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1. Enhanced Elephant Herding Optimization for Large Scale Information Access on Social Media

Author

Drias, Yassine, Drias, Habiba, and Khennak, Ilyes

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Artificial Intelligence
Abstract

In this article, we present a novel information access approach inspired by the information foraging theory (IFT) and elephant herding optimization (EHO). First, we propose a model for information access on social media based on the IFT. We then elaborate an adaptation of the original EHO algorithm to apply it to the information access problem. The combination of the IFT and EHO constitutes a good opportunity to find relevant information on social media. However, when dealing with voluminous data, the performance undergoes a sharp drop. To overcome this issue, we developed an enhanced version of EHO for large scale information access. We introduce new operators to the algorithm, including territories delimitation and clan migration using clustering. To validate our work, we created a dataset of more than 1.4 million tweets, on which we carried out extensive experiments. The outcomes reveal the ability of our approach to find relevant information in an effective and efficient way. They also highlight the advantages of the improved version of EHO over the original algorithm regarding different aspects. Furthermore, we undertook a comparative study with two other metaheuristic-based information foraging approaches, namely ant colony system and particle swarm optimization. Overall, the results are very promising.

Published
2024

2. A Three-Phase Artificial Orcas Algorithm for Continuous and Discrete Problems

Author

Drias, Habiba, Bendimerad, Lydia Sonia, and Drias, Yassine

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Discrete Mathematics, Computer Science - Machine Learning
Abstract

In this paper, a new swarm intelligence algorithm based on orca behaviors is proposed for problem solving. The algorithm called artificial orca algorithm (AOA) consists of simulating the orca lifestyle and in particular the social organization, the echolocation mechanism, and some hunting techniques. The originality of the proposal is that for the first time a meta-heuristic simulates simultaneously several behaviors of just one animal species. AOA was adapted to discrete problems and applied on the maze game with four level of complexity. A bunch of substantial experiments were undertaken to set the algorithm parameters for this issue. The algorithm performance was assessed by considering the success rate, the run time, and the solution path size. Finally, for comparison purposes, the authors conducted a set of experiments on state-of-the-art evolutionary algorithms, namely ACO, BA, BSO, EHO, PSO, and WOA. The overall obtained results clearly show the superiority of AOA over the other tested algorithms.

Published
2023
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3. Fuzzy Elephant Herding Optimization and DBSCAN for Emergency Transportation: A Case Study for the 2023 Türkiye Earthquake

Author

Drias, Yassine, Drias, Habiba, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Kahraman, Cengiz, editor, Cevik Onar, Sezi, editor, Cebi, Selcuk, editor, Oztaysi, Basar, editor, Tolga, A. Cagrı, editor, and Ucal Sari, Irem, editor

Published
2024
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4. Secure Information Foraging Using Fully Homomorphic Encryption and AGNES Clustering

Author

Drias, Yassine, Drias, Habiba, Tiloult, Aya, Çakar, Tuna, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Abraham, Ajith, editor, Pllana, Sabri, editor, Hanne, Thomas, editor, and Siarry, Patrick, editor

Published
2024
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5. Quantum FP-Growth for Association Rules Mining

Author

Belkadi, Widad Hassina, Drias, Yassine, Drias, Habiba, Hameurlain, Abdelkader, Editorial Board Member, Rocha, Álvaro, Series Editor, Dubey, Ashwani Kumar, Editorial Board Member, Montenegro, Carlos, Editorial Board Member, Moreira, Fernando, Editorial Board Member, Peñalvo, Francisco, Editorial Board Member, Dzemyda, Gintautas, Editorial Board Member, Mejia-Miranda, Jezreel, Editorial Board Member, Piattini, Mário, Editorial Board Member, Ivanovíc, Mirjana, Editorial Board Member, Muñoz, Mirna, Editorial Board Member, Anwar, Sajid, Editorial Board Member, Herawan, Tutut, Editorial Board Member, Colla, Valentina, Editorial Board Member, Devedzic, Vladan, Editorial Board Member, Drias, Habiba, editor, and Yalaoui, Farouk, editor

