Alumni
date
Aug 1, 2022
slug
members-alumni
status
Published
tags
summary
type
Members
Year | Degree | Students ID | Name | Thesis |
2012 | MS | R99725037 | 王婷儀 | How Novel is patent: Assessing Patent Novelty through Text and Citation Analysis |
ㅤ | MS | R99725038 | 佘亭維 | A text Mining Approach to Identifying Cross-Sectoral Applications for Patents |
ㅤ | MS | R99725039 | 陳弘堯 | Mining Supplier Relationships from Online News Documents |
ㅤ | MS | R99725043 | 郭岱茵 | Impact Mining for Supporting Literature-based Discovery |
ㅤ | MS | R99725045 | 李柏勳 | Identifying Competitor Relationships Using Network Features and Text Information |
2013 | MS | R00725017 | 潘冠宇 | A New Approach for Technological Opportunity Identification: Patent Novelty Assessment by Semantic and Citation Analysis |
ㅤ | MS | R00725019 | 郭泰頤 | Automatically constructing technology effect matrix for patent strategy analysis: Using text mining techniques |
ㅤ | MS | R00725020 | 陳奎安 | Mining Biomedical Literature and Ontologies for Drug Repositioning Discovery |
ㅤ | MS | R00725027 | 許鴻英 | A function-based Approach to Identifying Cross-setoral Applications for Patents |
ㅤ | MS | R00725028 | 陳尹安 | Prediction of Continuance Knowledge Sharing in Online Opinion-sharing Communities |
2014 | MS | R01725011 | 黃 葳 | Examining the Effect of Product Comparison in Online Reviews on Product Sales |
ㅤ | MS | R01725013 | 林蓓妤 | ㅤ |
ㅤ | MS | R01725025 | 謝采璇 | Detecting Drug Safety Signals from National Taiwan Health Insurance Research Database: A Learning to Rank Approach |
ㅤ | MS | R01725033 | 余光昇 | Patent Invalidity Search: A Learning to Rank Approach |
2015 | MS | R02725004 | 楊筑雅 | A thechnology-Effect-Matrix-Based Method for Technological Opportunity Discovery |
ㅤ | MS | R02725005 | 林子勻 | Minig Adverse Events Caused by Drug-drug Interactions from National Health Insurance Research Database |
ㅤ | MS | R02725010 | 陳昱安 | Predicting Firms’ Competitive Actions from Business News Documents |
ㅤ | MS | R02725025 | 張宇婷 | Compitational Drug respostitioning: A Learning to Rank Approach with Mutiple Data Sources |
ㅤ | MS | R02725026 | 孫敏倫 | A Data Mining Approach for Predicting Firm Innovation Performance after Coopetition |
2016 | MS | R03725006 | 陳冠穎 | ㅤ |
ㅤ | MS | R03725008 | 劉睿蕓 | ㅤ |
ㅤ | MS | R03725017 | 張 翔 | Capturing Brand Associations from Online Product Reviews: Method Development and Evaluation |
ㅤ | MS | R03725020 | 楊子嫻 | ㅤ |
2017 | MS | R04725005 | 蔡培暄 | ㅤ |
ㅤ | MS | R04725022 | 李坤樸 | Literature-based Discovery for Drug Repurposing: A Path-importance-based Approach |
ㅤ | MS | R04725024 | 陳彥勳 | Development of an SAO-based Approach to Supporting Patent Prior Art Retrieval |
ㅤ | MS | R04725030 | 朱雯伶 | Using User-Generated Content for Brand Association Extraction and Co-Branding Assessment |
ㅤ | MS | R04725035 | 黃奕閔 | A Function-and Bibliographic-coupling-based Approach for Identfiying Cross-setoracl Applications of Patents |
ㅤ | MS | R04725054 | 書世祐 | A Semi-supervised Approach for Profiling Online Reviewers |
2018 | MS | R05725002 | 洪蕾曜 | Using User-Generated Content for Predicting Customer-Perceived Brand Personality |
ㅤ | MS | R05725013 | 羅云伶 | Using Social Media Analytics for Brand Extension Evaluation. |
ㅤ | MS | R05725014 | 許予帆 | Technology Startup Value Prediction: A Machine Learning Approach |
ㅤ | MS | R05725015 | 翁瑞昕 | ㅤ |
2019 | MS | R06725004 | 陳昀靖 | Literature-based Discovery for Drug Repositioning: A Predicate-Pattern-Importance Ranking Approach |
ㅤ | MS | R06725007 | 賴冠廷 | RRCGAN: Robust Reading Comprehension with Adversarial Learning |
ㅤ | MS | R06725008 | 郭毓棠 | Using Piecewise Convolutional Neural Networks for Biomedical Relation Extraction |
ㅤ | MS | R06725012 | 陳泓志 | A Deep Learning Based Approach for Personality Detection from User Generated Content |
ㅤ | MS | R06725013 | 吳乙瑩 | A Neural Multi-task Learning for Aspect Extraction and Sentiment Classification |
ㅤ | MS | R06725014 | 周晅瑢 | Depression Detection from Users’ Posts on Social Media: A Deep Learning Approach |
ㅤ | MS | R06725051 | 丘文恒 | A Trajectory Based Collaborative Filtering Approach to Support Firm Technological Development Forecasting |
2020 | MS | R07725006 | 汪芷伊 | Neural Multi-task Learning Combined with Sentiment Lexicon for Aspect-based Sentiment Analysis |
ㅤ | MS | R07725026 | 簡辰宇 | Low-Resource Chinese Machine Reading Comprehension Using A Transfer Learning Approach |
ㅤ | MS | R07725031 | 張晉華 | Biomedical Relation Extraction Supporting by Knowledge Graph Embedding Model |
ㅤ | MS | R07725032 | 朱瑤章 | Representation Learning for Biomedical Relation Extraction with Dependency Parsing |
ㅤ | MS | R07725048 | 高勗倫 | A Two-phase Model for Predicting Brand Personality with Social Media Data |
2021 | MS | R08725020 | 高宗毅 | ㅤ |
ㅤ | MS | R08725021 | 王鼎元 | ㅤ |
ㅤ | MS | R08725023 | 何昱辰 | ㅤ |
ㅤ | MS | R08725025 | 陳禹媛 | ㅤ |
ㅤ | MS | R08725026 | 林楷翊 | Predicting ESG Performance of Firms Using Business News: A Text Mining Approach |
2022 | MS | R09725019 | 顏价廷 | Joint Biomedical Entity-Relation Extraction for 1-to-1 and 1-to-Many Relations Method Using a Deep-Learning-Based Sequence Labeling Method |
ㅤ | MS | R09725027 | 姜 皜 | A multi-task deep neural network method for sentiment lexicon extraction |
ㅤ | MS | R09725035 | 陳漢威 | Multi-gate Mixture-of-Experts Approach for Emotion-Cause Pair Extraction |
ㅤ | MS | R09725037 | 陳詩筠 | Diffusion Model Learning for Predicting Popularity of Marketing Videos on YouTube |
ㅤ | MS | R09725040 | 李惟慈 | Learning logics rules and reasoning on noisy knowledge graphs |
