| dc.contributor.advisor | 張源俊 | zh_TW |
| dc.contributor.advisor | Chang, Yuan-Chin | en_US |
| dc.contributor.author (Authors) | 洪浚皓 | zh_TW |
| dc.contributor.author (Authors) | Hung, Chun-Hao | en_US |
| dc.creator (作者) | 洪浚皓 | zh_TW |
| dc.creator (作者) | Hung, Chun-Hao | en_US |
| dc.date (日期) | 2020 | en_US |
| dc.date.accessioned | 2-Sep-2020 11:42:50 (UTC+8) | - |
| dc.date.available | 2-Sep-2020 11:42:50 (UTC+8) | - |
| dc.date.issued (上傳時間) | 2-Sep-2020 11:42:50 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0107354019 | en_US |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/131476 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 統計學系 | zh_TW |
| dc.description (描述) | 107354019 | zh_TW |
| dc.description.abstract (摘要) | 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。 | zh_TW |
| dc.description.abstract (摘要) | Watching films or motion pictures is an important entertainmentculture such that the film industry becomes more complex and unpredictablenowadays. After sucessfully syncroning sound and framesof film in 1927[10], Bambi (1942) had a huge progress in making ananimation film during World War II. Since then, as the advancementof technology and the development of filming techniques, the movieindustry 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 ofprocesses with all kinds of efforts. Thus, to have better prediction ofthe possible profit of our work, then it may encourage the productioncompanies to invest in such movies. In this thesis, we discuss thetrend of genre and other information via exploration data, and datavisualization, and then propose a prediction method for the potentialprofit of movies before investing more resources. Besides this maingoal – predicting movie profits, we also discuss how to have a novelrecommendation system via modifying the ideas of the blog post aspotential future studies. | en_US |
| dc.description.tableofcontents | 1 Introduction 42 Introduction of MovieLens dataset 62.1 MovieLens 20M Dataset 62.2 The Calibrated Data 73 EDA on Rating Data 104 Recommendation System 165 Trend of Genres 235.1 Genre Trend 245.2 Genre Similarity Matrix 266 Tag Analysis 287 Predict Movie Profits 317.1 Scraping Dataset 327.2 EDA and Data Cleaning 347.3 Building Model and Prediction 488 Conclusion and Future Studies 539 Reference 56 | zh_TW |
| dc.format.extent | 42852076 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0107354019 | en_US |
| dc.subject (關鍵詞) | MovieLens 資料集 | zh_TW |
| dc.subject (關鍵詞) | 機器學習 | zh_TW |
| dc.subject (關鍵詞) | 推薦系統 | zh_TW |
| dc.subject (關鍵詞) | 探索性資料分析 | zh_TW |
| dc.subject (關鍵詞) | MovieLens Dataset | en_US |
| dc.subject (關鍵詞) | Machine Learning | en_US |
| dc.subject (關鍵詞) | Recommendation System | en_US |
| dc.subject (關鍵詞) | Exploratory Data Analysis | en_US |
| dc.title (題名) | 統計分析與資料視覺化在電影利潤預測上之研究 | zh_TW |
| dc.title (題名) | Applications of Statistical Analysis and Data Visualization to MovieLens Data for Profit Prediction | en_US |
| dc.type (資料類型) | thesis | en_US |
| dc.relation.reference (參考文獻) | [1] James Baglama and Lothar Reichel. “Augmented implicitly restartedLanczos bidiagonalization methods”. In: SIAM Journal on ScientificComputing 27.1 (2005), pp. 19–42.[2] Posts on Data Science Diarist. Building a Recommendation Systemwith 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 sparsematrix 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 decisiontree”. 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 musictechnology. Oxford University Press on Demand, 2013.[32] Wikipedia. MovieLens. https://en.wikipedia.org/wiki/MovieLens.Accessed: 2020-05-20. | zh_TW |
| dc.identifier.doi (DOI) | 10.6814/NCCU202001674 | en_US |