Published
2024
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6. Quantum Recurrent Neural Networks for Soil Profiles Prediction in Türkiye

Author

Drias, Yassine, Siouane, Alaa Eddine, Çakar, Tuna, Hameurlain, Abdelkader, Editorial Board Member, Rocha, Álvaro, Series Editor, Dubey, Ashwani Kumar, Editorial Board Member, Montenegro, Carlos, Editorial Board Member, Moreira, Fernando, Editorial Board Member, Peñalvo, Francisco, Editorial Board Member, Dzemyda, Gintautas, Editorial Board Member, Mejia-Miranda, Jezreel, Editorial Board Member, Piattini, Mário, Editorial Board Member, Ivanovíc, Mirjana, Editorial Board Member, Muñoz, Mirna, Editorial Board Member, Anwar, Sajid, Editorial Board Member, Herawan, Tutut, Editorial Board Member, Colla, Valentina, Editorial Board Member, Devedzic, Vladan, Editorial Board Member, Drias, Habiba, editor, and Yalaoui, Farouk, editor

Published
2024
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11. A Data Warehouse for Spatial Soil Data Analysis and Mining: Application to the Maghreb Region

Author

Belkadi, Widad Hassina, Drias, Yassine, Drias, Habiba, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Abraham, Ajith, editor, Pllana, Sabri, editor, Casalino, Gabriella, editor, Ma, Kun, editor, and Bajaj, Anu, editor

Published
2023
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12. Multi-objective Harris Hawks Optimization for Optimal Emergency Vehicle Dispatching During a Pandemic

Author

Khennak, Ilyes, Drias, Habiba, Khelfa, Celia, Drias, Yassine, Bourouhou, Nour el Houda, Zafoune, Imene, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Abraham, Ajith, editor, Hanne, Thomas, editor, Gandhi, Niketa, editor, Manghirmalani Mishra, Pooja, editor, Bajaj, Anu, editor, and Siarry, Patrick, editor

Published
2023
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13. Slime Mould Algorithm for Solving Ambulance Dispatching Problem

Author

Khelfa, Celia, Khennak, Ilyes, Drias, Habiba, Drias, Yassine, Belharda, Yagoub, Smail, Mehrez, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Abraham, Ajith, editor, Hanne, Thomas, editor, Gandhi, Niketa, editor, Manghirmalani Mishra, Pooja, editor, Bajaj, Anu, editor, and Siarry, Patrick, editor

Published
2023
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15. Quantum Ordering Points to Identify the Clustering Structure and Application to Emergency Transportation

Author

Drias, Habiba, Drias, Yassine, Bendimerad, Lydia Sonia, Houacine, Naila Aziza, Zouache, Djaafar, Khennak, Ilyes, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Abraham, Ajith, editor, Gandhi, Niketa, editor, Hanne, Thomas, editor, Hong, Tzung-Pei, editor, Nogueira Rios, Tatiane, editor, and Ding, Weiping, editor

Published
2022
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16. Data Warehousing and Mining for Climate Change: Application to the Maghreb Region

Author

Drias, Yassine, Drias, Habiba, Khennak, Ilyes, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Abraham, Ajith, editor, Engelbrecht, Andries, editor, Scotti, Fabio, editor, Gandhi, Niketa, editor, Manghirmalani Mishra, Pooja, editor, Fortino, Giancarlo, editor, Sakalauskas, Virgilijus, editor, and Pllana, Sabri, editor

Published
2022
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17. Particle Swarm Optimization for Query Items Re-rating

Author

Khennak, Ilyes, Drias, Habiba, Drias, Yassine, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Abraham, Ajith, editor, Hanne, Thomas, editor, Castillo, Oscar, editor, Gandhi, Niketa, editor, Nogueira Rios, Tatiane, editor, and Hong, Tzung-Pei, editor

