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