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An M/M/1 Based Modeling Approach for the Web Crawled Data


  • Department of CSA, SCSVMV University, Enathur, Tamil Nadu, India
  • Department of MCA, St. Joseph’s College of Engineering, Chennai, India
  • Department of Computer Science & Engineering, RGMCET, Andhra Pradesh, India


Objectives: To develop a suitable model to study the behavior of web crawled dataset and perform simulation on the modeled data for better understanding of the system Methods/Statistical Analysis: M/M/1 model is a variation of Single Birth Single Death (SBSD) model which is applied to study the behavior of web crawled dataset for the Classification Problem. KanchiCrawler, a stylized focused web crawler is implemented to collect the data for this application. The size of the corpora (Population) is 500k. Control corpus (sample) can be drawn from the corpora based on enforcing certain pre-determined conditions. Findings: A 20-state model starting with an initial test corpus of 25k and then by gradually increasing with an increment of 25k up to 500k is developed. This is achieved through the computation of Forward State Transition Probability and Reverse State Transition Probability for the respective states. This model provides fairly good results by testing the algorithmic efficiency of a KanchiCrawler and to model the web crawled dataset for the classification problem. Applications: M/M/1 models are tractable and often used to model various operations of nature. In most situations where large numbers are involved, M/M/1 model are statistically stable and reflective of reality.


Dataset Modeling, KanchiCrawler, M/M/1 Model, State Transition Probability.

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  • Amandeep Verma, Amandeep Kaur Gahier. Topic Modeling of E-News in Punjabi. Indian Journal of Science and Technology. 2015 Oct; 8(27):1-10.
  • Peyman Salah, Seyed Siavash Karimi Madahi, Hassan Feshki Farahani, Ali Asghar Ghadimi. A New Method to Calculate Residential Consumer's Consumption Using Computer Modeling. Indian Journal of Science and Technology. 2012 May; 5(5):1-5.
  • Van Der Aalst WM. Process-oriented architectures for electronic commerce and inter organizational workflow. Information systems. 1999 Dec; 24(9):639-71.
  • Peterson JL. Petri net theory and the modeling of systems. Prentice Hall PTR Upper Saddle River, NJ, USA. 1981.
  • Shamim Yousefi, Samad Najjar Ghabel, Leyli Mohammad Khanli. Modeling Causal Consistency in a Distributed Shared Memory using Hierarchical Colored Petri Net. Indian Journal of Science and Technology. 2015 Dec; 8(33):1-7.
  • Bahman AR, Alialhosseini E. Modeling of Component Diagrams Using Petri Nets. Indian Journal of Science and Technology. 2010 Dec; 3(12):1-11.
  • Reisig W. Petri Nets: An Introduction, volume 4 of Monographs in Theoretical Computer Science. Springer. 1985 May.
  • Johnsonbaugh R, Murata T. Petri nets and marked graphs-mathematical models of concurrent computation. The American Mathematical Monthly. 1982 Oct; 89(8):552-66.
  • Sawyer H, Kauffman MJ. Stopover ecology of a migratory ungulate. Journal of Animal Ecology. 2011 Sep; 80(5):1078-87.
  • Shankar, Natarajan. Symbolic Analysis of Transition Systems? ASM '00 Proceedings of the International Workshop on Abstract State Machines, Theory and Applications.2000, p.287-302.
  • Larson RC. A hypercube queuing model for facility location and redistricting in urban emergency services. Computers and Operations Research. 1974 Mar; 1(1):67-95.
  • Leenaerts D, Van Bokhoven WM. Piecewise linear modeling and analysis. Kluwer Academic Publishers Norwell, MA, USA. 1998.
  • Ali Kiani, Mohsen Izadinia. An Overview on Effects of Geometric Parameters in Column Connection Behavior via Finite Element Method. Indian Journal of Science and Technology. 2015 Oct; 8(28):1-7.


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