In this paper, a new Information Foraging approach based on Elephant Herding Optimization (EHO) is proposed and tested on social media. We adapted the original EHO algorithm and combined it with the information foraging theory. In order to test our approach, we constructed a dataset containing more than one million tweets collected during the second semester of 2020. The results are very satisfying and show the ability of our approach to improve the information foraging process both in terms of relevance and response time. To further evaluate our system, we held a comparative study with another well-known metaheuristic applied to information foraging, namely Ant Colony Optimization. The outcomes show the superiority of our proposal.
Drias, Y., Drias, H., Khennak, I., Bouchlaghem, L., Chermat, S. (2021). Information Foraging on Social Media Using Elephant Herding Optimization. In Trends and Applications in Information Systems and Technologies Volume 2 (pp.304-314). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-72651-5_30].
Information Foraging on Social Media Using Elephant Herding Optimization
Drias Y.
;
2021
Abstract
In this paper, a new Information Foraging approach based on Elephant Herding Optimization (EHO) is proposed and tested on social media. We adapted the original EHO algorithm and combined it with the information foraging theory. In order to test our approach, we constructed a dataset containing more than one million tweets collected during the second semester of 2020. The results are very satisfying and show the ability of our approach to improve the information foraging process both in terms of relevance and response time. To further evaluate our system, we held a comparative study with another well-known metaheuristic applied to information foraging, namely Ant Colony Optimization. The outcomes show the superiority of our proposal.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
