In this paper, we present our contribution to the Linked Data Mining Challenge 2015. Our approach predicts the review class of movies using external data from the Open Movie Database API (OMDb-API). We select specific features, such as movie ratings and box office, that are very likely to describe the quality of a movie. With RapidMiner we utilize these features and apply three basic classifica...

In this paper, we design and develop various strategies required for sentiment analysis of movie domain in mobile environment. The main objective of review mining and summarization is extracting the features on which the reviewers express their opinions and determining whether the opinions are positive or negative. The sentiment classification is done by various classifiers such as maximum entr...

In this research, we develop a multi-criteria movie recommendation system that provides personalised recommendations by taking into consideration both user preferences and aspects. To get over each method's specific drawbacks, the suggested takes hybrid approach combines collaborative filtering with content-based techniques. The uses to capture based on historical ratings, while methods analyze...

Currently, users and consumers can review and rate products through online services, which provide huge databases that can be used to explore people's preferences and unveil behavioral patterns. In this work, we investigate patterns in movie ratings, considering IMDb (the Internet Movie Database), a highly visited site worldwide, as a source. We find that the distribution of votes presents scal...

To entice the target audience into paying to see the full movie, the production of movie trailers is an integral part of movie industry. Action scene is the main component of a movie trailer. In this paper, we propose an automatic action scene detection algorithm based on the analysis of high-level video structure. The input video is first decomposed into a number of basic components called sho...

We propose a novel technique for automatically creating film comics reflecting the camera-works of an original movie. Camera-works are one of the most important effects contributing to the mise en scene of the movie. A skilled director can use the camera-works dexterously for drawing the attention of audiences, representing sentiments, and give a change of pace in the movie. When creating film ...

With the rise of various streaming services like Netflix and Amazon Prime, and the rise of movie collections offered by a single provider, the need for determining user-specific movie ratings increases. It is highly crucial for a company to know, and recommend the type of movies liked by users to increase customer retention and improve user experience. In this paper, we are going to use data mi...

This paper addresses the issue of unobserved heterogeneity in film characteristics influence on boxoffice. We argue that the analysis of pooled samples, most common among researchers, does not shed light on underlying segmentations and leads to significantly different estimates obtained by researchers running similar regressions for movie success modeling. For instance, it may be expected that ...

Introduction: We explore the issues that are present in the Netflix Prize dataset. The Netflix Prize seeks to substantially improve the accuracy of user movie rating prediction based on their previous movie preferences and ratings [1]. The contest started in October 2006 and seeks to beat the current Netflix recommendation system by 10% in prediction accuracy. Though some teams have improved pr...