Archive for March, 2011

Updated Usecase

In the past couple of months, we have discussed the application and its features in depth during our group meetings. These discussions have lead to some changes in our application. The following diagram is the updated version of our use case diagram.

Read the rest of this entry »

No Comments

Towards linked data

Most Social networks at the moment provide information through APIs using json, jsonp or XML serialization. This reaches the third out of five stars on the linked data star rating system [1]. In our architecture we wanted to provide four and five star on linked data rating system by publishing the users’ data in RDF format. In this way people who give permission to do so they are able to point to movies they watched, liked or commented. In that way software agents can take advantage of this information and make suggestions like, movies that me and my friend does not have seen and combined with our agenda information the agent is able to suggest cinemas and hours and movies that we might like.

Read the rest of this entry »

, , , , , , , , , , , , , , , , , , , ,

1 Comment

MovieIt interaction sequence

This posts is going to answer the question of “How does it all work?”

We have visualised the sequence of interactions between the clients, server, database and facebook using UML sequence diagram. The following screenshot shows the interactions whithin MovieIt application.

No Comments

Project open discussion

Project discussionLast week we ran an open discussion of our project. The focus group of four people critically evaluated our idea and expressed their opinions how to extend and improve proposed system. Invited reviewers considered presented suggestion tool from different points of view: starting from required functionality and technical details and ending with social, legal and economic aspects. Below is a short description of the most interesting ideas and critics expressed during the meeting.

Read the rest of this entry »

, , ,

4 Comments

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.  

To check the results click on the rest of this entry…

Read the rest of this entry »

1 Comment

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.

Read the rest of this entry »

, , , ,

2 Comments

Usecase

No Comments