Example of Journal of Computer Science format
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Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format
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Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format Example of Journal of Computer Science format
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open access Open Access

Journal of Computer Science — Template for authors

Categories Rank Trend in last 3 yrs
Computer Networks and Communications #267 of 334 down down by 90 ranks
Artificial Intelligence #197 of 227 down down by 61 ranks
Software #341 of 389 down down by 49 ranks
journal-quality-icon Journal quality:
Low
calendar-icon Last 4 years overview: 498 Published Papers | 474 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 08/07/2020
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Related Journals

open access Open Access
recommended Recommended

IEEE

Quality:  
High
CiteRatio: 19.8
SJR: 2.882
SNIP: 3.86
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SJR: 0.427
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Elsevier

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SJR: 0.638
SNIP: 1.44
open access Open Access

Springer

Quality:  
Good
CiteRatio: 4.6
SJR: 0.983
SNIP: 1.376

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

A measure of average citations received per peer-reviewed paper published in the journal.

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

1.0

CiteRatio for Journal of Computer Science from 2016 - 2020
Year Value
2020 1.0
2019 1.0
2018 0.9
2017 1.2
2016 1.4
graph view Graph view
table view Table view

0.161

6% from 2019

SJR for Journal of Computer Science from 2016 - 2020
Year Value
2020 0.161
2019 0.171
2018 0.162
2017 0.147
2016 0.172
graph view Graph view
table view Table view

0.437

12% from 2019

SNIP for Journal of Computer Science from 2016 - 2020
Year Value
2020 0.437
2019 0.499
2018 0.679
2017 0.453
2016 0.645
graph view Graph view
table view Table view

insights Insights

  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has decreased by 6% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 12% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Journal of Computer Science

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Science Publications

Journal of Computer Science

Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experim...... Read More

Computer Networks and Communications

Software

Artificial Intelligence

Computer Science

i
Last updated on
08 Jul 2020
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ISSN
1549-3636
i
Impact Factor
Medium - 0.67
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
plainnat Science Publication custom citation
i
Citation Type
Author Year
(Blonder et al., 1982)
i
Bibliography Example
G E Blonder, M Tinkham, and T M Klapwijk, 1982. Tran- sition from metallic to tunneling regimes in supercon- ducting microconstrictions: Excess current, charge im- balance, and supercurrent conversion. Phys. Rev. B, 25 (7):4515–4532. URL 10.1103/PhysRevB.25.4515.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.3844/JCSSP.2006.735.739
Data Mining: A Preprocessing Engine
Luai Al Shalabi, Zyad Shaaban, Basel Kasasbeh

Abstract:

This study is emphasized on different types of normalization. Each of which was tested against the ID3 methodology using the HSV data set. Number of leaf nodes, accuracy and tree growing time are three factors that were taken into account. Comparisons between different learning methods were accomplished as they were applied t... This study is emphasized on different types of normalization. Each of which was tested against the ID3 methodology using the HSV data set. Number of leaf nodes, accuracy and tree growing time are three factors that were taken into account. Comparisons between different learning methods were accomplished as they were applied to each normalization method. A new matrix was designed to check for the best normalization method based on the factors and their priorities. Recommendations were concluded. read more read less

Topics:

Normalization (statistics) (65%)65% related to the paper, Decision tree learning (53%)53% related to the paper, Incremental decision tree (52%)52% related to the paper
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391 Citations
open accessOpen access Journal Article DOI: 10.3844/JCSSP.2007.740.746
Combined DWT-DCT Digital Image Watermarking

Abstract:

The proliferation of digitized media due to the rapid growth of networked multimedia systems, has created an urgent need for copyright enforcement technologies that can protect copyright ownership of multimedia objects. Digital image watermarking is one such technology that has been developed to protect digital images from il... The proliferation of digitized media due to the rapid growth of networked multimedia systems, has created an urgent need for copyright enforcement technologies that can protect copyright ownership of multimedia objects. Digital image watermarking is one such technology that has been developed to protect digital images from illegal manipulations. In particular, digital image watermarking algorithms which are based on the discrete wavelet transform have been widely recognized to be more prevalent than others. This is due to the wavelets' excellent spatial localization, frequency spread, and multi-resolution characteristics, which are similar to the theoretical models of the human visual system. In this paper, we describe an imperceptible and a robust combined DWT-DCT digital image watermarking algorithm. The algorithm watermarks a given digital image using a combination of the Discrete Wavelet Transform (DWT) and the Discrete Cosine Transform (DCT). Performance evaluation results show that combining the two transforms improved the performance of the watermarking algorithms that are based solely on the DWT transform. read more read less

Topics:

Digital Watermarking Alliance (69%)69% related to the paper, Digital watermarking (65%)65% related to the paper, Discrete wavelet transform (59%)59% related to the paper, Discrete cosine transform (59%)59% related to the paper, Digital image processing (58%)58% related to the paper
319 Citations
open accessOpen access Journal Article DOI: 10.3844/JCSSP.2007.430.435
Chi Square Feature Extraction Based Svms Arabic Language Text Categorization System

