Paper Info
Title
Twitter's Experts Recommendation System Based on User Content.
Abstract
The Internet provides users with an overwhelming amount of information. For this reason they may not always be able to find the information they are looking for. Recommendation systems help users locate useful information and save time. Twitter is one of the social networks that implements this type of system in order to help its users in searching content. However, the traditional recommendation system implemented by Twitter only considers people from the user's surroundings or it suggests the followees/followers of the user's followees. Many use Twitter as a source of information, it is therefore necessary to create a recommendation system that would suggest experts profiles to other users. Experts must be capable of providing interesting information to users. The "expert" recommended to a users will be chosen on the basis of the content they publish and whether this content is of interest to the user. The proposed system offers accurate and suitable recommendations.
Year
DOI
Venue
2018
10.1007/978-3-319-99608-0_28
DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
Content-based recommendation,Information retrieval,Recommendation system,Text mining,Twitter,Web mining
Recommender system,Publication,World Wide Web,Social network,Web mining,Computer science,Distributed computing,The Internet
Conference
Volume
ISSN
Citations 
801
2194-5357
0
PageRank 
References 
Authors
0.34
5
3
Name
Order
Citations
PageRank
Diego M. Jiménez-Bravo111.37
Juan Francisco de Paz239552.24
Gabriel Villarrubia318324.85