Netflix: the Streaming Challenge1
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The Netflix Prize Contest
1) New Paths to New Machine Learning Science 2) How an Unruly Mob Almost Stole the Grand Prize at the Last Moment Jeff Howbert University of Washington February 4, 2014 Netflix Viewing Recommendations Recommender Systems DOMAIN: some field of activity where users buy, view, consume, or otherwise experience items PROCESS: 1. users provide ratings on items they have experienced 2. Take all < user, item, rating > data and build a predictive model 3. For a user who hasn’t experienced a particular item, use model to predict how well they will like it (i.e. predict rating) Roles of Recommender Systems y Help users deal with paradox of choice y Allow online sites to: y Increase likelihood of sales y Retain customers by providing positive search experience y Considered essential in operation of: y Online retailing, e.g. Amazon, Netflix, etc. y Social networking sites Amazon.com Product Recommendations Social Network Recommendations y Recommendations on essentially every category of interest known to mankind y Friends y Groups y Activities y Media (TV shows, movies, music, books) y News stories y Ad placements y All based on connections in underlying social network graph, and the expressed ‘likes’ and ‘dislikes’ of yourself and your connections Types of Recommender Systems Base predictions on either: y content‐based approach y explicit characteristics of users and items y collaborative filtering approach y implicit characteristics based on similarity of users’ preferences to those of other users The Netflix Prize Contest y GOAL: use training data to build a recommender system, which, when applied to qualifying data, improves error rate by 10% relative to Netflix’s existing system y PRIZE: first team to 10% wins $1,000,000 y Annual Progress Prizes of $50,000 also possible The Netflix Prize Contest y CONDITIONS: y Open to public y Compete as individual or group y Submit predictions no more than once a day y Prize winners must publish results and license code to Netflix (non‐exclusive) y SCHEDULE: y Started Oct. -
Lessons Learned from the Netflix Contest Arthur Dunbar
Lessons Learned from the Netflix Contest Arthur Dunbar Background ● From Wikipedia: – “The Netflix Prize was an open competition for the best collaborative filtering algorithm to predict user ratings for films, based on previous ratings without any other information about the users or films, i.e. without the users or the films being identified except by numbers assigned for the contest.” ● Two teams dead tied for first place on the test set: – BellKor's Pragmatic Chaos – The Ensemble ● Both are covered here, but technically BellKor won because they submitted their algorithm 20 minutes earlier. This even though The Ensemble did better on the training set (barely). ● Lesson one learned! Be 21 minutes faster! ;-D – Don't feel too bad, that's the reason they won the competition, but the actual test set data was slightly better for them: ● BellKor RMSE: 0.856704 ● The Ensemble RMSE: 0.856714 Background ● Netflix dataset was 100,480,507 date-stamped movie rating performed by anonymous Netflix customers between December 31st 1999 and December 31st 2005. (Netflix has been around since 1997) ● This was 480,189 users and 17,770 movies Background ● There was a hold-out set of 4.2 million ratings for a test set consisting of the last 9 movies rated by each user that had rated at lest 18 movies. – This was split in to 3 sets, Probe, Quiz and Test ● Probe was sent out with the training set and labeled ● Quiz set was used for feedback. The results on this were published along the way and they are what showed upon the leaderboard ● Test is what they actually had to do best on to win the competition. -
Home Video Philology: Methodological Reflections
Special – peer-reviewed Cinergie – Il cinema e le altre arti. N.13 (2018) https://doi.org/10.6092/issn.2280-9481/7878 ISSN 2280-9481 Home Video Philology: Methodological Reflections Valerio Sbravatti Submitted: March 1, 2018 – Revised version: May 25, 2018 Accepted: June 15, 2018 – Published: July 12, 2018 Abstract Digital home video is an extremely useful means of watching and analyzing films. However, scholars often neglect the fact that official home video or streaming releases of a film can have differences from theoriginal version of the film itself. Such variances typically are lack of film grain (resulting from digital noise reduction), differences in color grading, and soundtrack remixing. This can depend on the fact that the technicians who work on home video releases are unprepared, or are instructed to adjust the look and the sound of the film to the current taste, or because the filmmakers changed their mind and requested some modifications. Atany rate, film scholars must be aware of such possible inconsistencies, otherwise their study could be fallacious. In this article I discuss upon philological problems of home video releases mainly from a practical point of view. Keywords: Blu-ray Disc; DVD; film fandom; film philology; film restoration. Valerio Sbravatti: Sapienza Università di Roma (It) https://orcid.org/0000-0002-0817-6129 [email protected] Valerio Sbravatti (1988) has a PhD in Music and performing arts at Sapienza University of Rome, where he is honorary fellow in film studies. His main research interests are film sound and film music, on which he published somearticlesand a book (Allegro non troppo. -