Abstract:

This paper aims to implement a Support Vector Machines (SVMs) based text classification system for Arabic language articles. This classifier uses CHI square method as a feature selection method in the pre-processing step of the Text Classification system design procedure. Comparing to other classification methods, our system ... This paper aims to implement a Support Vector Machines (SVMs) based text classification system for Arabic language articles. This classifier uses CHI square method as a feature selection method in the pre-processing step of the Text Classification system design procedure. Comparing to other classification methods, our system shows a high classification effectiveness for Arabic data set in term of F-measure (F=88.11). read more read less

Topics:

Support vector machine (53%)53% related to the paper, Feature extraction (52%)52% related to the paper, Feature selection (51%)51% related to the paper
View PDF
235 Citations
open accessOpen access Journal Article DOI: 10.3844/JCSSP.2006.194.200
Empirical Study on Applications of Data Mining Techniques in Healthcare

Abstract:

The healthcare environment is generally perceived as being ‘information rich’ yet ‘knowledge poor’. There is a wealth of data available within the healthcare systems. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. Knowledge discovery and data mining have found numerou... The healthcare environment is generally perceived as being ‘information rich’ yet ‘knowledge poor’. There is a wealth of data available within the healthcare systems. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. Knowledge discovery and data mining have found numerous applications in business and scientific domain. Valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, we briefly examine the potential use of classification based data mining techniques such as Rule based, decision tree and Artificial Neural Network to massive volume of healthcare data. In particular we consider a case study using classification techniques on a medical data set of diabetic patients. read more read less

Topics:

Knowledge extraction (62%)62% related to the paper, Software mining (57%)57% related to the paper
View PDF
230 Citations
open accessOpen access Journal Article DOI: 10.3844/JCSSP.2010.363.368
Computational Complexity between K-Means and K-Medoids Clustering Algorithms for Normal and Uniform Distributions of Data Points

Abstract:

Problem statement: Clustering is one of the most important research ar eas in the field of data mining. Clustering means creating groups of ob jects based on their features in such a way that th e objects belonging to the same groups are similar an d those belonging to different groups are dissimila r. Clustering is an unsupe... Problem statement: Clustering is one of the most important research ar eas in the field of data mining. Clustering means creating groups of ob jects based on their features in such a way that th e objects belonging to the same groups are similar an d those belonging to different groups are dissimila r. Clustering is an unsupervised learning technique. T he main advantage of clustering is that interesting patterns and structures can be found directly from very large data sets with little or none of the background knowledge. Clustering algorithms can be applied in many domains. Approach: In this research, the most representative algorithms K-Mean s and K-Medoids were examined and analyzed based on their basic approach. The best algorithm i n each category was found out based on their performance. The input data points are generated by two ways, one by using normal distribution and another by applying uniform distribution. Results: The randomly distributed data points were taken as input to these algorithms and clusters are found ou t for each algorithm. The algorithms were implemented using JAVA language and the performance was analyzed based on their clustering quality. The execution time for the algorithms in each category was compar ed for different runs. The accuracy of the algorith m was investigated during different execution of the program on the input data points. Conclusion: The average time taken by K-Means algorithm is greater than the time taken by K-Medoids algorithm for both the case of normal and uniform distributions. The r esults proved to be satisfactory. read more read less

Topics:

Cluster analysis (69%)69% related to the paper, Correlation clustering (68%)68% related to the paper, Single-linkage clustering (67%)67% related to the paper, CURE data clustering algorithm (66%)66% related to the paper, Canopy clustering algorithm (66%)66% related to the paper
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211 Citations
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Journal of Computer Science format uses plainnat Science Publication custom citation citation style.

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Frequently asked questions

1. Can I write Journal of Computer Science in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Journal of Computer Science guidelines and auto format it.

2. Do you follow the Journal of Computer Science guidelines?

Yes, the template is compliant with the Journal of Computer Science guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Journal of Computer Science?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Journal of Computer Science citation style.

4. Can I use the Journal of Computer Science templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Journal of Computer Science.

5. Can I use a manuscript in Journal of Computer Science that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Journal of Computer Science that you can download at the end.

6. How long does it usually take you to format my papers in Journal of Computer Science?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Journal of Computer Science.

7. Where can I find the template for the Journal of Computer Science?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Journal of Computer Science's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Journal of Computer Science's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Journal of Computer Science an online tool or is there a desktop version?

SciSpace's Journal of Computer Science is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Journal of Computer Science?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Journal of Computer Science?”

11. What is the output that I would get after using Journal of Computer Science?

After writing your paper autoformatting in Journal of Computer Science, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Journal of Computer Science's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Journal of Computer Science?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Journal of Computer Science. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Journal of Computer Science?

The 5 most common citation types in order of usage for Journal of Computer Science are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Journal of Computer Science?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Journal of Computer Science's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Journal of Computer Science in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Journal of Computer Science Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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