Archive for March 8th, 2011

Survey

http://www.eSurveysPro.com/Survey.aspx?id=b9cb2f32-a7f9-4b70-ac7d-bbaef09f247c

As mentioned before, our proposed system is a movie recommendation system that tells its users what movies to watch and also who has suggested that movie. It also suggests its users the best place for them to watch the movie using geo-location info. Another feature of our system is that it lets its users to know who from their friends might be interested in watching the movie.

In order to estimate the usability of our system, we conducted a survey to check other people`s opinions about our system. What the results show, encourage us to work harder on our system.

About 30 people took part in our survey. 94% of them are interested in watching movies. 42.31% of them prefer to watch a movie with other people at social places and 33.33% of them prefer cinema instead of home or any other places. 59.26% of them go to the movies with their friends. Internet is the best way for 59.26% of them to choose a movie to watch and 25.93% of them use their friend recommendations. More than 95% of them show interest in telling or recommending their favourite movies to their friends. Almost all of them have Facebook accounts and more than half of them want to use Facebook as a way to tell their friends about the movies they have watched and enjoyed. Some of them use their mobile phones to search for a movie or cinema. More than 80% believe that the location of the cinema is very important for them and they want to tell their friends about the location and quality of the cinema they have been to.  

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Idea evaluation

CyberTube Recommendation System logoIn previous posts (literature survey, existing applications) devoted to a field of interests’ investigation, we published an overview of existing applications and researches related to our initial idea. The survey showed that the demand in the web market and research community for recommendation systems, has led to its mass production in the past few years. Some of these suggestion tools are quite successful (Jinni, Filmaster Blog, Faves for Facebook, etc.) as they provide rich functionality and a good quality of recommendations.  However, in this sketch we will differentiate our idea from existing solutions and also outline strengths of the proposed system.

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