Developing a framework that utilizes intelligent agents to extract multi-lingual web news

Author

Al-Daraiseh, Ahmad ; Haddoush, Wafa

Author_Institution

Comput. Inf. Syst., King Saud Univ., Riyadh, Saudi Arabia

fYear

2015

Firstpage

1

Lastpage

5

Abstract

This paper proposes a framework for personalized news application that utilizes intelligent agents to aggregate specific articles from web news based on users´ preferences. It shows how to extract web news stories in Arabic language, in particular, in addition to English language. Intelligent agents learn user´s interests by exploiting data gathered from social media, web browsing history and also explicit and implicit feedback from the user. To suit the various facets of the user´s interests, the system adopt multiagent with different genres. Each agent covers a particular task to fulfil the desired functionality of the framework.

Keywords

Internet; data handling; information retrieval; learning (artificial intelligence); multi-agent systems; natural language processing; social networking (online); Arabic language; English language; Web browsing history; data gathering; explicit feedback; implicit feedback; intelligent agent utilization; machine learning; multilingual Web news stories extraction; personalized news application; social media; user interest learning; Data mining; Feature extraction; History; Intelligent agents; Internet; Media; Monitoring; bi-lingual; intelligent agent; machine learning; personalized news;

fLanguage

English

Publisher

ieee

Conference_Titel

Web Applications and Networking (WSWAN), 2015 2nd World Symposium on

Conference_Location

Sousse

Print_ISBN

978-1-4799-8171-7

Type

conf

DOI

10.1109/WSWAN.2015.7210335

Filename

7210335