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International Journal
of Computer Engineering in Research Trends (IJCERT)

Scholarly, Peer-Reviewed, Open Access and Multidisciplinary

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International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed,Open Access and Multidisciplinary

ISSN(Online):2349-7084                 Submit Paper    Check Paper Status    Conference Proposal

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Asst. Professor, Dept of CSE, RVS College of Engineering& Technology, Pondicherry University, India.
Final year students, Dept of CSE, RVS College of engineering & Technology, Pondicherry University, India.

Search Engine Marketing (SEM) manages thousands of search keywords for their clients. Using dashboards, users had created test variants for various bid choices, keyword ideas, and advertisement text options. And then, they used controlled experiments for selecting the best performing variants. Campaign management can easily become a burden on every advertiser. In order to target users in need of a particular service, advertisers have to determine the purchase intents or information needs of target users. Once the target intents are determined, advertisers can target those users with relevant search keywords. In order to formulate information needs and to scale campaign management with increasing number of keywords, we propose a framework called topic machine, where we learn the latent topics hidden in the available search terms reports. Our hypothesis is that these topics correspond to the set of information needs that best match-make a given client with users. We foresee, the advertisers can view a topic by a campaign management to thousands of keywords comfortably with the use of topic machine while at the same time optimizing for conversions. Topic machine’s internal model can be used to reduce dimensions of the search term space.

VIJAYALAKSHMI.S,VENKATESHAN.J,RUBASHRI.P,NITHYA.B."TOPIC MACHINE: IDENTIFYING KEYWORDS USING LTM". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.2, Issue 03,pp.205-207, March - 2015, URL :,

Keywords : Internet advertising, Search Engine Marketing, Topic machine

[1] Topic machine: conversion prediction in search advertising using latent topic models, Ahmet Bulut,Member,IEEE. 
[2] D. Easley and J. Kleinberg, Networks, Crowds, and Markets: Reasoning about a Highly Connected World. New York, USA: Cambridge University Press. 
[3] R. Kohavi, R. Longbotham, D. Sommerfield, and R. M. Henne, ‚Controlled experiments on the web: Survey and practical guide,‛Data Mining and Knowledge Discovery. 
[4] C. D. Manning, P. Raghavan, and H. Schutze, Introduction to Information Retrieval. Cambridge University Press. 
[5]B. Ribeiro-Neto, M. Cristo, P. B. Golgher, and E. S. de Moura, ‚Impedance coupling in contenttargeted advertising,‛ International Conference on Research and Development in Information Retrieval (SIGIR). ACM.


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Latest issue :Volume 10 Issue 1 Articles In press

A plagiarism check will be implemented for all the articles using world-renowned software. Turnitin.

Digital Object Identifier will be assigned for all the articles being published in the Journal from September 2016 issue, i.e. Volume 3, Issue 9, 2016.

IJCERT is a member of the prestigious.Each of the IJCERT articles has its unique DOI reference.
DOI Prefix : 10.22362/ijcert

IJCERT is member of The Publishers International Linking Association, Inc. (“PILA”)

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☞   LAST DATE OF SUBMISSION : 31st March 2023
In 7 Days

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4. A List of blacklisted authors will be shared among the Chief Editors of other prestigious Journals
We have been screening articles for plagiarism with a world-renowned tool: Turnitin However, it is only rejected if found plagiarized. This more stern action is being taken because of the illegal behavior of a handful of authors who have been involved in ethical misconduct. The Screening and making a decision on such articles costs colossal time and resources for the journal. It directly delays the process of genuine materials.

Citation Index

Citations Indices All
Citations 1026
h-index 14
i10-index 20
Source: Google Scholar

Acceptance Rate (By Year)

Acceptance Rate (By Year)
Year Rate
2021 10.8%
2020 13.6%
2019 15.9%
2018 14.5%
2017 16.6%
2016 15.8%
2015 18.2%
2014 20.6%

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