scholarly journals Retrieving Arabic Textual Documents Based on Queries Written in Bahraini Slang Language

2019 ◽  
Vol 13 (6) ◽  
pp. 44
Author(s):  
Ayat Amin Al-Jarrah ◽  
Ghassan Kanaan ◽  
Mustafa Abdel-Kareem Ababneh
Keyword(s):  
Information Retrieval ◽  
Social Communication ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Colloquial Language ◽  
The Social ◽  
Classical Language ◽  
F Measure

Nowadays, the most used language is the colloquial language not the classical language. It is widely used in many nations. The kingdom of Bahrain had the largest share in the spread of the colloquial language, which becomes the trader's language and the language of the social communication too. It became so popular that its usage starts dominating the daily conversations. In this research, we will create algorithm to enhance the process of information retrieval in Arabic slang language of the Gulf. In this algorithm, we put some special Bahraini rules to convert queries from Slang Bahraini to a classical language. In addition, we will apply this algorithm on the Bahraini colloquial language. After making an evaluation for the system relying on the results of three main aspects recall, precision, and F-measure, we noticed that the results of precision about 0.64 for both researches slang and classical, which gives a great indication that the system supports searching in Bahraini slang language. The purpose of this research is to improve the Information Retrieval system field. In addition, it will save the time and the effort of the researchers of the Bahraini colloquial language.

Social Networks Discovery Based on Information Retrieval Technologies and Bees Swarm Optimization

2016 ◽  
pp. 821-840
Author(s):  
Yassine Drias ◽  
Habiba Drias
Keyword(s):  
Social Networks ◽  
Information Retrieval ◽  
Retrieval System ◽  
Optimization Method ◽  
Information Retrieval System ◽  
Swarm Optimization ◽  
Large Graphs ◽  
Social Community ◽  
The Social ◽  
The Given

Unlike the previous works where detecting communities is performed on large graphs, our approach considers textual documents for discovering potential social networks. More precisely, the aim of this paper is to extract social communities from a collection of documents and a query specifying the domain of interest that may link the group. We propose a methodology that develops an information retrieval system capable to generate the documents that are in relationship with any topic. The authors of these documents are linked together to constitute the social community around the given thematic. The search process in the information retrieval system is designed using BSO, the bee swarm optimization method in order to optimize the retrieval time for large amount of documents. Our approach was implemented and tested on CACM and DBLP and the time of building a social network is quasi instant.

Social Networks Discovery Based on Information Retrieval Technologies and Bees Swarm Optimization

2014 ◽  
Vol 4 (3) ◽  
pp. 46-65
Author(s):  
Yassine Drias ◽  
Habiba Drias
Keyword(s):  
Social Networks ◽  
Information Retrieval ◽  
Retrieval System ◽  
Optimization Method ◽  
Information Retrieval System ◽  
Swarm Optimization ◽  
Large Graphs ◽  
Social Community ◽  
The Social ◽  
The Given

Unlike the previous works where detecting communities is performed on large graphs, our approach considers textual documents for discovering potential social networks. More precisely, the aim of this paper is to extract social communities from a collection of documents and a query specifying the domain of interest that may link the group. We propose a methodology that develops an information retrieval system capable to generate the documents that are in relationship with any topic. The authors of these documents are linked together to constitute the social community around the given thematic. The search process in the information retrieval system is designed using BSO, the bee swarm optimization method in order to optimize the retrieval time for large amount of documents. Our approach was implemented and tested on CACM and DBLP and the time of building a social network is quasi instant.

Adaptive information retrieval system applied to digital libraries

2006 ◽  
Author(s):  
Roberto Willrich ◽  
Rafael de Moura Speroni ◽  
Christopher Viana Lima ◽  
André Luiz de Oliveira Diaz ◽  
Sérgio Murilo Penedo
Keyword(s):  
Information Retrieval ◽  
Digital Libraries ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Adaptive Information Retrieval

Open System for Indexing and Retrieving Multimedia Information

2013 ◽  
Author(s):  
Hanene Maghrebi ◽  
Amos David
Keyword(s):  
Information Retrieval ◽  
Multimedia Information ◽  
Open System ◽  
Large Volume ◽  
Retrieval System ◽  
Main Idea ◽  
Relevant Information ◽  
Information Retrieval System ◽  
Multimedia Content ◽  
Nous Proposons

Managing the increasing growth of multimedia content still poses some problems. The challenge is to propose relevant information to the users among the large volume of information available. The main idea that drives our approach is to provide an open information retrieval system, which can adapt its results to several…La gestion de l’information multimédia soulève encore quelques problèmes. Le défi est de pouvoir proposer à l’utilisateur des informations pertinentes parmi la quantité d’information qui ne cesse de s’accroître. Dans cette lignée, nous proposons un système ouvert de recherche d’information capable d’adapter ses résultats aux différents… 

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