A study and analysis of recommendation systems for location-based social network (LBSN) with big data

被引：24

作者：

Narayanan, Murale ^{[1
]}

Cherukuri, Aswani Kumar ^{[2
]}

机构：

[1] EMC Corp, India Ctr Excellence, Informat Technol, Bangalore, Karnataka, India

[2] VIT Univ, Sch Informat Technol & Engn, Vellore, Tamil Nadu, India

来源：

IIMB MANAGEMENT REVIEW | 2016年 / 28卷 / 01期

关键词：

Big data; Data mining; Recommendation system; Social network; LBSN;

D O I：

10.1016/j.iimb.2016.01.001

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

Recommender systems play an important role in our day-to-day life. A recommender system automatically suggests an item to a user that he/she might be interested in. Small-scale datasets are used to provide recommendations based on location, but in real time, the volume of data is large. We have selected Foursquare dataset to study the need for big data in recommendation systems for location-based social network (LBSN). A few quality parameters like parallel processing and multimodal interface have been selected to study the need for big data in recommender systems. This paper provides a study and analysis of quality parameters of recommendation systems for LBSN with big data. (C) 2016 Production and hosting by Elsevier Ltd on behalf of Indian Institute of Management Bangalore.

引用

页码：25 / 30

页数：6

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