Faculty Members
Dr. Rinkal Sardhara
Associate Professor
PhD (Computer Science), GSET Qualified
Date of Joining LJICA 2nd Dec, 2010.
Area of Interest
Graph theory, Data Structures, Web mining, Data Science, Machine Learning and Programming languages.
Majors Degrees
2016 - 2020 Doctor of philosophy in computer science, Department of Computer Science, Gujarat University, Gujarat, India.
2007 - 2010 Master of computer applications, Charotar Institutes of Computer Applications, Gujarat University, Gujarat, India.
2004 - 2007 Bachelor of science in Physics, M. G. Science College, Gujarat University, Gujarat, India.
2002 - 2004 High School Education, Vivekanand Higher Secondary school, Ahmedabad, Gujarat, India.
Online Certified Courses
2020 Machine learning with Python, successfully completed an online course authorized by IBM.
2018 Getting and Cleaning Data, successfully completed an online course authorized by Johns Hopkins University, Maryland
2018 Exploratory Data Analysis, successfully completed an online course authorized by Johns Hopkins University, Maryland
2017 Introduction to HTML5, successfully completed an online course authorized by University of Michigan, Ann Arbor
2017 Introduction to Programming with MATLAB, successfully completed an online course authorized by Vanderbilt University, Nashville.
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2010 - 2012 Lecturer cum tutor, L. J. Institute of Computer Applications, Gujarat University, Gujarat, India.
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2012 - Present ASSISTANT PROFESSOR, L. J. Institute of Computer Applications, Gujarat University, Gujarat, India.
Patents
2020
Id tracking to 4-g mobile with security using deep learning programming Date of filing: 3 May 2020, Patent no: 202021018871(Published)
Journal Publication
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Rinkal sardhara, Shanti verma “COVID-19 Pandemic: Recovery and Death Ratio Analysis Based on Latitude Using Correlation and ANOVA”, in industry 4.0 and intelligent business analytics for healthcare published by nova science, ISBN: 978-1-68507-602-3
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Shanti verma, Rinkal sardhara “A Novel Model to Anticipate Transparency in COVID-19 Records of India Using Blockchain”, in industry 4.0 and intelligent business analytics for healthcare published by nova science, ISBN: 978-1-68507-602-3
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2019 Rinkal Sardhara, Kamaljit I. Lakhataria “Comparision of Pagerank and Weighted Page Rank Algorithm Using Data Set Of Genetics Keyword” in International Journal of Research and analytical reviews (E-ISSN 2348-1269 P-ISSN 2349-5138) vol. 6 issue 2. pp 277-282
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2019 Rinkal Sardhara, Kamaljit I. Lakhataria “A Novel Approach To Reduce Mutual Reinforcement Effect In Web Page Ranking” in International Journal of Research and analytical reviews (E- ISSN 2348-1269 P-ISSN 2349-5138). vol. 6 issue 2. pp 451-455
Conference Publication
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2019 Rinkal Sardhara, Kamaljit I. Lakhtaria,” An Improved PageRank Algorithm Based on Reachability to Reduce Mutual Reinforcement Effect”, in The 10th International conference on Computing, Communication and Networking technologies held on 6-8 July 2019 at IIT Knapur ,Kanpur, India. Published in IEEE Xplorer ISBN: 978-1-5386-5906-9
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2019 Rinkal Sardhara, Kamaljit I. Lakhtaria,” A flowchart to reduce mutual reinforcement effect on web page ranking based on web structure mining” in 3rd International Conference on Electronics,Communicstions and Aerospace Technology held on 12-14 June 2019 at RVS Technical Campus,Coimbatore,India, Published in IEEE Xplorer
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2019 Rinkal Sardhara,Kamaljit I. Lakhtaria, “Impact of Rechability, Number of Inlink and Outlink of Different Domain on Relevance of Web Page Using Correlation”,in International Conference on Intelligent Computing and Control Systems held on 15-17 May,2019 at Vaigai College of Engineering, Madurai, India, Published in IEEE Xplorer, ISBN - 978-1-5386-8113-8
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2018 Rinkal Sardhara,Kamaljit I. Lakhtaria, “Web Structure Mining : A Novel Approach to Reduce Mutual Reinforcement “ ,in 3rd International Conference and Workshops on Recent Advances and Innovations in Engineering held on 22-25 November, 2018 at Poornima University, Jaipur ,Rajsthan, India, Published in IEEE xplorer, Electronic ISBN: 978-1-5386-4525-3, Print on Demand(PoD) ISBN: 978-1-5386-4526-0,INSPEC Accession Number: 18655782
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2017 Rinkal Sardhara, Kamaljit .I. Lakhtaria, “A Comparative Study of Page Ranking Algorithms on the Basis of Web Structure Mining”, in AICTE Sponsored International Conference on Efficient Implementation of Digital India and Cashless Transaction held on 27-28 November, 2017, at Janardan Rai Nagar Rajasthan Vidyapeeth, Udaipur, Rajasthan , India.
