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An Efficient and Scalable Auto Recommender System Based on Users Behavior

N.Sujatha 1 , K. Prakash2

Section:Review Paper, Product Type: Isroset-Journal
Vol.6 , Issue.6 , pp.35-40, Dec-2018


CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v6i6.3540


Online published on Dec 31, 2018


Copyright © N.Sujatha, K. Prakash . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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IEEE Style Citation: N.Sujatha, K. Prakash, “An Efficient and Scalable Auto Recommender System Based on Users Behavior,” International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.6, pp.35-40, 2018.

MLA Style Citation: N.Sujatha, K. Prakash "An Efficient and Scalable Auto Recommender System Based on Users Behavior." International Journal of Scientific Research in Computer Science and Engineering 6.6 (2018): 35-40.

APA Style Citation: N.Sujatha, K. Prakash, (2018). An Efficient and Scalable Auto Recommender System Based on Users Behavior. International Journal of Scientific Research in Computer Science and Engineering, 6(6), 35-40.

BibTex Style Citation:
@article{Prakash_2018,
author = {N.Sujatha, K. Prakash},
title = {An Efficient and Scalable Auto Recommender System Based on Users Behavior},
journal = {International Journal of Scientific Research in Computer Science and Engineering},
issue_date = {12 2018},
volume = {6},
Issue = {6},
month = {12},
year = {2018},
issn = {2347-2693},
pages = {35-40},
url = {https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=1041},
doi = {https://doi.org/10.26438/ijcse/v6i6.3540}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i6.3540}
UR - https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=1041
TI - An Efficient and Scalable Auto Recommender System Based on Users Behavior
T2 - International Journal of Scientific Research in Computer Science and Engineering
AU - N.Sujatha, K. Prakash
PY - 2018
DA - 2018/12/31
PB - IJCSE, Indore, INDIA
SP - 35-40
IS - 6
VL - 6
SN - 2347-2693
ER -

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Abstract :
Online purchasing is becoming more common in our everyday lives. Understanding customers interests and behaviour is basic so as to adjust web based business sites according to customers necessities. The data about customers` behaviour is put away in the web server logs. The examination of such data has concentrated on applying information mining methods where a somewhat static characterization is utilized to demonstrate customers` behaviour and the succession of the activities performed by them isn`t generally considered. Subsequently, consolidating a perspective of the procedure pursued by customers during a session can be of extraordinary enthusiasm to distinguish progressively complex personal conduct standards. To address this issue, this paper proposes a straight transient rationale demonstrate checking approach for the examination of organized web based business web logs. By defining a typical method for mapping log records as indicated by the web based business structure, web logs can be effectively changed over into occasion logs where the behaviour of customers is caught. At that point, diverse predefined questions can be performed to distinguish distinctive standards of behaviour that consider the diverse activities performed by customer during the session. At last, the value of the proposed methodology has been considered by applying it to a genuine contextual investigation of a business site. The outcomes have identified fascinating findings that have made conceivable to propose a few enhancements in the website design with the aim of expanding its efficiency.

Key-Words / Index Term :
Data mining, e-commerce, web logs analysis, behavioral patterns, model checking

References :
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