Collaborative filtering has been most widely used in commercial sites to recommend items based on the history of user preferences for items. The idea behind this method is to find similar users whose ratings for items are incorporated to make recommendation. Hence, similarity calculation is most critical in recommendation performance. For movie recommendation, this paper enhances performance of...

This project explores several Machine Learning methods to predict movie genres based on plot summaries. Naive Bayes, Word2Vec+XGBoost and Recurrent Neural Networks are used for text classification, while K-binary transformation, rank method and probabilistic classification with learned probability threshold are employed for the multi-label problem involved in the genre tagging task. Experiments...

We present a new method to evaluate a search ontology, which relies on mapping ontology instances to textual documents. On the basis of this mapping, we evaluate the adequacy of ontology relations by measuring their classification potential over the textual documents. This data-driven method provides concrete feedback to ontology maintainers and a quantitative estimation of the functional adequ...

The ultimate goal of this paper is to provide a comparative analysis Sorry for and about in the COCA BNC. When it comes COCA, interesting point out that types show same pattern TV/movie fiction genres academic genre, whereas they different blog, web, magazine, newspaper spoken genre. With respect BNC, significant note genre magazine misc, non-academic genres. It can thus be inferred these two a...

Movie producers and exhibitors make various decisions requiring an understanding of moviegoer’s preferences at the local level. Two examples of such decisions are exhibitors’ allocation of screens to movies, and producers’ allocation of advertising across different regions of the country. This study presents a predictive model of local demand for movies with two unique features. First, arguing ...

This paper examines the determinants of box office revenue in the motion picture industry. The sample consists of 505 films released during 2001-2003. Regression results indicate the primary determinants of box office earnings are critic reviews, award nominations, sequels, Motion Picture Association of America rating, budget, and release exposure. Specific results include the observation that ...