VHS and VCR (Edited from Wikipedia)
VHS And VCR (Edited from Wikipedia) SUMMARY A videocassette recorder, VCR, or video recorder is an electromechanical device that records analog audio and analog video from broadcast television or other source on a removable, magnetic tape videocassette, and can play back the recording. Use of a VCR to record a television program to play back at a more convenient time is commonly referred to as timeshifting. VCRs can also play back prerecorded tapes. In the 1980s and 1990s, prerecorded videotapes were widely available for purchase and rental, and blank tapes were sold to make recordings. Most domestic VCRs are equipped with a television broadcast receiver (tuner) for TV reception, and a programmable clock (timer) for unattended recording of a television channel from a start time to an end time specified by the user. These features began as simple mechanical counter-based single-event timers, but were later replaced by more flexible multiple-event digital clock timers. In later models the multiple timer events could be programmed through a menu interface displayed on the playback TV screen ("on-screen display" or OSD). This feature allowed several programs to be recorded at different times without further user intervention, and became a major selling point. The Video Home System (VHS) is a standard for consumer-level analog video recording on tape cassettes. Developed by Victor Company of Japan (JVC) in the early 1970s, it was released in Japan in late 1976 and in the United States in early 1977. From the 1950s, magnetic tape video recording became a major contributor to the television industry, via the first commercialized video tape recorders (VTRs). -
1 WELCOME to the NEW WORLD of DISTRIBUTION by Peter Broderick
WELCOME TO THE NEW WORLD OF DISTRIBUTION By Peter Broderick (First appeared in indieWIRE, September 16 & 17, 2008) Welcome to the New World of Distribution. Many filmmakers are emigrating from the Old World, where they have little chance of succeeding. They are attracted by unprecedented opportunities and the freedom to shape their own destiny. Life in the New World requires them to work harder, be more tenacious, and take more risks. There are daunting challenges and no guarantees of success. But this hasn’t stopped more and more intrepid filmmakers from exploring uncharted territory and staking claims. Before the discovery of the New World, the Old World of Distribution reigned supreme. It is a hierarchical realm where filmmakers must petition the powers that be to grant them distribution. Independents who are able to make overall deals are required to give distributors total control of the marketing and distribution of their films. The terms of these deals have gotten worse and few filmmakers end up satisfied. All is not well for companies and filmmakers in what I call the Old World of Distribution. At Film Independent’s Film Financing Conference, Mark Gill vividly described “the ways the independent film business is in trouble” in his widely read and discussed keynote. Mark listed the companies and divisions that have been shut down or are teetering on the brink of bankruptcy, noted that five others are in “serious financial peril,” and said that ten independent film financiers may soon “exit the business.” Mark made a persuasive case that “the sky really is falling… because the accumulation of bad news is kind of awe-inspiring.” While he doesn’t 1 expect that the sky will “hit the ground everywhere,” he warned “it will feel like we just survived a medieval plague. -
Distribution Forward Distribution Forward: a Guide to Strategic Self-Initiated Digital and DVD Documentary Film Distribution
Distribution Forward Distribution Forward: a guide to strategic self-initiated digital and DVD documentary film distribution. THIS PUBLICATION WAS MADE POSSIBLE THROUGH THE SUPPORT OF: 1 Contents Introduction 3 Elizabeth Radshaw, Hot Docs Forum and Market Director The Marketplace 4 Elizabeth Radshaw, Hot Docs Forum and Market Director The Rights 6 Greg Rubidge, Syndicado The Players 7 Greg Rubidge, Syndicado The Deals 8 Greg Rubidge, Syndicado The Strategy 9 • Greg Rubdige, Syndicado 9 • Jon Reiss, JonReiss.com 12 • Melanie Miller, Gravitas Ventures 19 • Robin Smith, KinoSmith 14 • Andrew Mer, Snag Films 18 The Example 21 Felice Gorica, Gorica Productions The Wisdom 23 Janet Brown, Cinetic The Resources 24 2 Introduction Distribution Forward: a guide to strategic self-initiated digital and DVD documentary film distribution. Distribution Forward illustrates the current climate of digital and DVD distribution of documentary films through examples, case studies and direct market intelligence from players in the field. This guide will provide tools, information and support to help filmmakers determine their own strategies for their films’ market trajectory. Additionally, Distribution Forward intends to dispel the myths Twitter length conversation bubbles @DistributionFwd tiny bits of and better inform filmmakers about the realities of the market distribution wisdom. place, helping them to achieve positive results and meet their financial, professional and artistic goals. The dialogue around digital documentary distribution has run the gamut of DIY, DIWO, hybrid, and self-distribution, which can confuse filmmakers and muddle their expectations. This guide intends to shed some light on the current climate. It is by no means exhaustive and there are a many avenues worthy of exploration. -
