Ant-based friends recommendation in social tagging systems. Issue 4 (2015)

• Record Type: Journal Article
• Authors: Bedi, Punam; Sharma, Ravish
• Is Part Of: International journal of swarm intelligence. Volume 1:Issue 4(2015)
• Page Start: 321
• Page End: 343
• Publication Date: 2015
• Subjects: social tagging systems -- ant colony metaphor -- pheromone updating -- co-occurrence graph -- deliciouscom -- friends recommendation -- user interests -- pheromone updating strategy -- trust path -- foraging behaviour -- recommender systems -- social bookmarking websites; Swarm intelligence -- Periodicals; 006.3
• Languages: English
• ISSNs: 2049-4041

Abstract

Aggregated tagging behaviour in social tagging systems provides valuable information about the interests of the users which may help in broadening their perspective and expand their network of friends. This paper proposes an ant-based friends recommendation (AbFR) approach to recommend friends to the target user. In AbFR, prominent-N tags are recommended to the target user for a specific resource using tag co-occurrence graph where weights on the edges are computed based on pheromone updating strategy known from ant algorithms. Each target user's trust graph containing friends is maintained based on implicit feedback over a period of time. Optimal trust path is computed from the combined trust graph of all the users and friends are recommended to the target user based on foraging behaviour of biological ants. Experimental study conducted with delicious.com, a social bookmarking website shows significant improvement in discovering new friends.