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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/131476


    Title: 統計分析與資料視覺化在電影利潤預測上之研究
    Applications of Statistical Analysis and Data Visualization to MovieLens Data for Profit Prediction
    Authors: 洪浚皓
    Hung, Chun-Hao
    Contributors: 張源俊
    Chang, Yuan-Chin
    洪浚皓
    Hung, Chun-Hao
    Keywords: MovieLens 資料集
    機器學習
    推薦系統
    探索性資料分析
    MovieLens Dataset
    Machine Learning
    Recommendation System
    Exploratory Data Analysis
    Date: 2020
    Issue Date: 2020-09-02 11:42:50 (UTC+8)
    Abstract: 隨著電影成為重要的娛樂文化，在今日，電影產業已經成長得
    相當龐大以及難以預測。自從電影在1927年，聲音以及影像能被同
    步，到小鹿斑比(1942)以動畫電影在第二次世界大戰期間取得巨大的
    成功。在往後的70年間，隨著科技的進步以及拍攝手法的發展，電
    影產業成長的速度極為快速，今日，一部電影需要經過極大的努力
    以及許多的手續，才能被大眾觀賞。因此若我們能精準的預測一部
    作品的利潤，則能更好的說服製片公司能投資龐大的金錢以製作出
    好電影。在本篇論文，我們會透過資料探索以及資料視覺化探討電
    影類別的趨勢，然後提出一個方法，在投入那些巨大努力之前，來
    預測電影利潤。除利預測利潤這個主要目標之外，我們還會基於一
    個部落格文章的想法做修改，提出一個建造推薦系統的方法。
    Watching films or motion pictures is an important entertainment
    culture such that the film industry becomes more complex and unpredictable
    nowadays. After sucessfully syncroning sound and frames
    of film in 1927[10], Bambi (1942) had a huge progress in making an
    animation film during World War II. Since then, as the advancement
    of technology and the development of filming techniques, the movie
    industry has grown rapidly and vastly in the following 70 years. Now,
    to play a piece of work to audiences, we have to go through a lot of
    processes with all kinds of efforts. Thus, to have better prediction of
    the possible profit of our work, then it may encourage the production
    companies to invest in such movies. In this thesis, we discuss the
    trend of genre and other information via exploration data, and data
    visualization, and then propose a prediction method for the potential
    profit of movies before investing more resources. Besides this main
    goal – predicting movie profits, we also discuss how to have a novel
    recommendation system via modifying the ideas of the blog post as
    potential future studies.
    Reference: [1] James Baglama and Lothar Reichel. “Augmented implicitly restarted
    Lanczos bidiagonalization methods”. In: SIAM Journal on Scientific
    Computing 27.1 (2005), pp. 19–42.
    [2] Posts on Data Science Diarist. Building a Recommendation System
    with Beer Data. https : / / www . r - bloggers . com / building - a -
    recommendation-system-with-beer-data/. Accessed: 2020-05-20.
    [3] Timothy A Davis and Yifan Hu. “The University of Florida sparse
    matrix collection”. In: ACM Transactions on Mathematical Software
    (TOMS) 38.1 (2011), pp. 1–25.
    [4] IMDb. Året gjennom Børfjord (1991). https : / / www . imdb . com /
    title/tt0103301/. Accessed: 2020-05-20.
    [5] IMDb. Babylon 5. https : / / www . imdb . com / title / tt0105946/.
    Accessed: 2020-05-20.
    [6] IMDb. Bicicleta, cullera, poma (2010). https : / / www . imdb . com /
    title/tt1710542/. Accessed: 2020-05-20.
    [7] IMDb. Brazil: In the Shadow of the Stadiums. https://www.imdb.
    com/title/tt3778744/. Accessed: 2020-05-20.
    [8] IMDb. Cialo (original title). https://www.imdb.com/title/tt4358230/.
    Accessed: 2020-05-20.
    [9] IMDb. Das Millionenspiel (1970). https://www.imdb.com/title/
    tt0066079/. Accessed: 2020-05-20.
    [10] IMDb. Don Juan Trivia. https://www.imdb.com/title/tt0016804/
    trivia. Accessed: 2020-06-16.
    [11] IMDb. Im Schmerz geboren. https://www.imdb.com/title/tt3096440/.
    Accessed: 2020-05-20.
    [12] IMDb. In Our Garden (2002). https : / / www . imdb . com / title /
    tt0495225/. Accessed: 2020-05-20.
    [13] IMDb. Michael Laudrup - en fodboldspiller (1993). https : / / www .
    imdb.com/title/tt0378357/. Accessed: 2020-05-20.
    [14] IMDb. Moving Alan (2003). https://www.imdb.com/title/tt0310741/.
    Accessed: 2020-05-20.
    [15] IMDb. My Own Man (2014). https : / / www . imdb . com / title /
    tt3356434/. Accessed: 2020-05-20.
    [16] IMDb. National Theatre Live: Frankenstein (2011). https://www.
    imdb.com/title/tt1795369/. Accessed: 2020-05-20.
    [17] IMDb. P’tit Quinquin. https://www.imdb.com/title/tt3053694/.
    Accessed: 2020-05-20.
    [18] IMDb. Polskie gówno (2014). https : / / www . imdb . com / title /
    tt4438688/. Accessed: 2020-05-20.
    [19] IMDb. Slaying the Badger. https://www.imdb.com/title/tt3793686/.
    Accessed: 2020-05-20.
    [20] IMDb. Star Trek Beyond (original title). https://www.imdb.com/
    title/tt2660888/. Accessed: 2020-05-20.
    [21] IMDb. Star Trek IV: The Voyage Home (original title). https://www.
    imdb.com/title/tt0092007/. Accessed: 2020-05-20.
    [22] IMDb. Stephen Fry in America. https://www.imdb.com/title/
    tt1307789/. Accessed: 2020-05-20.
    [23] IMDb. The Court-Martial of Jackie Robinson (1990). https://www.
    imdb.com/title/tt0099311/. Accessed: 2020-05-20.
    [24] IMDb. The Dark Knight Trivia. https://www.imdb.com/title/
    tt0468569/trivia. Accessed: 2020-06-30.
    [25] IMDb. Third Reich: The Rise Fall. https://www.imdb.com/title/
    tt1855924/. Accessed: 2020-05-20.
    [26] IMDb. Two: The Story of Roman Nyro (2013). https://www.imdb.
    com/title/tt2740874/. Accessed: 2020-05-20.
    [27] Guolin Ke et al. “Lightgbm: A highly efficient gradient boosting decision
    tree”. In: Advances in neural information processing systems.
    2017, pp. 3146–3154.
    [28] Sven Kosub. “A note on the triangle inequality for the Jaccard distance”.
    In: Pattern Recognition Letters 120 (2019), pp. 36–38.
    [29] MovieLens. Star Trek Beyond. https://movielens.org/movies/
    135569. Accessed: 2020-05-20.
    [30] MovieLens. Star Trek IV: The Voyage Home. https://movielens.
    org/movies/1376. Accessed: 2020-05-20.
    [31] Scott L Phillips. Beyond sound: the college and career guide in music
    technology. Oxford University Press on Demand, 2013.
    [32] Wikipedia. MovieLens. https://en.wikipedia.org/wiki/MovieLens.
    Accessed: 2020-05-20.
    Description: 碩士
    國立政治大學
    統計學系
    107354019
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0107354019
    Data Type: thesis
    DOI: 10.6814/NCCU202001674
    Appears in Collections:[Department of Statistics] Theses

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