A Survey - Approaches and Challenges for Cloud Based Recommendation System

Authors(2) :-Sindhu J, Roopa G M

Today there is a big variety of different approaches and algorithms of recommendation systems. Recommender System is an expedient software tool that is integrated with the e-Commerce business applications for effective information access. It provides suggestions by filtering the information from this availability of information, such that the users meet their needs and interest. Till now different approaches and techniques have been proposed and implemented to provide accurate recommendations to user. But still there exists some gaps to provide effective recommendations to users. In this paper we describe the recommendation system related research and then introduce various techniques, methods, and approaches used by the recommender system. Also we describe the challenges and drawbacks of the existing recommendation system.

Authors and Affiliations

Sindhu J
Department of Computer Science and Engineering Bapuji Institute of Engineering and Technology, Davanagere, Karnataka, India
Roopa G M
Department of Computer Science and Engineering Bapuji Institute of Engineering and Technology, Davanagere, Karnataka, India

Recommendation system, Content based algorithm, Collaborative Filtering Approach, Content Based Filtering Approach, Hybrid Approach, Cold Start, Data Sparseness and Scalability, Context-Aware Web Services, Multi-objective Optimization

  1. Yarona Kanza,Hanan Samet,"An online Marketplace for Geosocial Data"international conference on advances in Geographic Information Systems,2015.
  2. JayashreeM,somwanshi,prof,Y.B.Gurav,"Clud-based mobile multimedia recommendation system with user behaviour information"International journal of innovative research in computer and communication engineering,2014.
  3. P. G. Campos,F. Díez,I. Cantador,"Time-aware Recommender Systems: A Comprehensive Survey and Analysis of ExistingEvaluationProtocols,"User Modeling and User-Adapted Interaction,vol. 24,no.1-2,pp. 67-119,2014.
  4. A.Majid,L.Chen,G.Chen,H.Turab,I.Hussain,and J. Woodward,"A Context-aware Personalized Travel Recommendation System based on Geo-tagged Social Media Data Mining,"InternationalJournalof Geographical Information Science,pp. 662-684,2013.
  5. B. Hidasi,and D. Tikk,"Initializing Matrix Factorization Methods on Implicit Feedback Database," Journal of Universal Computer Science,vol. 19,no. 12,pp. 1835-1853,2013.
  6. Noulas,S.Scellato,N.Lathia,and C. Mascolo,"A Random Walk around the City:New Venue Recommendation in Location-Based Social Networks," In Proceedings of International Conference on Social Computing (SocialCom),pp.144-153,2012.
  7. Y.Doytsher,B.Galon,and Y.Kanza,"Storing Routes in Sociospatial Networks and SupportingSocial-basedRoute Recommendation," In Proceedings of 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks,ACM,pp. 49-56,2011.
  8. M.Ye,P.Yin,and W.Lee,"Location recommendation for location-based social networks," In Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems,ACM,pp. 458-461,2010.
  9. S.Seema,and S. Alex,"Dynamic Bus Arrival Time Prediction,using GPS Data," In Proceedings of the Nat. Conference Technological Trends (NCTT),pp. 193-197,2010.
  10. B.Chandra,S.Bhaskar,"Patterned Growth Algorithm using Hub-Averaging without Pre-assigned Weights," In Proceeding of IEEE International Conference on Systems,man,and Cybernetics (SMC),pp.3518-3523,2010.
  11. C.Chow,J. Bao,and M. Mokbel,"Towards Location-Based Social Networking Services," In Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks,ACM,pp. 31-38,2010.
  12. Y.Zheng,L. Zhang,X. Xie,and W.Y. Ma,"Mining interesting locations and travel sequences from gps trajectories," In Proceedings of the 18th international conference on World wide web,ACM,pp. 791-800,2009.

Publication Details

Published in : Volume 3 | Issue 3 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 140-144
Manuscript Number : CSEIT1725204
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Sindhu J, Roopa G M , "A Survey - Approaches and Challenges for Cloud Based Recommendation System", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.140-144, March-April-2018.
Journal URL : http://ijsrcseit.com/CSEIT1725204

Article Preview