Published
2021
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18. Information Foraging on Social Media Using Elephant Herding Optimization

Author

Drias, Yassine, Drias, Habiba, Khennak, Ilyes, Bouchlaghem, Lydia, Chermat, Sihem, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Rocha, Álvaro, editor, Adeli, Hojjat, editor, Dzemyda, Gintautas, editor, Moreira, Fernando, editor, and Ramalho Correia, Ana Maria, editor

Published
2021
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19. A New Swarm Algorithm Based on Orcas Intelligence for Solving Maze Problems

Author

Drias, Habiba, Drias, Yassine, Khennak, Ilyes, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Rocha, Álvaro, editor, Adeli, Hojjat, editor, Reis, Luís Paulo, editor, Costanzo, Sandra, editor, Orovic, Irena, editor, and Moreira, Fernando, editor

Published
2020
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20. Credible Information Foraging on Social Media

Author

Drias, Yassine, Pasi, Gabriella, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Rocha, Álvaro, editor, Adeli, Hojjat, editor, Reis, Luís Paulo, editor, Costanzo, Sandra, editor, Orovic, Irena, editor, and Moreira, Fernando, editor

Published
2020
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23. A SCORPAN‐based data warehouse for digital soil mapping and association rule mining in support of sustainable agriculture and climate change analysis in the Maghreb region.

Author

Belkadi, Widad Hassina, Drias, Yassine, Drias, Habiba, Dali, Mustapha, Hamdous, Samira, Kamel, Nadjet, and Aksa, Djemai

Subjects
*DIGITAL soil mapping, *SUSTAINABLE agriculture, *ASSOCIATION rule mining, *DATA warehousing, *SUSTAINABILITY
Abstract

Sustainable agriculture is becoming increasingly important in the face of growing environmental challenges. One key aspect of sustainable agriculture is managing soil resources effectively. In this context, digital soil mapping (DSM) has emerged as a powerful tool to understand soil variability better and inform land management decisions. This paper proposes a comprehensive data warehouse for DSM that supports climate change analysis. Our architecture integrates frequent itemset mining (FMI) and association rules mining (ARM) to extract insights from large‐scale soil data. We review related studies in soil data warehousing and ARM, identify gaps, and propose a data warehouse architecture leveraging the galaxy multidimensional model for DSM based on the SCORPAN model, which incorporates all relevant soil forming factors. We employ and compare A‐priori, FP‐growth, and ECLAT algorithms to efficiently mine frequent itemsets and generate association rules. Our intensive experiments evaluation demonstrates that FP‐growth outperforms the other algorithms in accuracy, scalability, and speed and requires less memory. Additionally, we utilized correlation metrics for ARM, such as lift, cosine, kulc, and Imbalance ratio, to obtain the most significant and relevant association rules. These rules provide valuable insights into the complex relationships between soil properties and environmental factors, which can inform land management decisions and improve sustainable agriculture practices. This work contributes to the growing body of research on DSM and data‐driven approaches to sustainable agriculture. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Bees Swarm Optimization for Web Information Foraging

Author

Drias, Yassine, Kechid, Samir, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, Series editor, Tanaka, Yuzuru, Series editor, Wahlster, Wolfgang, Series editor, Siekmann, Jörg, Series editor, Prasath, Rajendra, editor, O’Reilly, Philip, editor, and Kathirvalavakumar, T., editor

Published
2014
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40. A novel Orca Cultural Algorithm and applications.

