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Kandidat 109 INFO310 0 Advanced Topics in Model-Based Information Systems Kandidat 109 Oppgaver Oppgavetype Vurdering Status Introduction Dokument Automatisk poengsum Levert Plagiarism and Declaration Dokument Automatisk poengsum Levert 1 Essay Filopplasting Manuell poengsum Levert INFO310 0 Advanced Topics in Model-Based Information Systems Emnekode INFO310 PDF opprettet 16.11.2016 16:36 Vurderingsform INFO310 Opprettet av Andreas Lothe Opdahl Starttidspunkt: 03.11.2016 14:00 Antall sider 22 Sluttidspunkt: 09.11.2016 14:00 Oppgaver inkludert Nei Sensurfrist Ikke satt Skriv ut automatisk rettede Nei 1 Kandidat 109 Seksjon 1 1 OPPGAVE Essay Upload your file here. Maximum one file. BESVARELSE Filopplasting Filnavn 9066477_cand-9333784_9157556 Filtype pdf Filstørrelse 1660.232 KB Opplastingstid 09.11.2016 09:38:21 Neste side Besvarelse vedlagt INFO310 0 Advanced Topics in Model-Based Information Systems Page 2 av 22 Kandidat 109 SEMANTICS TECHNOLOGIES IN STREAMING SERVICES By Gonzalo Molina Gallego INFO310 0 Advanced Topics in Model-Based Information Systems Page 3 av 22 Kandidat 109 INDEX INTRODUCTION ......................................................................................................................... 3 THE ARISING OF STREAMING SERVICES ............................................................................ 3 VIDEO STREAMING SERVICES .......................................................................................... 4 MUSIC STREAMING SERVICES .......................................................................................... 5 RECOMMENDER SYSTEMS ..................................................................................................... 5 TYPES OF RECOMMENDER SYSTEMS ............................................................................. 5 COLLABORATIVE FILTERING ........................................................................................ 5 CONTENT-BASED FILTERING ........................................................................................ 6 HYBRID RECOMMENDER ............................................................................................... 6 SEMANTIC RECOMMENDER SYSTEM .............................................................................. 6 PANDORA AND MUSIC GENOME PROJECT ........................................................................ 7 SEMANTIC SIMILARITY METHOD .................................................................................... 8 MUSIC GENOME PROJECT .................................................................................................. 8 SUPPORT VECTOR MACHINES ...................................................................................... 9 MY CONTRIBUTION – TESTING PANDORA..................................................................... 9 JINNI AND MOVIE GENOME PROJECT ............................................................................... 12 CONCLUSION & CHALLENGES ............................................................................................ 13 FIGURES .................................................................................................................................... 14 REFERENCES ............................................................................................................................ 20 INFO310 0 Advanced Topics in Model-Based Information Systems Page 4 av 22 Kandidat 109 INTRODUCTION Nowadays we can see the rapid growth of streaming services, they offer us a large collection of media content and it does not need to download whole file. This is possible by the improvement of Internet network, bandwidth and storage. These advances combined with powerful computers are the principal reasons of the popularization of several streaming services. But in these past few years, we also see how the advantages of semantic technologies and the Web 2.0, and now the semantics technologies are present in some streaming services. On one hand, there are streaming music services, leads by Spotify. Spotify is the most popular streaming music service, it is in almost the whole world and it has a big database of songs, but does not have the best recommender system. Instead, exist other music streaming service, it is not able to use in many countries, but uses semantics technologies for recommend and discover new music that would like to the user. This service is Pandora Internet Radio, based on Music Genome, that offers music streaming and smart recommendations. Pandora is capable to analyses songs and creates a user’s profile based on the tastes of users. All this data about different songs is store in Music Genome and each song has approximately 450 tags or attributes to be compared with user’s tastes. On the other hand, we have movie streaming services and the most popular is Netflix, but Netflix at the beginning had a problem, it had not a good recommendation system. It created Netflix Prize to search the best engine to analyse user’s profile and tastes, but another recommender search arises, this recommender engine is Jinni. Jinni is the Pandora for movies, also uses a database like the Music Genome, but in this case, is Movie Genome, composed by thousands of tags to describe and analyse a movie. In this paper, we are going to see why semantic recommendation are popular, what is the history of these recommender systems and how semantic recommendation systems work. THE ARISING OF STREAMING SERVICES First of all, we should analyse when and how streaming services appears and how impact to people. Big companies like Netflix or Spotify are now increasingly used rather than TV or radio and that’s only the beginning of this new tendency. Streaming media is multimedia that is constantly received by and presented to an end-user while being delivered by a provider. Is an alternative to download because the end-user can use its data file (maybe a movie or music) before the entire file has been transmitted [1]. Through streaming media, the live streaming appears. With the live streaming, we can watch on Internet events happening in real-time, delivered to us via a television signals in real-time. INFO310 0 Advanced Topics in Model-Based Information Systems Page 5 av 22 Kandidat 109 With the improvements and the growth of the streaming media and the advances in computer networking, combined with powerful computers and fast Internet, several services or delivers of social media content has been created. The main improvement was the support of RTSP protocol. This protocol is used by media players and streaming services to control the transmission. Figure 1 shows how streaming media works. Nowadays, Jinni is one of the most popular recommendation engine for movies and Pandora for music, they use semantics search to improve the accuracy of the search and recommendation, for that reason, big social media companies are interested in this new technology, but before to talk deeply about these two companies, we should understand the explosive growth of streaming services. VIDEO STREAMING SERVICES Between the 19th and 20th ages, the television was invented and improved until to be in every house. TV is the main information system and is basically the easier way to influence people, for example the 99% of households in Unites States possess at least one television. According to the A.C. Nielsen Company, the average American spent more than 4 hours TV-watching [2]. Netflix provides streaming media and video on demand (VOD) – VOD are systems which allows users to watch video content when they choose to. Nowadays, Netflix has more than 85 million users in Worldwide and it revenues rise to 6.7$ billion. Can Netflix and new video-streaming systems dethrone Television? Video-streaming systems are used by almost the half of the people in Unites States, more precisely, in the 42% American households. Mainly, the video-streaming systems are more popular between the young people, the older people are still use the pay-TV [3]. As we have said before, each time, more and more teenagers join the new tendency of using other devices to view films instead of TV. In the Figure 2 we see the percentage of time watching TV shows by device in US. The time watching the TV is still the higher one in each range of ages, but if you focus only in the first range and in the last, you can see this tendency of using other devices. Finally, the Figure 3 shows the clear victory of online streaming over rent or purchase movies, in no case people prefer rent or purchase a film, they use online streaming to watch it [4]. The TV is still the favourite device to watch movies or TV shows, but in a few years, we will see how the online streaming platforms grow up and if we combine the advantages of streaming media with the semantic recommendation, streaming platforms will overtake live-TV. INFO310 0 Advanced Topics in Model-Based Information Systems Page 6 av 22 Kandidat 109 MUSIC STREAMING SERVICES With Spotify, we can listen our favourite music without download it in our smartphone or computer, because Spotify provides a digital music-streaming service [5]. But not only Spotify is helping music panorama, also there are many big companies like Google Play Music, Amazon Prime Music and Pandora. The global music market has a big problem with the piracy and the last years have been really difficult to music companies, but now tendency is changing to a better situation. The last 2015, streaming music services grow fast – more than 66%– and they overcome music physical format. Streaming music represents
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