An In-Home Video Study and Questionnaire Survey of Food Preparation, Kitchen Sanitation, and Hand Washing Practices
AdvAncEmEnt of tHE SCIENCE An In-Home Video Study and Questionnaire Survey of Food Preparation, Kitchen Sanitation, and Hand Washing Practices Elizabeth Scott, PhD Nancie Herbold, RD, EdD million for premature deaths, $30 million for medical care, and $5 million in lost pro- Foodborne illnesses pose a problem to all individuals Abstract ductivity (Frenzen, Drake, Angulo, & the but are especially signifi cant for infants, the elderly, and individuals with Emerging Infections Program FOODNET compromised immune systems. Personal hygiene is recognized as the num- Working Group, 2005). ber-one way people can lower their risk. The majority of meals in the U.S. A new interest has arisen in household are eaten at home. Little is known, however, about the actual application of practices as a result of the understanding that a link exists between contaminated personal hygiene and sanitation behaviors in the home. inanimate surfaces and disease transmis- The study discussed in this article assessed knowledge of hygiene prac- sion and acquisition within settings such tices compared to observed behaviors and determined whether knowledge as the home (Cozad & Jones, 2003). Do- equated to practice. It was a descriptive study involving a convenience sam- mestic sanitation practices, especially those ple of 30 households. Subjects were recruited from the Boston area and a employing wet sponges, cloths, and mops, have been found to further disseminate bac- researcher and/or a research assistant traveled to the homes of study par- teria to other inanimate surfaces and direct- ticipants to videotape a standard food preparation procedure preceded by ly to the hands, leading to cross-contami- fl oor mopping. -
Netflix and the Development of the Internet Television Network
Syracuse University SURFACE Dissertations - ALL SURFACE May 2016 Netflix and the Development of the Internet Television Network Laura Osur Syracuse University Follow this and additional works at: https://surface.syr.edu/etd Part of the Social and Behavioral Sciences Commons Recommended Citation Osur, Laura, "Netflix and the Development of the Internet Television Network" (2016). Dissertations - ALL. 448. https://surface.syr.edu/etd/448 This Dissertation is brought to you for free and open access by the SURFACE at SURFACE. It has been accepted for inclusion in Dissertations - ALL by an authorized administrator of SURFACE. For more information, please contact [email protected]. Abstract When Netflix launched in April 1998, Internet video was in its infancy. Eighteen years later, Netflix has developed into the first truly global Internet TV network. Many books have been written about the five broadcast networks – NBC, CBS, ABC, Fox, and the CW – and many about the major cable networks – HBO, CNN, MTV, Nickelodeon, just to name a few – and this is the fitting time to undertake a detailed analysis of how Netflix, as the preeminent Internet TV networks, has come to be. This book, then, combines historical, industrial, and textual analysis to investigate, contextualize, and historicize Netflix's development as an Internet TV network. The book is split into four chapters. The first explores the ways in which Netflix's development during its early years a DVD-by-mail company – 1998-2007, a period I am calling "Netflix as Rental Company" – lay the foundations for the company's future iterations and successes. During this period, Netflix adapted DVD distribution to the Internet, revolutionizing the way viewers receive, watch, and choose content, and built a brand reputation on consumer-centric innovation. -
Introduction
Introduction James Bennett Charles Elkan Bing Liu Netflix Department of Computer Science and Department of Computer Science 100 Winchester Circle Engineering University of Illinois at Chicago Los Gatos, CA 95032 University of California, San Diego 851 S. Morgan Street La Jolla, CA 92093-0404 Chicago, IL 60607-7053 [email protected] [email protected] [email protected] Padhraic Smyth Domonkos Tikk Department of Computer Science Department of Telecom. & Media Informatics University of California, Irvine Budapest University of Technology and Economics CA 92697-3425 H-1117 Budapest, Magyar Tudósok krt. 2, Hungary [email protected] [email protected] INTRODUCTION Both tasks employed the Netflix Prize training data set [2], which The KDD Cup is the oldest of the many data mining competitions consists of more than 100 million ratings from over 480 thousand that are now popular [1]. It is an integral part of the annual ACM randomly-chosen, anonymous customers on nearly 18 thousand SIGKDD International Conference on Knowledge Discovery and movie titles. The data were collected between October, 1998 and Data Mining (KDD). In 2007, the traditional KDD Cup December, 2005 and reflect the distribution of all ratings received competition was augmented with a workshop with a focus on the by Netflix during this period. The ratings are on a scale from 1 to concurrently active Netflix Prize competition [2]. The KDD Cup 5 (integral) stars. itself in 2007 consisted of a prediction competition using Netflix Task 1 (Who Rated What in 2006): The task was to predict which movie rating data, with tasks that were different and separate from users rated which movies in 2006. -
