Collaborative filtering recommends items to a user based on the interests of other users having similar preferences. However, high dimensional, sparse data result in poor performance in collaborative filtering. This paper introduces an approach called multiple metadata-based collaborative filtering (MMCF), which utilizes meta-level information to alleviate this problem, e.g., metadata such as g...

User content curation is becoming an important source of preference data, as well as providing information regarding the items being curated. One popular approach involves the creation of lists. On Twitter, these lists might contain accounts relevant to a particular topic, whereas on a community site such as the Internet Movie Database (IMDb), this might take the form of lists of movies sharing...

in this article we study the attitudes of iranian cinema audience toward popular films. affected by classic elite cultural theories, popular culture and consumers of popular culture have been humiliated for many years. according to this theories, audience of popular magazines, popular music, popular films and other popular culture products, have been considered as passive victims. cultural stud...

Social tagging of movies reveals a wide range of heterogeneous information about movies, like the genre, plot structure, soundtracks, metadata, visual and emotional experiences. Such information can be valuable in building automatic systems to create tags for movies. Automatic tagging systems can help recommendation engines to improve the retrieval of similar movies as well as help viewers to k...

Major studios and independent production firms (Indies) often have to select or “greenlight” a portfolio of scripts to turn into movies. Despite the huge financial risk at stake, there is currently no risk management tool they can use to aid their decisions, even though such a tool is sorely needed. In this paper, we developed a forecasting and risk management tool, based on movies scripts, to ...

In the movie industry habit, the demand of exploitation windows next to theatres is usually related to the success in cinemas, which is assumed to orient subsequent consumption among audience. Using a data base made of 1035 movies broadcast in peak time by the six main Italian networks during the period 1993-2002, we regress movies’ tv audience outcome on several independent variables as the at...

Business organizations experience cut-throat competition in the e-commerce era, where a smart organization needs to come up with faster innovative ideas enjoy competitive advantages. A user decides from review information of an online product. Data-driven machine learning applications use real data support immediate decision making. Web scraping technologies supplying sufficient relevant and up...

We present a novel technique to characterize and index violent scenes in general TV drama and movies. Our goal is to identify violent signatures and localize violent events within a movie to support \high-level" video indexing. In particular, we exploit multiple \audiovisual" signatures to create a perceptual relation for conceptually meaningful violent scene identi cation. Potential applicatio...

The article discusses translation strategies of Audiovisual Translation engaged with the movie on Netflix. research concentrates involved in AVT subtitle case an adventure mystery genre Enola Holmes Netflix to know relation concept. This is audiovisual a qualitative descriptive, along data collecting English and Indonesian subtitles movie. From findings, it found nine applied translating result...