DocumentCode :
162704
Title :
Measuring similarity between user profile and library book
Author :
Shirude, Snehalata Bhikanrao ; Kolhe, Satish Ramesh
Author_Institution :
Sch. of Comput. Sci., North Maharashtra Univ., Jalgaon, India
fYear :
2014
fDate :
1-2 March 2014
Firstpage :
50
Lastpage :
54
Abstract :
In the development of recommender system either the content or collaborative filtering is necessary. To filter the records it is required to measure the similarity between profile of user and items present in the dataset. This experiment is performed on the dataset containing 978 books related to computer science field and 7 users. Similarity between profile of user and contents of book is measured using Euclidean, Manhattan, Minkowski, Cosine distances. The results are evaluated and compared. This work is useful in the development of library recommender system.
Keywords :
collaborative filtering; library automation; recommender systems; Cosine distances; Euclidean distances; Manhattan distances; Minkowski distances; collaborative filtering; computer science field; content filtering; library book; library recommender system; record filtering; similarity measurement; user profile; Books; Educational institutions; Euclidean distance; Libraries; Recommender systems; Taxonomy; Cosine distance; Euclidean distance; Manhattan distance; Minkowski distance; Recommender System; collaborative filtering; content filtering; measuring similarity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Systems and Computer Networks (ISCON), 2014 International Conference on
Conference_Location :
Mathura
Print_ISBN :
978-1-4799-2980-1
Type :
conf
DOI :
10.1109/ICISCON.2014.6965217
Filename :
6965217
Link To Document :
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