Author

Drias, Habiba, Drias, Yassine, and Khennak, Ilyes

Subjects
*KILLER whale, *EVOLUTIONARY algorithms, *ALGORITHMS, *HUNTING techniques, *ANIMAL intelligence, *SWARM intelligence
Abstract

In this article, the paradigm of machine culture as an extension to machine intelligence is introduced. This new concept is modelled based on animal intelligence and culture. The example of orca intelligence and culture is considered as orcas possess in addition to skills allowing them to reach preys, the ability to transmit their culture from generation to generation. The orca intelligence is studied and then simulated to design an algorithm called Orca Algorithm (OA). OA consists in modelling the orca lifestyle and in particular the orcas social organization, echolocation behaviour and hunting techniques. In order to integrate the cultural dimension, OA was hybridized with the Cultural Algorithm (CA) to get an algorithm called Orca Cultural Algorithm (OCA). OCA was tested on 22 benchmark problems of the literature to evaluate its performance. Extensive experiments were first performed to set the algorithm parameters prior to measure its effectiveness and efficiency. In a second stage, OCA was adapted to discrete problems and applied to the maze game with four level of complexity. Additional experiments were held to compare the designed algorithm with recent state‐of‐the‐art evolutionary algorithms. The overall obtained results are very promising. [ABSTRACT FROM AUTHOR]

Published
2023
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46. A collaborative approach to web information foraging based on multi-Agent systems

Author

Drias, Yassine, Pasi, Gabriella, Drias, Y, Pasi, G, DRIAS, YASSINE, Drias, Yassine, Pasi, Gabriella, Drias, Y, Pasi, G, and DRIAS, YASSINE

Abstract

In this paper the task of Information Foraging (IF) is considered as a useful paradigm to address Exploratory Search. In the context of IF, aWeb navigation strategy is introduced and formalized, and a multiagent based model is proposed to exploit a collaborative approach to Information Foraging. A system based on this model has been developed, and its evaluations on the ACM and DBLP repositories are reported. Two datasets with different sizes were considered to show the effectiveness and the efficiency of the developed system. Furthermore, comparative evaluations were conducted in order to compare our approach with classical information access approaches. The results are promising and show the ability of the proposedWeb Information Foraging system to find relevant Web pages in a very short time.

Published
2017

47. Enhanced Elephant Herding Optimization for Large Scale Information Access on Social Media.

Author

Drias, Yassine, Drias, Habiba, and Khennak, Ilyes

Subjects
SOCIAL media, ACCESS to information, INFORMATION foraging theory, PARTICLE swarm optimization, K-means clustering
Abstract

In this article, we present a novel information access approach inspired by the information foraging theory (IFT) and elephant herding optimization (EHO). First, we propose a model for information access on social media based on the IFT. We then elaborate an adaptation of the original EHO algorithm to apply it to the information access problem. The combination of the IFT and EHO constitutes a good opportunity to find relevant information on social media. However, when dealing with voluminous data, the performance undergoes a sharp drop. To overcome this issue, we developed an enhanced version of EHO for large scale information access. We introduce new operators to the algorithm, including territories delimitation and clan migration using clustering. To validate our work, we created a dataset of more than 1.4 million tweets, on which we carried out extensive experiments. The outcomes reveal the ability of our approach to find relevant information in an effective and efficient way. They also highlight the advantages of the improved version of EHO over the original algorithm regarding different aspects. Furthermore, we undertook a comparative study with two other metaheuristic-based information foraging approaches, namely ant colony system and particle swarm optimization. Overall, the results are very promising. [ABSTRACT FROM AUTHOR]

Published
2022

48. A Three-Phase Artificial Orcas Algorithm for Continuous and Discrete Problems

Author

Drias, Habiba, Bendimerad, Lydia, and Drias, Yassine

Abstract

In this paper, a new swarm intelligence algorithm based on orca behaviors is proposed for problem solving. The algorithm called artificial orca algorithm (AOA) consists of simulating the orca lifestyle and in particular the social organization, the echolocation mechanism, and some hunting techniques. The originality of the proposal is that for the first time a meta-heuristic simulates simultaneously several behaviors of just one animal species. AOA was adapted to discrete problems and applied on the maze game with four level of complexity. A bunch of substantial experiments were undertaken to set the algorithm parameters for this issue. The algorithm performance was assessed by considering the success rate, the run time, and the solution path size. Finally, for comparison purposes, the authors conducted a set of experiments on state-of-the-art evolutionary algorithms, namely ACO, BA, BSO, EHO, PSO, and WOA. The overall obtained results clearly show the superiority of AOA over the other tested algorithms.

