博碩士論文 106522098 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:31 、訪客IP:3.14.247.239
姓名 楊智傑(Chih-Chieh Yang)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 反毒小幫手:用於提倡反毒意識的聊天機器人
(Anti-Drug Friend: A Chatbot for advocating the awareness of Anti-Drug)
相關論文
★ 具多重樹狀結構之可靠性群播傳輸★ 在嵌入式行動裝置上設計與開發跨平台Widget
★ 在 ARM 架構之嵌入式系統上實作輕量化的手持多媒體播放裝置圖形使用者介面函式庫★ 基於網路行動裝置所設計可擴展的服務品質感知GStreamer模組
★ 針對行動網路裝置開發可擴展且跨平台之GSM/HSDPA引擎★ 於單晶片多媒體裝置進行有效率之多格式解碼管理
★ IMS客戶端設計與即時通訊模組研發:個人資訊交換模組與即時訊息模組實作★ 在可攜式多媒體裝置上實作人性化的嵌入式小螢幕網頁瀏覽器
★ 以IMS為基礎之及時語音影像通話引擎的實作:使用開放原始碼程式庫★ 電子書嵌入式開發: 客制化下載服務實作, 資料儲存管理設計
★ 於數位機上盒實現有效率訊框參照處理與多媒體詮釋資料感知的播放器設計★ 具數位安全性的電子書開發:有效率的更新模組與資料庫實作
★ 適用於異質無線寬頻系統的新世代IMS客戶端軟體研發★ 在可攜式數位機上盒上設計並實作重配置的圖形使用者介面
★ Friendly GUI design and possibility support for E-book Reader based Android client★ Effective GUI Design and Memory Usage Management for Android-based Services
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 ( 永不開放)
摘要(中) 近年來,毒品的傳播和濫用一直是社會關注的焦點。毒品的傳播可能會給我們的社會帶來嚴重的問題,危害公眾的生命,健康和財產安全。儘管在反毒領域已經做了很多的努力,但毒品案件中的犯罪人數仍在增加。因此,有必要找到一種提昇一般民眾反毒意識的方法。
使用人工智慧可以實現更多應用程序,例如聊天機器人。使用聊天機器人有幾個優點:它可以全天候工作、有效降低人工成本、可以快速的部署在社群媒體訊息平台上且易於使用。目前,市場上的聊天機器人不能完全應用於反毒領域,因此我們提出其他的架構改善反毒相關的問答,並能夠回答更詳細的毒品知識。接著,我們提出利用聊天機器人提倡毒品的一般知識和加深對人們的反毒意識的反毒小幫手。現在,我們的反毒小幫手已經在LINE上服務。在這個毒品相關的領域上,我們的聊天機器人可以回答用使用者:有關毒品的知識、如何處理與毒品相關的問題、以及提供有關反毒的最新消息和新聞。
摘要(英) In recent years, the spread and abuse of drugs has always been the focus of social attention. The spread of drugs can cause serious problems in our society and endanger the lives, property and health of the public. Although there have been many efforts in the domain of anti-drug, the number of guilty persons in drug cases is still rising. Therefore, there is a need to find a way to promote anti-drug awareness.
More applications can achieved with an artificial intelligence computer, such as chatbot. There are several advantages to using a chatbot: it can work around the clock, effectively reducing labor costs, can be deployed on social media messaging platforms and easy to use. At present, chatbots on the market cannot be completely applied to the anti-drug domain, so we propose other architectures to improve the anti-drug related QA and to answer more detailed knowledge about drugs. Then, we propose Anti-Drug Friend that utilize chatbot to advocate general knowledge about drugs and deepening anti-drug awareness for people. Currently, our Anti-Drug Friend is already serving on LINE. For an anti-drug domain, our chatbot can answer user: Information about drugs, How to deal with drug problems, Pushing the latest news and information about drugs.