Case Analysis.1
Management of Technology & Entrepreneurship (MTE) Technology Venturing & Entrepreneurship Sony Betamax Case Analysis GROUP 2 Patrick Hammer, Oliver Stampfli, Marcel Sutter, Thomas Thalmann, Donato Verardi [firstname.lastname]@epfl.ch Professor: Christopher L. Tucci Assistant: Farah Abdallah January 14, 2007 TSE - Sony Betamax - Case Analysis Group 2 Table of Content Summary of case report.................................................................... 2 Related topics and class sessions.................................................... 2 Format war (primary subject)............................................................................. 2 Customer needs............................................................................................... 2 Attacker’s advantage........................................................................................ 3 List of discussion questions.............................................................. 3 Brief answers..................................................................................... 3 Detailed answers............................................................................... 4 Recommendations.......................................................................... 10 Lessons learned.............................................................................. 10 Exhibits ............................................................................................11 Seven Key assets by Shapiro & Varian [6] [7] ................................................. -
ŠKODA AUTO VYSOKÁ ŠKOLA O.P.S. Valuation of Netflix, Inc. Diploma
ŠKODA AUTO VYSOKÁ ŠKOLA o.p.s. Course: Economics and Management Field of study/specialisation: Corporate Finance in International Business Valuation of Netflix, Inc. Diploma Thesis Bc. Alena Vershinina Thesis Supervisor: doc. Ing. Tomáš Krabec, Ph.D., MBA 2 I declare that I have prepared this thesis on my own and listed all the sources used in the bibliography. I declare that, while preparing the thesis, I followed the internal regulation of ŠKODA AUTO VYSOKÁ ŠKOLA o.p.s. (hereinafter referred to as ŠAVŠ), directive OS.17.10 Thesis guidelines. I am aware that this thesis is covered by Act No. 121/2000 Coll., the Copyright Act, that it is schoolwork within the meaning of Section 60 and that under Section 35 (3) ŠAVŠ is entitled to use my thesis for educational purposes or internal requirements. I agree with my thesis being published in accordance with Section 47b of Act No. 111/1998 Coll., on Higher Education Institutions. I understand that ŠAVŠ has the right to enter into a licence agreement for this work under standard conditions. If I use this thesis or grant a licence for its use, I agree to inform ŠAVŠ about it. In this case, ŠAVŠ is entitled to demand a contribution to cover the costs incurred in the creation of this work up to their actual amount. Mladá Boleslav, Date ......... 3 I would like to thank doc. Ing. Tomáš Krabec, Ph.D., MBA for his professional supervision of my thesis, advice, and information. I also want to thank the ŠAVS management for their support of the students’ initiative. -
When Diversity Met Accuracy: a Story of Recommender Systems †
proceedings Extended Abstract When Diversity Met Accuracy: A Story of Recommender Systems † Alfonso Landin * , Eva Suárez-García and Daniel Valcarce Department of Computer Science, University of A Coruña, 15071 A Coruña, Spain; [email protected] (E.S.-G.); [email protected] (D.V.) * Correspondence: [email protected]; Tel.: +34-881-01-1276 † Presented at the XoveTIC Congress, A Coruña, Spain, 27–28 September 2018. Published: 14 September 2018 Abstract: Diversity and accuracy are frequently considered as two irreconcilable goals in the field of Recommender Systems. In this paper, we study different approaches to recommendation, based on collaborative filtering, which intend to improve both sides of this trade-off. We performed a battery of experiments measuring precision, diversity and novelty on different algorithms. We show that some of these approaches are able to improve the results in all the metrics with respect to classical collaborative filtering algorithms, proving to be both more accurate and more diverse. Moreover, we show how some of these techniques can be tuned easily to favour one side of this trade-off over the other, based on user desires or business objectives, by simply adjusting some of their parameters. Keywords: recommender systems; collaborative filtering; diversity; novelty 1. Introduction Over the years the user experience with different services has shifted from a proactive approach, where the user actively look for content, to one where the user is more passive and content is suggested to her by the service. This has been possible due to the advance in the field of recommender systems (RS), making it possible to make better suggestions to the users, personalized to their preferences.