Published
2021
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49. Web information foraging using Multi-agent System

Author

DRIAS, YASSINE, Drias, Y, and PASI, GABRIELLA

Subjects
Social media, Swarm Intelligence, Multi-agent system, Game Theory, Sistemi multi-agente, INF/01 - INFORMATICA, Web information fora, Teoria del gioco, Information Acce
Abstract

Lo scopo principale dei motori di ricerca, che supportano il compito di information retrieval, è quello di fornire agli utenti un metodo facile per trovare informazioni sul Web. Nonostante i loro vantaggi, i motori di ricerca hanno ancora numerosi limiti. Sono state realizzate diverse opere per migliorare i sistemi di accesso alle informazioni e offrire un'esperienza di utilizzo migliore in settori diversi, come distribuite e contestuali information retrieval, link analysis e exploratory search. Questa tesi si occupa di Web Information Foraging, un paradigma di information access più recente che mira a scoprire i percorsi che portano a informazioni rilevanti sul Web. L'obiettivo principale della ricerca intrapresa durante il Ph.D. è stato quello di progettare e implementare sistemi efficaci ed efficienti di Information Foraging basati sulla tecnologia multi-agent. A questo scopo, abbiamo studiato information foraging in diversi domini, tra cui salute, pubblicazioni scientifiche e social media. Per affrontare questo problema, abbiamo proposto un'architettura modulare con due fasi importanti per il sistema di Information Foraging. La prima fase è un processo di apprendimento che mira a localizzare le pagine Web più rilevanti che potrebbero interessare l'utente secondo i propri interessi. Questo può essere eseguito su un'istanza fissa del Web. La seconda fase tiene conto dell'apertura e della dinamicità del Web e consiste in un apprendimento incrementale partendo dai risultati della prima fase e ricondizionando i risultati tenendo conto delle modifiche apportate sul Web. L'intero sistema offre uno strumento per aiutare gli utenti a accedere facilmente alle informazioni online. Lo sviluppo del sistema ha attraversato tre importanti passaggi in cui sono stati utilizzati diversi concetti e tecnologie per ottenere efficacia ed efficienza e anche rendere il sistema in grado di operare in diversi ambienti. Innanzitutto, abbiamo proposto un approccio basato sulla Swarm Intelligence per simulare il processo di foraggicazione come descritto nella Information Foraging Theory. Abbiamo eseguito la nostra proposta utilizzando Bee Swarm Optimization (BSO) per realizzare un processo automatico di information foraging fondato sul comportamento del foraggicazione delle informazioni dell'uomo. Conoscendo che BSO è un approccio di swarm intelligence che coinvolge agenti reattivi e che il concetto di Information Foraging si basa sulla natura, abbiamo pensato che questo potrebbe essere uno dei modi più appropriati per affrontare il problema del Web Information Foraging. Per convalidare la nostra proposta, sono stati condotti esperimenti su MedlinePlus, un sito dedicato al dominio medico e che contiene informazioni su oltre 1000 malattie e condizioni sanitarie. I risultati sono stati promettenti e hanno dimostrato la capacità di Information Foraging di accedere alle informazioni pertinenti sul Web in base agli interessi di un utente. The main purpose of search engines, which support the task of Information Retrieval, is to provide the users with an easy method to find information on the Web. Despite their advantages, Web search engines still have numerous limitations. Several works have been done to enhance information access systems and offer a better user experience in different fields such as distributed and contextual information retrieval, link analysis and exploratory search. This thesis deals with Web Information Foraging, which is a recent information access paradigm that aims at discovering paths leading to relevant information on the Web. The principal goal of the research undertaken during the Ph.D. has been to design and implement effective and efficient Information Foraging systems based on multi-agent technology. For this purpose, we investigated Information Foraging in different domains including health, scientific publications and social media. To address this issue, we proposed a modular architecture with two important phases for the Information Foraging system to be developed. The first phase is a learning process, which aims to locate the most relevant Web pages that might interest the user according to his/her interests. This can be performed on a fixed instance of the Web. The second phase takes into account the openness and dynamicity of the Web and it consists of an incremental learning starting from the results of the first phase and reshaping the outcomes taking into account the changes that occur on the Web. The whole system offers a tool to help users access information online easily. The development of the system went through three important steps, where different concepts and technologies were used in order to achieve both effectiveness and efficiency and also to make the system able to operate on various environments.

