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Associate Research Fellow/Professor | Huang, Hen-Hsen |
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Software Name: | 1. AutoSurvey: Automatic Survey Generation based on a Research Draft |
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Date: | 2020/07–/ |
Abstract: | AutoSurvey: Automatic Survey Generation based on a Research DraftBased on deep learning and evolutionary optimization, AutoSurvey is an intelligent systemthat performs literature survey and generates a summary specific to a research draft. Thissystem is extremely used for both academic and educational purposes. (Demonstrated atIJCAI 2020) |
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Software Name: | A Complete Shift-Reduce Chinese Discourse Parser with Robust Dynamic Oracle |
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Date: | 2020/07–/ |
Abstract: | A Complete Shift-Reduce Chinese Discourse Parser with Robust Dynamic OracleA state-of-the-art Chinese discourse parser, incorporating a revised dynamic-oracle procedurewith unsupervised data augmentation, is released as a ready-to-use resource for theresearch community. (Released with an ACL 2020 paper) |
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Software Name: | MPD Player with Expert Knowledge-based Music Recommendation |
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Date: | 2019/10–/ |
Abstract: | An audiophile music player based on the MPD protocol suggests the relevant albums andartists to the user based the playback log. A knowledge base built on the top of All MusicGuide is employed to perform the recommendation as a task of knowledge base completion.(Demonstrated at WI 2019) |
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Software Name: | CISA: Chinese Information Structure Analysis for Scientific Writing |
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Date: | 2018/07–/ |
Abstract: | CISA extends our prior system, DISA, which addresses English writing advising, to offeringa system for Chinese scientific writing advising. We propose the first model for Chineseinformation structure identification. Adversarial learning is employed to enhance the crosslingualsentence representation. (Demonstrated at IJCAI 2018) |
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Software Name: | DISA: A Scientific Writing Advisor with Deep Information Structure Analysis |
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Date: | 2017/08–/ |
Abstract: | DISA: A Scientific Writing Advisor with Deep Information Structure AnalysisA higher-level writing assistant system analyzes the information structure of abstracts, andretrieves the knowledge according to the research goals from the related work. By incorporatingthe latest neural-network technologies including linguistically-informed neuralnetworkand autoencoder, DISA extends the scope of computer-aided writing. (Demonstratedat IJCAI 2017) |
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