chen, “Predicting
60 研究人員 Research Faculty
古倫維 Lun-Wei Ku
Assistant Research Fellow
Ph.D., Computer Science, National Taiwan University
Tel: +886-2-2788-3799 ext. 1808 Fax: +886-2-2782-4814
Email: lwku@iis.sinica.edu.tw
http://www.lunweiku.com
• AFNLP Executive Committee Members-at-Large (MAL), (2016-present)
• Information Officer, ACL-SIGHAN (2016-present)
• Secretary-General, Association for Computational Linguistics and Chinese Language Processing (2015-present)
• Assistant Research Fellow, Institute of Information Science, Academia Sinica (2012-present)
• Assistant Professor, Computer Science and Information Engineering, National Yunlin University of Science and Technology (2011-2012)
• Ph.D., Department of Computer Science and Information Engineering, National Taiwan University (2003-2009)
• M.S., Department of Computer Science and Information Engineering, National Taiwan University (1998-2000)
Research Description apps on hand-held devices. We have implicitly but successfully
constructed the largest private conversation dataset and now are
My research interests lie in the field of sentiment analysis and working to overcome challenges in applying related technologies.
opinion mining, which is a subarea of natural language processing. Social Media Sentiment and Recommendation: To classify the user
I am especially interested in its interplay with human-computer and post stance for generating recommendations in social media
interaction (HCI) and computer assisted language learning (CALL), channels, we develop techniques which jointly label user and post
as wells as its application in social media analytics. I have devoted stance. We propose a state-of-the-art deep learning model for
myself to sentiment analysis for over a decade and developed the social stance classification and a novel but powerful deep neural
most popular Chinese sentiment analysis toolkit CSentipackage, network which learns multi-relational graph embeddings to capture
which is free for research purposes. social dynamics.
Knowledge Utilization and Representation: We can decently
I love to work actively in my research community, and some of manage knowledge by predicting relation links and inferring via
my representative professional international activities include: links of entities. Methods that consider both local contextual
Area Chair in ACL 2017, CCL 2016, NLPCC 2016, ACL 2015, and information and global knowledge have been proposed to improve
EMNLP 2015. Additionally, I am currently organizing the promising performance. We plan to develop deep text and dialog generation
SocialNLP workshop twice a year at different top conferences. models to represent knowledge using natural languages, where
chatbot is one of the example applications.
Recently, I have been interested in deep language understanding to
bring the benefits of affective computing to people’s lives. Related Opinion Dependency Relations for Opinion Analysis”, In Proceedings
research includes: of the 5th International Joint Conference on Natural Language
Processing (IJCNLP), pages 345-353, November 2011.
Emotion Detection and HCI: We develop technologies for emotion 7. Seki, Yohei, Ku, Lun-Wei, Sun, Le, Chen, Hsin-Hsi and Kando,
detection in short messages and deliver them to end users via Noriko, “Overview of Multilingual Opinion Analysis Task at
NTCIR-8: A Step Toward Cross Lingual Opinion Analysis,” In
Publications Proceedings of the 8th NTCIR Workshop Meeting on Evaluation of
Information Access Technologies: Information Retrieval, Question
1. Chieh-Yang Huang, Mei-Hua Chen and Lun-Wei Ku, “Towards Answering, and Cross-Lingual Information Access (NTCIR), pages
a Better Learning of Near-Synonyms: Automatically Suggesting 209-220, June 2010.
Example Sentences via Filling in the Blank,” In Proceedings of the 8. Ku, Lun-Wei, Ho, Xiu-Wei and Chen, Hsin-Hsi, “Opinion Mining and
26th International World Wide Web Conference (WWW 2017), Digital Relationship Discovery Using CopeOpi Opinion Analysis System”,
Learning Track. Journal of American Society for Information Science and Technology,
volume 60, number 7, pages 1486-1503, July 2009.
2. Wei-Fan Chen and Lun-Wei Ku, “UTCNN: a Deep Learning Model of 9. Ku, Lun-Wei, Huang, Ting-Hao and Chen, Hsin-Hsi, “Using
Stance Classification on Social Media Text,” In Proceedings of the 26th Morphological and Syntactic Structures for Chinese Opinion Analysis”,
International Conference on Computational Linguistics (COLING 2016). In Proceedings of Conference on Empirical Methods in Natural
Language Processing (EMNLP), pages 1260-1269, August 2009.
3. Wei-Fan Chen, Mei-Hua Chen, Ming-Lung Chen, and Lun-Wei Ku, “A 10. Ku, Lun-Wei and Chen, Hsin-Hsi, “Mining Opinions from the Web:
Computer-Assistance Learning System for Emotional Wording,” IEEE Beyond Relevance Retrieval”, Journal of American Society for
Transactions on Knowledge and Data Engineering (TKDE), volume Information Science and Technology, volume 58, number 12, pages
28, number 5, pages 1093-1104, May 2016. 1838-1850, August 2007, Special Issue on Mining Web Resources for
Enhancing Information Retrieval
4. Lun-Wei Ku, Shafqat Mumtaz Virk and Yann-Huei Lee, “A Dual-
Layer Semantic Role Labeling System,” In Proceedings of the 53th
Annual Meeting of the Association for Computational Linguistics
& The 7th International Joint Conference on Natural Language
Processing of The Asian Federation of Natural Language Processing
(ACL-IJCNLP 2015, System Demonstration), pages 49-54, July 2015.
5. Ku, Lun-Wei, Sun, Cheng-Wei, and Hsueh, Ya-Hsin, “Demonstration
of IlluMe: Creating Ambient According to Instant Message Logs”, In
Proceedings of the System Demonstrations, 50th Annual Meeting of
Association for Computational Linguistics (ACL), pages 97-102, July
2012,
6. Ku, Lun-Wei, Ting-Hao Kenneth Huang, Hsin-Hsi Chen, “Predicting
60 研究人員 Research Faculty