Published
2017

50. Web information foraging using Multi-agent System

Author

Drias, Y, PASI, GABRIELLA, DRIAS, YASSINE, Drias, Y, PASI, GABRIELLA, and DRIAS, YASSINE

Abstract

Lo scopo principale dei motori di ricerca, che supportano il compito di information retrieval, è quello di fornire agli utenti un metodo facile per trovare informazioni sul Web. Nonostante i loro vantaggi, i motori di ricerca hanno ancora numerosi limiti. Sono state realizzate diverse opere per migliorare i sistemi di accesso alle informazioni e offrire un'esperienza di utilizzo migliore in settori diversi, come distribuite e contestuali information retrieval, link analysis e exploratory search. Questa tesi si occupa di Web Information Foraging, un paradigma di information access più recente che mira a scoprire i percorsi che portano a informazioni rilevanti sul Web. L'obiettivo principale della ricerca intrapresa durante il Ph.D. è stato quello di progettare e implementare sistemi efficaci ed efficienti di Information Foraging basati sulla tecnologia multi-agent. A questo scopo, abbiamo studiato information foraging in diversi domini, tra cui salute, pubblicazioni scientifiche e social media. Per affrontare questo problema, abbiamo proposto un'architettura modulare con due fasi importanti per il sistema di Information Foraging. La prima fase è un processo di apprendimento che mira a localizzare le pagine Web più rilevanti che potrebbero interessare l'utente secondo i propri interessi. Questo può essere eseguito su un'istanza fissa del Web. La seconda fase tiene conto dell'apertura e della dinamicità del Web e consiste in un apprendimento incrementale partendo dai risultati della prima fase e ricondizionando i risultati tenendo conto delle modifiche apportate sul Web. L'intero sistema offre uno strumento per aiutare gli utenti a accedere facilmente alle informazioni online. Lo sviluppo del sistema ha attraversato tre importanti passaggi in cui sono stati utilizzati diversi concetti e tecnologie per ottenere efficacia ed efficienza e anche rendere il sistema in grado di operare in diversi ambienti. Innanzitutto, abbiamo proposto un approccio basato sulla Swarm, The main purpose of search engines, which support the task of Information Retrieval, is to provide the users with an easy method to find information on the Web. Despite their advantages, Web search engines still have numerous limitations. Several works have been done to enhance information access systems and offer a better user experience in different fields such as distributed and contextual information retrieval, link analysis and exploratory search. This thesis deals with Web Information Foraging, which is a recent information access paradigm that aims at discovering paths leading to relevant information on the Web. The principal goal of the research undertaken during the Ph.D. has been to design and implement effective and efficient Information Foraging systems based on multi-agent technology. For this purpose, we investigated Information Foraging in different domains including health, scientific publications and social media. To address this issue, we proposed a modular architecture with two important phases for the Information Foraging system to be developed. The first phase is a learning process, which aims to locate the most relevant Web pages that might interest the user according to his/her interests. This can be performed on a fixed instance of the Web. The second phase takes into account the openness and dynamicity of the Web and it consists of an incremental learning starting from the results of the first phase and reshaping the outcomes taking into account the changes that occur on the Web. The whole system offers a tool to help users access information online easily. The development of the system went through three important steps, where different concepts and technologies were used in order to achieve both effectiveness and efficiency and also to make the system able to operate on various environments.

Published
2017

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