Web feeds recommending system based on social data

Diego  Oliveira Rodrigues; Sagar Gurung; Mihaela Cocea

Web feeds recommending system based on social data

Diego Oliveira Rodrigues, Sagar Gurung, Mihaela Cocea

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

60 Downloads (Pure)

Abstract

Staying up to date with an individual's interests is a daunting task. An unstoppable number of growing online resources such as websites, blogs and news portals are providing information on various subjects and topics and it is provoking certain difficulties on individuals to identify the best resources or providers in order to trust and follow them continuously. Even though, some trustworthy useful sources have been identified, individuals are still losing them due to lack of management, not bookmarking the sites, carelessness, and so on. The proposed system in this paper will help internet users to figure out an approach to identify and recommend web feeders based on the social data collected from social channels like Facebook. It aims to provide a common place for internet users to read updates of their interest without having to perform search queries. It will also explain about the techniques used to filter data to generate recommended web feeds for users.

Original language	English
Title of host publication	ENCOINFO — congresso de computação e sistemas de informação
Publication status	Published - Oct 2015
Event	2015 Congress of Computing and Information Systems - , United Kingdom Duration: 19 Oct 2015 → 22 Oct 2015

Publication series

Name	ENCOINFO
ISSN (Print)	2447-0767

Conference

Conference	2015 Congress of Computing and Information Systems
Abbreviated title	ENCOINFO
Country/Territory	United Kingdom
Period	19/10/15 → 22/10/15

Keywords

Recommender Systems
Web feeds
collaborative filtering

Access to Document

Encoinfo2015

http://ulbra-to.br/encoinfo/index.php/encoinfo/encoinfo2015

Cite this

@inproceedings{5be5c397bf784fc5930fdd039c73cb31,

title = "Web feeds recommending system based on social data",

abstract = "Staying up to date with an individual's interests is a daunting task. An unstoppable number of growing online resources such as websites, blogs and news portals are providing information on various subjects and topics and it is provoking certain difficulties on individuals to identify the best resources or providers in order to trust and follow them continuously. Even though, some trustworthy useful sources have been identified, individuals are still losing them due to lack of management, not bookmarking the sites, carelessness, and so on. The proposed system in this paper will help internet users to figure out an approach to identify and recommend web feeders based on the social data collected from social channels like Facebook. It aims to provide a common place for internet users to read updates of their interest without having to perform search queries. It will also explain about the techniques used to filter data to generate recommended web feeds for users.",

keywords = "Recommender Systems, Web feeds, collaborative filtering",

author = "{Oliveira Rodrigues}, Diego and Sagar Gurung and Mihaela Cocea",

year = "2015",

month = oct,

language = "English",

series = "ENCOINFO",

booktitle = "ENCOINFO — congresso de computa{\c c}{\~a}o e sistemas de informa{\c c}{\~a}o",

note = "2015 Congress of Computing and Information Systems, ENCOINFO ; Conference date: 19-10-2015 Through 22-10-2015",

}

TY - GEN

T1 - Web feeds recommending system based on social data

AU - Oliveira Rodrigues, Diego

AU - Gurung, Sagar

AU - Cocea, Mihaela

PY - 2015/10

Y1 - 2015/10

N2 - Staying up to date with an individual's interests is a daunting task. An unstoppable number of growing online resources such as websites, blogs and news portals are providing information on various subjects and topics and it is provoking certain difficulties on individuals to identify the best resources or providers in order to trust and follow them continuously. Even though, some trustworthy useful sources have been identified, individuals are still losing them due to lack of management, not bookmarking the sites, carelessness, and so on. The proposed system in this paper will help internet users to figure out an approach to identify and recommend web feeders based on the social data collected from social channels like Facebook. It aims to provide a common place for internet users to read updates of their interest without having to perform search queries. It will also explain about the techniques used to filter data to generate recommended web feeds for users.

AB - Staying up to date with an individual's interests is a daunting task. An unstoppable number of growing online resources such as websites, blogs and news portals are providing information on various subjects and topics and it is provoking certain difficulties on individuals to identify the best resources or providers in order to trust and follow them continuously. Even though, some trustworthy useful sources have been identified, individuals are still losing them due to lack of management, not bookmarking the sites, carelessness, and so on. The proposed system in this paper will help internet users to figure out an approach to identify and recommend web feeders based on the social data collected from social channels like Facebook. It aims to provide a common place for internet users to read updates of their interest without having to perform search queries. It will also explain about the techniques used to filter data to generate recommended web feeds for users.

KW - Recommender Systems

KW - Web feeds

KW - collaborative filtering

M3 - Conference contribution

T3 - ENCOINFO

BT - ENCOINFO — congresso de computação e sistemas de informação

T2 - 2015 Congress of Computing and Information Systems

Y2 - 19 October 2015 through 22 October 2015

ER -

Web feeds recommending system based on social data

Abstract

Publication series

Conference

Keywords

Access to Document

Fingerprint

Cite this