Collecting user data with client side web techonolgies

OData support
Supervisor:
Szabó Zoltán
Department of Automation and Applied Informatics

Readers of big news sites might find useful the services of a

recommendation system, which, based on their previous choices, can

make recommendations from the latest articles. For testing and

training such recommendation systems, user-history data sets are

needed, that contain the reading history of users, and reflects their

preferences as closely as possible. But big news sites have many

articles, some emphasized heavily, and that biases the users choices,

and thus the preference-fidelity of the user-data. Browser-run

applications however can alter the appearance of the news sites, and

it can facilitate the easy finding of the articles that are really

interesting to the user.

This assignment's goal is to develop a browser-run application that,

firstly is capable of collecting user data and passing it on to a

server, and secondarily, it overwrite the typographic emphasis on the

news sites, and alters the arrangement of the articles in a way that

hopefully aids users in finding the articles that are interesting to

them. Data collected with this tool will hopefully give a more close

indication of the user tastes, and therefore recommendation systems

training on that data will give better recommendations.

In this paper I am going to present the steps of designing and

implementing such an application, and also study the difficulties met

and their solutions.

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