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Contents. 1. Introduction. 2. Procedure. The Results. 3. Conclusion. 4. Contents. 1. Introduction. 2. Procedure. The Results. 3. Conclusion. 4. Background. The rapid growth of the e.Publications . Most web search engines provide knowledge from different areas. - PowerPoint PPT PresentationTRANSCRIPT
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Contents
Introduction
Procedure
The Results
Conclusion4
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2
3
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Contents
Introduction
Procedure
The Results
Conclusion4
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2
3
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Background
• The rapid growth of the e.Publications.• Most web search engines provide knowledge from
different areas.– e.g. Google.com
• Some databases are focusing on specialized fields.– e.g. PubMed
• Each search engine is ranking the results depending on pre-defined factors.
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The Problem
• The variety of ranking and classifications might hinder the researchers’ work.
• Researchers and doctors spend long time to read all articles to find strong evidence to support their work.
• Beginner researchers’ decisions might be affected by relying on articles have low – quality with high – ranking or low-quality with large number of citations.
• The need to study and evaluate the popular ranking systems to focus on the most important publications.
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Project Aim
• Test the rank of 2,075 medical publications in four web ranking systems and a specialized citation index, which are:– Google PageRank.– Yahoo WebRank.– Bing ranking systems.– Alexa ranking systems.– PubMed citation index.
• Compare the results with the Strength of Recommendation Taxonomy ( SORT ) methodology.
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The Strength of Recommendation Taxonomy (SORT)
• The SORT classification has been designed to determine the strength of evidences in the medical publications.
• SORT uses three criteria to classify the publications:– The strength of recommendation for the body of evidence.
• A consistent and high quality patient-oriented evidence.• B inconsistent or limited quality patient-oriented evidence. • C opinions, disease-oriented, consensus and usual practice as well
as case studies for treatment, diagnosis, screening or prevention.– The quality of the individual studies. ( 1, 2 , 3 ).– The consistency of the publication. ( Consistent or inconsistent )
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Contents
Introduction
Procedure
The Results
Conclusion4
1
2
3
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Development Steps
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Step 1: Generating the PubMed Publications’ Links
• PubMed Publications’ ID have been given.• Automatic links generating.• The link = http://www.ncbi.nlm.nih.gov/pubmed/ + Publication ID
The Given Data The Generated links
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Steps 2-5: Testing Web Ranking Systems
• Automatic links testing framework have been developed.
• Pre-developed script has been used.• AJAX technologies have been used to improve the
test speed.Ranking System Approximate number of
links per testGoogle PageRank 200
Yahoo WebRank 30
Bing 50
Alexa 50
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Step 6: Testing PubMed Database
• PubMed citation index does not provide web service to implement the test.
• The PubMed publication pages have been studied to develop an automated method to fetch the number of citations.
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Step 6: Testing PubMed Database
Example of PubMed Page
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Step 6: Testing PubMed Database
Example of PubMed Citation Format
• The pages have been copied and analysed automatically.
• The system is able to process around 20 links per test.
• Some articles do not have citations.
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Step 6: Testing PubMed Database
Example of PubMed test results
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Contents
Introduction
Procedure
The Results
Conclusion4
1
2
3
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Google PageRank Results
0 1 2 3 4 50
50
100
150
200
250
300
350
400
450
ABC
Google PageRank Results
14
130
65
229
206
145
372
404
182
17
176
224
32
122
3 20Publication
rank
Number of Publications
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Google PageRank Results
• The correlation between the SORT classification and Google PageRank has been calculated using Pearson, Spearman and Kendall Correlation Coefficients as the following: – Pearson Correlation = 0.10793– Spearman Rank Correlation = 0.09971– Kendall Correlation = 0.08813
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Yahoo, Bing and Alexa Results
• Yahoo assigned all results to zero.
• Bing assigned all results to zero.
• Alexa assigned all results as same as the root page; which is: http://www.nih.gov/ . e.g. In 2 / November / 2011, the rank of http://www.nih.gov/
was 355. all publications’ ranks = 355
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PubMed Results
0 10 20 30 40 50 60 70 80 90 1000
100
200
300
400
500
600
ABC
Google PageRank Results
432
7 5101417
577
130
44406
116
393
4
83
31
131
Number ofCitations
Number of Publications
6 2371011 2
269
448
81
2222
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PubMed Results
• The correlation between the SORT classification and PubMed citation index has been calculated among Pearson, Spearman and Kendall Correlation Coefficients as the following: – Pearson Correlation = 0.07157– Spearman Rank Correlation = 0.05207– Kendall Correlation = 0.04267
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Results comparison
Correlation Google PageRank PubMedPearson 0.10793 0.07157
Spearman 0.09971 0.05207
Kendall 0.08813 0.04267
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Contents
Introduction
Procedure
The Results
Conclusion4
1
2
3
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Conclusion
• This study attempted to test whether the web ranking systems and citation indexes can help to determine the strength of 2,075 clinical publications according to their SORT classifications.
• Three generic measures have been used to calculate the correlations.
• Neither publication’s rank in the four popular systems nor the number of citations in PubMed database are correlated to the Strength Of Recommendation Taxonomy.
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Recommendations
• Studying other citation indexes such as Google Scholar, ScienceDirect, and Scopus.
• Track the positions of the authors who rank the publications and putting the publication date into the consideration
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Thank You!