Subjects taught : Undergraduates
Basic mathematics (1st sem),
Fundamentals of web(1st sem.),
Software Project - I (1st sem.),
User defined project-II (2nd Sem.) ,
Data Structures (3rd sem.) ,
UML and Object- Oriented Language(4th sem),
Python (4th sem),
Fundamental of Computer Applications(1st sem),
WDT (3rd sem),
SE (5th sem)
Subjects taught: Postgraduates
Data Science Project(9th sem),
Data Structures(L-3rd sem),
SEO(5th sem),
AN(5th sem),
User Define Project (10th sem and 6th sem),
Operations research (4th sem)
Syllabus as per GTU MCA/IMCA
Research Work:
Research study includes mining of web structure. Web structure mining has main two components such as arcs and nodes. Arcs means link between two web pages and node means web page itself. It is a tedious task to find relevant and authoritative webpage from vast web. Web structure mining plays important role in finding authoritative and relevant web pages. There are two basic algorithms, works on web structure mining such as PageRank and HITS which provides efficient search results. PageRank algorithm used by one of famous search engine, Google. HITS provides two types of rank score Hub and Authority score. The aim of research study is to find an efficient web page rank algorithm using web structure mining. I have divided research study in following four phases such as literature review, identify loophole, proposed algorithm to reduce the effect of the problem found and result and analysis. This way I have decide my research scope. However, I have collected the research papers which are related to web structure mining. After collecting numerous research papers, I have analysed the research paper and distinguished paper which are purely based on web structure. During the observation I have found the mutual reinforcement problem. I have decided to work on mutual reinforcement problem. Mutual reinforcement means creating a link between web pages from the same domain and to the same domain, just to improve the rank of web pages. I have collected data from cs.torrento.edu website and cleaned it according to the requirements. To reduce the mutual reinforcement effect author has proposed three different parameters such number of inlink from different domain, number of outlink from different domain and reachability. I have also checked correlation of proposed parameters with the relevancy of web pages. It has been observed that there is a positive correlation between proposed parameters and relevancy of the web page. In proposed algorithm (IPRA) I have used all the proposed parameters. I have reduced the links between web pages with the help of reachability value. In research study I have proposed the algorithm (IPRA) through which mutual reinforcement effect will be reduced. The fourth phase is result and analysis in that I have analysed the proposed algorithm with the two analysis techniques. First is independent variable t-test. By using python scripts, I have generated data for the analysis and check the significance of result at 95%. To check how much mutual reinforcement effect will be reduced through the proposed algorithm(IPRA), I have used precision and recall test. I have generated the data using python scripts for the calculation of precision, recall and accuracy. In this research study I have also used different graphs to represent the result set. I have used different tool to represent chart such as Ms-Excel, Tableau, R programming and Python
2019 Conducted a one day workshop on Web design technology(PHP) at LJICA, Ahmedabad.
2019 Participated in FDP on Cloud based web application development using python (Django + MongoDB) at LJICA, Ahmedabad.
2019 Attended one day FDP on Data Science and Code optimization at GTU, Ahmedabad.
2014 Participated in the How to write workshop at GTU, Ahmedabad
2013 Attended the workshop on Research Methodology at LJMCA campus.
2011 Provided services as a Lab Trainer at “10 days’ stage gate workshop on C” at L.J. IIPC, Ahmedabad.
Contact
LJ Institute of Computer Appliactions,
LJ Campus, Near Sarkhej-Sanand Circle,
Off. S.G. Road, Ahmedabad-382210
Phone: 9099063417
Email: rinkal.sardhara@ljku.edu.in