Title :
Personalized versus non-personalized tag recommendation: A suitability study on three social networks
Author :
Uddin, Muhammad Moeen ; Hassan, Malik Tahir ; Karim, Asim
Author_Institution :
Dept. of Comput. Sci., Lahore Univ. of Manage. Sci., Lahore, Pakistan
Abstract :
Tag recommendation systems are either personalized or non-personalized. Personalized tag recommendation utilizes a user´s tagging behavior from her tagging history for predictions. Whereas non-personalized recommendation systems recommend what is popular and relevant to the user. In this study, we have analyzed the role of personal tagging history in recommending tags. The experiments are done on three folksonomy datasets: Delicious, Flickr and Bibsonomy. Important results for three popular tag recommendation algorithms: PITF, FolkRank and Adapted PageRank are reported in terms of prediction quality. It is found that users´ history usage preferences change across all data sets; hence overall prediction quality of personalized recommendation system may suffer. We discover a generic life cycle of folksonomy users on the basis of their history usage. We propose this life cycle can be used to improve an overall prediction performance of a recommendation system across all folksonomies.
Keywords :
recommender systems; social networking (online); user interfaces; Adapted PageRank algorithm; Bibsonomy dataset; Delicious dataset; Flickr dataset; FolkRank algorithm; PITF algorithm; history usage; nonpersonalized tag recommendation; personalized tag recommendation; social networks; tag recommendation system; usage preference; user tagging behavior; Adaptation models; Lead; Prediction algorithms; Folksonomy; Personalization; Tag Recommendation;
Conference_Titel :
Multitopic Conference (INMIC), 2011 IEEE 14th International
Conference_Location :
Karachi
Print_ISBN :
978-1-4577-0654-7
DOI :
10.1109/INMIC.2011.6151510