Enhancing news recommendation using a personalized content manager

The surge in the amount of information available on the internet and the number of users utilizing such information poses new challenges for information systems. This rapid growth in information is palpable in the news provisioning domain where users spend time deciding which of the many channels pr...

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Main Author: Okojie, Charles
Other Authors: Informaatioteknologian tiedekunta, Faculty of Information Technology, Information Technology, Informaatioteknologia, University of Jyväskylä, Jyväskylän yliopisto
Format: Master's thesis
Language:eng
Published: 2018
Subjects:
Online Access: https://jyx.jyu.fi/handle/123456789/57311
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author Okojie, Charles
author2 Informaatioteknologian tiedekunta Faculty of Information Technology Information Technology Informaatioteknologia University of Jyväskylä Jyväskylän yliopisto
author_facet Okojie, Charles Informaatioteknologian tiedekunta Faculty of Information Technology Information Technology Informaatioteknologia University of Jyväskylä Jyväskylän yliopisto Okojie, Charles Informaatioteknologian tiedekunta Faculty of Information Technology Information Technology Informaatioteknologia University of Jyväskylä Jyväskylän yliopisto
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description The surge in the amount of information available on the internet and the number of users utilizing such information poses new challenges for information systems. This rapid growth in information is palpable in the news provisioning domain where users spend time deciding which of the many channels provides news in a most reliable and useful fashion. In the last few years, News aggregation platforms are now present which reduces the time users spends in consuming news from multiple sources. But news provisioning is more than just aggregating and presenting news. It must also include taking into cognizance users’ needs. Therefore, recommendation algorithms are developed by information systems and news contents are recommended and personalized for users while utilizing user’s specific data. If content recommendation is to be optimal, better and more efficient algorithms must be developed and implemented. Challenges associated with this type information systems include providing quality and novel information, feeding out relevant information while dealing with problems such as ‘data-sparsity’ commonly associated with recommending content. To this end I conduct a study which employs a hybrid approach to solving the existing problems with recommendation system and providing quality, relevant and serendipitous news content for users.
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spellingShingle Okojie, Charles Enhancing news recommendation using a personalized content manager IBM Watson Information services Web Scraping Tietotekniikka Mathematical Information Technology 602 uutiset suosittelujärjestelmät personointi tietojärjestelmät
title Enhancing news recommendation using a personalized content manager
title_full Enhancing news recommendation using a personalized content manager
title_fullStr Enhancing news recommendation using a personalized content manager Enhancing news recommendation using a personalized content manager
title_full_unstemmed Enhancing news recommendation using a personalized content manager Enhancing news recommendation using a personalized content manager
title_short Enhancing news recommendation using a personalized content manager
title_sort enhancing news recommendation using a personalized content manager
title_txtP Enhancing news recommendation using a personalized content manager
topic IBM Watson Information services Web Scraping Tietotekniikka Mathematical Information Technology 602 uutiset suosittelujärjestelmät personointi tietojärjestelmät
topic_facet 602 IBM Watson Information services Mathematical Information Technology Tietotekniikka Web Scraping personointi suosittelujärjestelmät tietojärjestelmät uutiset
url https://jyx.jyu.fi/handle/123456789/57311 http://www.urn.fi/URN:NBN:fi:jyu-201803131716
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