關鍵字(中) ★ 反毒
★ 聊天機器人
★ 自然語言
★ 基於知識庫的系統
關鍵字(英) ★ Anti-Drug
★ Chatbot
★ Natural languages
★ Knowledge based systems
論文目次 摘要 I
Abstract II
致謝 III
Table of Contents IV
List of Figures VI
1. Introduction 1
1.1 Motivation & Proposed Goal 1
1.2 Organization of Thesis 6
2. Related Works 7
3. System Design 10
3.1 Background 10
3.2 System Architecture 12
3.2.1 Response module 18
3.2.2 Modules Analysis 21
4. Implementation 22
4.1 ChatBot Server module 22
4.2 Web Server module 23
4.3 Results and Displays 24
5. Conclusion and Future Works 29
References 30
參考文獻 [1] Lu Chao Fen, “Research on cognitive differences between decriminalization of high school (vocational) student drug abuse - A Case Study of School in Taipei”, Journal of Health Management, 2016
[2] Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding”, arXiv, 2018.
[3] B. T. Xu, Yong Xu, Jiaqing Liang, Chenhao Xie, Bin Liang, Wanyun Cui, Yanghua Xiao, “CN-DBpedia: A Never-Ending Chinese Knowledge Extraction System”, IEA/AIE, Jun 2017
[4] Ram G. Athreya, Axel-Cyrille Ngonga Ngomo, Ricardo Usbeck, “Enhancing Community Interactions with Data-Driven Chatbots-The DBpedia Chatbot”, www’18, April 2018
[5] "Google Duplex: An AI System for Accomplishing Real-World Tasks Over the Phone" Google AI Blog, May 2018
[6] CHIN-MEI LIU, CHARLES TZU-CHI LEE, “Factors associated with future illicit drug recidivating for young adult students who misuse drugs: a population-based cohort study from Taiwan”, Taiwan J Public Health, 2018
[7] Ahmed Fadhil, "Assistive System in Conversational Agent for Health Coaching: The CoachAI Approach" arXiv, Apr 2019
[8] Meng-Han Tsai ,OrcID, James Yichu Chen, Shih-Chung Kang, “Ask Diana: A Keyword-Based Chatbot System for Water-Related Disaster Management” MDPI Water, Jan 2019
[9] 法務部, “毒品案件裁判確定有罪人數統計表”, 2018
[10] M. A. Wakefield, B. Loken, R. C. Hornik, "Use of mass media campaigns to change health behaviour", The Lancet, 2010.
[11] Chang-Mai Huang ; Jen-Hang Wang ; Sherry Y. Chen, “An Investigation of a Game-Based Anti-Drug System: Addictive Learners vs. Non-addictive Learners”, IEEE International Conference on Advanced Learning Technologies, 2015
[12] Tzu-Chi Yang ; Meng-Chang Chen ; Yeali S. Sun, “An Investigation of the Influence of Drug Addiction on Learning Behaviors in a Game-Based Learning Environment”, IEEE International Conference on Advanced Learning Technologies, 2017
[13] Maali Mnasri, “Recent advances in conversational NLP : Towards the standardization of Chatbot building”, arxiv, 2019.
[14] “World Drug Report notes stability in use of traditional drugs and points to alarming rise in new psychoactive substances”, UNODC, 2013.
[15] Amber Nigam, Prashik Sahare, Kushagra Pandya, “Intent Detection and Slots Prompt in a Closed-Domain Chatbot”, arxiv, 2018.
[16] Bingquan Liu ; Zhen Xu ; Chengjie Sun ; Baoxun Wang ; Xiaolong Wang ; Derek F. Wong ; Min Zhang, “Content-Oriented User Modeling for Personalized Response Ranking in Chatbots”, IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2018.
[17] Yankai Lin, Haozhe Ji, Zhiyuan Liu, Maosong Sun, “Denoising Distantly Supervised Open-Domain Question Answering”, ACL, 2018.
[18] Lin Xu, Qixian Zhou, Ke Gong, Xiaodan Liang, Jianheng Tang, Liang Lin, “End-to-End Knowledge-Routed Relational Dialogue System for Automatic Diagnosis”, arxiv, 2019.
[19] Wei Wu, Rui Yan, “Deep Chit-Chat: Deep Learning for ChatBots”, EMNLP, 2018.
