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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/128575


    Title: 以機器學習方法評估旅館業發展潛能
    Using Machine Learning To Evaluate The Development Potential Of The Hotel Industry
    Authors: 莊家榮
    Chuang, Chia-Jung
    Contributors: 謝明華
    Hsieh, Ming-Hua
    莊家榮
    Chuang, Chia-Jung
    Keywords: 人工智慧
    自然語言處理
    Artificial intelligence
    AI
    Natural Language Processing
    Date: 2019
    Issue Date: 2020-02-05 17:39:07 (UTC+8)
    Abstract: 2017年可以說是人工智慧應用大爆發的一年,各式各樣的AI應用都在不同領域中有所突破,從交通、醫療到娛樂服務。人工智慧的進步不但能提供更佳的決策,亦能強化組織能力並增加效率。在過去十年中,幾乎所有企業都或多或少接觸了數位轉型。在未來可以預見的是,許多以人工智慧為基礎所開發的系統開始進行各種商業測試,也會有許多供應商接著推出由人工智慧所打造的資料分析商業軟體,幫助品牌預測影響客戶留存率的關鍵點或是提升品牌與客戶間的互動。
    本篇研究之自然語言處理、數據分析之結果,便能了解到哪些因素會影響到顧客對顧客對飯店的評論,進而影響到評論分數的高低。
    2017 can be said to be the year of the explosion of artificial intelligenceapplications. A variety of AI applications have made breakthroughs in different fields, from transportation, medical to entertainment services. Advances in artificial intelligence not only provide better decisions, they also strengthen organizational capabilities and increase efficiency. Over the past decade, almost all companies have been more or less exposed to digital transformation. In the future, it is foreseeable that many systems developed based on artificial intelligence will start various commercial tests, and many vendors will then launch data analysis business software created by artificial intelligence to help brands predict the impact of customer retention The key point is to improve the interaction between the brand and the customer.
    From the results of natural language processing and data analysis in this study, we can understand what factors affect customer reviews of restaurants, and then affect the level of review scores.
    Reference: 林大貴(2017)。Tensorflow+keras深度學習人工智慧實務應用。新北市:博碩。

    人工智能. (n.d.).In Wikipedia.,上網日期107年11月25日,
    檢自: https://wiki.mbalib.com/zh-tw/人工智能

    蕭佑和(2018).完整解析AI人工智慧:3大浪潮+3大技術+3大應用,
    上網日期107年11月25日,
    檢自:https://meethub.bnext.com.tw/完整解析ai人工智慧:3大浪潮+3大技術+3大應用

    c.s.blog.2017.Understanding LSTM Networks,from:http://colah.github.io/posts/2015-08-Understanding-LSTMs/

    Entrepreneur Network.(2018/1/18).10 Artificial Intelligence Trends to Watch in 2018.fromhttps://www.entrepreneur.com/article/307589
    Géron, A. (2017). Hands-on machine learning with Scikit-Learn and TensorFlow: concepts, tools, and techniques to build intelligent systems: " O`Reilly Media, Inc.".
    Hochreiter, S., & Schmidhuber, J. J. N. c. (1997). Long short-term memory. 9(8), 1735-1780.

    Jacques Bughin, Eric Hazan, SreeRamaswamy, Michael Chui, TeraAllas, Peter Dahlström, Nicolaus Henke, and Monica Trench(2017). How artificial intelligence can deliver real value to companies,from https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-artificial-intelligence-can-deliver-real-value-to-companies

    M. Abadi, A. Agarwal et al., "Tensorflow: Large-scale machine learning on heterogeneous distributed systems", 2016.

    PwC (2017).Sizing the prize What’s the real value of AI for your business and how can you capitalise?,fromhttps://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report.pdf

    Sebastian RaschkaVahidMirjalili (2015). Python Machine Learning.Birmingham :Packt Publishing Ltd
    Description: 碩士
    國立政治大學
    經營管理碩士學程(EMBA)
    105932407
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0105932407
    Data Type: thesis
    DOI: 10.6814/NCCU202000034
    Appears in Collections:[Executive Master of Business Administration] Theses

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