A framework for real time recommendation system for web-content websites
Dissertant
Thesis advisor
Comitee Members
Qasif, Abd Allah
Awajan, Arafat
Ubayd, Nadim
University
Princess Sumaya University for Technology
Faculty
King Hussein Faculty for Computing Sciences
Department
Department of Computer Sciences
University Country
Jordan
Degree
Master
Degree Date
2015
English Abstract
The fast growth of technology in both software and hardware levels resulted in moving several industries like the industries of media, news, publishing, printing, and entertainment from classic approach to more digital approach.
This creates the need to understand the audience and their behaviors toward their products or services to increase their growth and improve satisfaction of both readers and publisher.
The experience of recommending products based on user's behavior showed huge impact on the business.
Many studies were done on batch processing and showed that the bottleneck in recommendation algorithms is the search for neighbors among a large user population of potential neighbors.
This thesis proposes a framework for recommending content for news websites users in real time to increase both user and business satisfaction using xii academic and news industry standards, it starts with gathering data and ending with delivering personalized recommendations per user.
The framework used users’ articles reading interests as rating input to generate recommendations and find similar items and users.
An experiment was conducted; it was implemented and integrated with a test news website, then evaluated using industry standard tools like google analytics to track users’ insights and measure their engagement with the recommendation in two cases: active and inactive.
Results show an improvement of users engagement when the recommendation was active; average user time was increased by 39.45%, while the users’ engagement with the recommendation feature was 22.9% of the users.
Main Subjects
Information Technology and Computer Science
Topics
No. of Pages
71
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Background information.
Chapter Three : Framework discussion.
Chapter Four : Tests, results, and analysis.
Chapter Five : Conclusion and future work.
References.
American Psychological Association (APA)
Yakti, Ibrahim Muhammad. (2015). A framework for real time recommendation system for web-content websites. (Master's theses Theses and Dissertations Master). Princess Sumaya University for Technology, Jordan
https://search.emarefa.net/detail/BIM-650931
Modern Language Association (MLA)
Yakti, Ibrahim Muhammad. A framework for real time recommendation system for web-content websites. (Master's theses Theses and Dissertations Master). Princess Sumaya University for Technology. (2015).
https://search.emarefa.net/detail/BIM-650931
American Medical Association (AMA)
Yakti, Ibrahim Muhammad. (2015). A framework for real time recommendation system for web-content websites. (Master's theses Theses and Dissertations Master). Princess Sumaya University for Technology, Jordan
https://search.emarefa.net/detail/BIM-650931
Language
English
Data Type
Arab Theses
Record ID
BIM-650931