[20] Haolan Chen, Yu Xu, Dong Liu, Kunfeng Lai, Chenglin Wu, “MIX: Multi-Channel Information Crossing for Text Matching”, ACM KDD, 2018
[21] Baotian Hu, Zhengdong Lu, Hang Li, Qingcai Chen, “Convolutional Neural Network Architectures for Matching Natural Language Sentences”, NIPS, 2014
[22] Shengxian Wan, “A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations”, AAAI, 2016
[23] Wanyun Cui, Yanghua Xiao, Haixun Wang, Yangqiu Song, Seung-won Hwang, Wei Wang, “KBQA: Learning Question Answering over QA Corpora and Knowledge Bases”, arXiv, Mar 2019
[24] Heung-Yeung Shum, Xiaodong He, Di Li, “From Eliza to XiaoIce: Challenges and Opportunities with Social Chatbots”, arXiv, Feb 2018.
[25] Li Zhou, Jianfeng Gao, Di Li, Heung-Yeung Shum, "The Design and Implementation of XiaoIce, an Empathetic Social Chatbot" arXiv, Dec 2018
[26] Jianfeng Gao, Michel Galley, Lihong Li, "Neural Approaches to Conversational AI" arXiv, Dec 2018
[27] Shafquat Hussain, Ginige Athula, "Extending a conventional chatbot knowledge base to external knowledge source and introducing user based sessions for diabetes education" IEEE International Conference on Advanced Information Networking and Applications Workshops, May 2018
[28] Shih-Hung Wu, Liang-Pu Chen, Ping-Che Yang, Tsun Ku, "Automatic Dialogue Template Synthesis for Chatbot by Story Information Extraction" IEEE International Conference on Information Reuse and Integration, July 2018
[29] Jan-Gerrit Harms ; Pavel Kucherbaev ; Alessandro Bozzon ; Geert-Jan Houben, "Approaches for Dialog Management in Conversational Agents“, IEEE Internet Computing, March-April 2019
[30] Jeffrey O. Kephart ; Victor C. Dibia ; Jason Ellis ; Biplav Srivastava ; Kartik Talamadupula ; Mishal Dholakia, " An Embodied Cognitive Assistant for Visualizing and Analyzing Exoplanet Data“, IEEE Internet Computing, March-April 2019
[31] Kang-Min Kim ; Woo-Jong Ryu ; Jun-Hyung Park ; SangKeun Lee, "meChat: In-Device Personal Assistant for Conversational Photo Sharing“, IEEE Internet Computing, March-April 2019
[32] Kun Xu, Siva Reddy, Yansong Feng, Songfang Huang, Dongyan Zhao, “Question answering on freebase via relation extraction and textual evidence”, arXiv, 2016
[33] Zhao Yan, Nan Duan, Junwei Bao, Peng Chen, Ming Zhou, Zhoujun Li, Jianshe Zhou, “DocChat: An Information Retrieval Approach for Chatbot Engines Using Unstructured Documents”, ACL, 2016.
[34] Zhou Yu, Alexandros Papangelis, and Alexander Rudnicky. 2015. “TickTock: A non-goal-oriented multimodal dialog system with engagement awareness.” In Proceedings of the AAAI Spring Symposium
[35] Haolan Chen, Yu Xu, Dong Liu, Kunfeng Lai, Chenglin Wu, Fred X. Han, Di Niu, “MIX: Multi-Channel Information Crossing for Text Matching” ACM SIGKDD , August 2018
[36] Zhou Yu, Alexandros Papangelis, and Alexander Rudnicky, “TickTock: A non-goal-oriented multimodal dialog system with engagement awareness.” In Proceedings of the AAAI Spring Symposium, 2015
[37] Jay Pujara, Hui Miao, Lise Getoor, William Cohen, “Knowledge Graph Identification”, ISWC, 2013
[38] Ilya Sutskever, Oriol Vinyals, Quoc V Le..” Sequence to sequence learning with neural networks. In Advances in neural information processing systems.”, ACM, 2014
[39] Tianran Hu, Anbang Xu, Zhe Liu, Quanzeng You, Yufan Guo, Vibha Sinha, Jiebo Luo, Rama Akkiraju, “Touch Your Heart: A Tone-aware Chatbot for Customer Care on Social Media”, arXiv, 2018
指導教授 吳曉光 審核日期 2019-7-24
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明