Show simple item record

Consultant
dc.contributor.advisor
Benczúr, András
Author
dc.contributor.author
Ayala Gómez, Frederick 
Availability Date
dc.date.accessioned
2019-10-02T08:45:48Z
Availability Date
dc.date.available
2019-10-02T08:45:48Z
Release
dc.date.issued
2019
Language
dc.language
angolhu_HU
Title
dc.title
Context- Aware Recommendations for Groups in Location- Based Social Networks and Academic Social Networkshu_HU
Language
dc.language.rfc3066
eng
Language
dc.language.rfc3066
eng
Rights
dc.rights.holder
A doktori disszertációk szerzői jogvédelem alatt állnak, csak a szerzői jogok maradéktalan tiszteletben tartásával használhatók.hu_HU
Abstract in English
dc.description.abstracteng
The impact of the World Wide Web goes beyond communicating between computers. The web changed the way we interact with organizations, people, documents, and data. Social media is one of the new buzzwords of the web. It is a comparatively new term that covers a wide range of online applications, platforms, and media that support online interactions, collaboration, and the sharing of content. It includes all that constitutes human interaction in online platforms. Social media has had grown explosively in a short time and has a profound impact on advertising, publicity, marketing, public opinion, entertainment, software services, and decision-making. The content offered in social networks is exciting to users. However, it is challenging, as users need to spend time and effort finding content that might be of their interest. Navigating such an extensive collection of items becomes difficult if there are no tools to help the users. To overcome this problem, social media relies on data mining solutions such as recommender systems and information retrieval systems. In particular, recommender systems have found applications in many domains including movies, music, videos, news, books, and products in general. Depending on the context they produce a list of recommended items using a variety of techniques. The goal of this dissertation is to research new approaches in recommender systems that help to satisfy the needs of users in social media. Specifically, we examine the role of recommender systems for users in two types of social media, Location-Based Social Networks and academic social networks. LBSNs enable their users to share the places they go to and with whom they are. Academic social networks help modern researchers organize their scientific libraries and discover relevant papers to their research. For both types of social media most of the existing work focuses on recommendations for individual users. The proposed approaches are distinguishable from others in that we focus on providing recommendations to a group of users, rather than to individuals. Moreover, we investigate the importance of item-to-item recommendations and propose a new method for recommending on infrequent items.hu_HU
Name of Committee Member (a title, degree)
dc.description.commemb
Lendák Imre (egyetemi docens, PhD)hu_HU
Name of Committee Member (a title, degree)
dc.description.commemb
Farkas Richárd (adjunktus, PhD)hu_HU
Name of Committee Member (a title, degree)
dc.description.commemb
Micsik András (tudományos főmunkatárs, PhD)hu_HU
Name of Committee Member (a title, degree)
dc.description.commemb
Laki Sándor (adjunktus, Phd)hu_HU
Official reviewer (a title, degree)
dc.description.reviewer
Jelasity Márk (tanszékvezető egyetemi tanár, PhD, dr. habil.)hu_HU
Official reviewer (a title, degree)
dc.description.reviewer
Horváth Tamás (tanszékvezető egyetemi docens, PhD)hu_HU
Scope
dc.format.page
103hu_HU
Doi ID
dc.identifier.doi
10.15476/ELTE.2019.018
MTMT ID
dc.identifier.mtmt
30827355
Opac ID
dc.identifier.opac
http://opac.elte.hu/F?func=direct&doc_number=975832
Language
dc.language.other
angolhu_HU
Discipline Discipline +
dc.subject.discipline
Műszaki tudományok/Informatikai tudományokhu_HU
Keyword English
dc.subject.en
Group Recommendationshu_HU
Keyword English
dc.subject.en
POI Itinerary Recommendationshu_HU
Keyword English
dc.subject.en
Location-Based Social Networkshu_HU
Keyword English
dc.subject.en
Recommender Systemshu_HU
Keyword English
dc.subject.en
Citation recommendationshu_HU
Keyword English
dc.subject.en
Knowledge Graphshu_HU
Graduate schools / programs
dc.subject.prog
Informatika D. I./Az informatika alapjai és módszerei.hu_HU
Class
dc.type.genre
phdhu_HU
Type
dc.type.resrep
Tudományoshu_HU
Author
dc.contributor.inst
ELTE IK PHD/Informatika D. I.hu_HU
Goalkeeping Day
dc.date.defended
2019-05-07
Keywords
dc.subject.hu
Knowledge Graphshu_HU
Keywords
dc.subject.hu
Citation recommendationshu_HU
Keywords
dc.subject.hu
Recommender Systemshu_HU
Keywords
dc.subject.hu
Location-Based Social Networkshu_HU
Keywords
dc.subject.hu
POI Itinerary Recommendationshu_HU
Keywords
dc.subject.hu
Group Recommendationshu_HU
Chairman of the Evaluation Committee (a title, degree)
dc.description.compres
Horváth Zoltán (tanszékvezető egyetemi tanár, PhD, dr. habil.)hu_HU
Resolution dated
dc.date.decreedate
2019-09-26
date of submission
dc.date.presented
2019-02-28


Files in this item

Context- Aware Recommendations for Groups in Location- Based Social Networks and Academic Social Networks
Context- Aware Recommendations for Groups in Location- Based Social Networks and Academic Social Networks
 

This item appears in the following Collection(s)

Show simple item record