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• Open Access   Article

  Assessment and Implementation of Service Quality of A HOTEL Using SERVQUAL Model

  D. Dapkara, D.S. Verma

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.3 , pp.68-73, Jun-2017

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  Abstract
  Now a days service industries growing very fast than other industries, it was the fact highlighted by economist in whole World. The quality of this sector is seems to be declining so the major challenge in the service industries is to designing quality service. This study identify that the satisfaction level of the consumer in HOTEL industries in India or any other place in the whole world. I am applying it in A HOTEL in INDORE MP. Applying model of SERVQUAL in A HOTEL to measure the customer satisfaction level, and find the Gap between the expectation and perceptions of the customer. After finding Gap, provide some suggestion to Hotel management for implementation of the Quality of the HOTEL. Data are collected by preparing a questionnaire and feedback is taken of that questionnaire from the customers of that HOTEL and result are found by method of calculating AM (Arithmetic Mean).

  Key-Words / Index Term
  SERVQUAL, Service Quality, Expectation, Perception, Customer Satisfaction, Hotel

  References
  [1]Asubonteng P., McCleary K.J., Swan J.E., “SERVQUAL revisited: a critical review of service quality”, The Journal of Services Marketing, Vol.10, No.6, pp.62- 81, 1996.
  [2] Sureshchander G.S., Rajendran C., Anatharaman R.N., “The relationship between service quality and customer satisfaction: a factor specific approach”, Journal of Services Marketing, Vol. 16 No. 4, pp. 363-79, 2002
  [3].Silvestro R., Cross S., “Applying service profit chain in a retail environment”, International Journal of Service Industry Management, Vol. 11 No. 3, pp. 244-68, 2000.
  [4]Parasuraman A., Zeithaml V.A., Berry, L.L., “A conceptual model of service quality and its implications for future research”, Journal of Marketing, Vol. 49 No. 3, pp.41-50, 1985,
  [5]. Carman J.M., “Consumer Perceptions of Service Quality: An Assessment of the SERVQUAL Dimensions”, Journal of Retailing, Vol.66, Issue.1, pp.33-55, 1990.
  [6]A. Shahin, “SERVQUAL and Model of Service Quailty Gaps: A framework for determining and prioritizing critical factors in delivering quality services”, Department of Management-University of Isfahan, Iran, pp.1-10, 1990.
  

  Citation
  D. Dapkara, D.S. Verma, "Assessment and Implementation of Service Quality of A HOTEL Using SERVQUAL Model," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.68-73, 2017

• Open Access   Article

  An Integrated and Improved Scheme for Efficient Intrusion Detection in Cloud

  Prachi Tembhare, Neeraj Shukla

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.3 , pp.74-78, Jun-2017

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  Abstract
  Cloud computing environments are easy targeted by intruders and pose new risks and threats to an organization because of its service and operational models, the underlying technologies, and their distributed nature that relies on the network for its working. However, IDSs are among the efficient security mechanisms that can handle most of the threats of cloud computing. In spite this, several deficiencies of current IDSs technologies and solutions hinder their adoption in a cloud. The proposed work focuses on developing improved IDS that provides an integrated approach of both techniques i.e. anomaly based as well as knowledge based whether implement on network or host based IDS for cloud computing to detect masquerade, host, and network attacks and provides efficient deployments to detect DDoS attacks. The work comprises of integration of two powerful open source tool Suricata and Snort together with the proposed DDoS detection rule make the working of IDS more effective and high alarm rate generating Hybrid IDS.

  Key-Words / Index Term
  Cloud Security, Distributed Denial of Service Attack, Intrusion Detection System, Suricata, Snort, Hybrid IDS

  References
  [1] Vivek Raich, Pradeep Sharma, Shivlal Mewada and Makhan Kumbhkar, “Performance Improvement of Software as a Service and Platform as a Service in Cloud Computing Solution”, International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.6, pp.13-16, 2013.
  [2] V.P.Muthukumar and R.Saranya, “A Survey on Security Threats and Attacks in Cloud Computing”, International Journal of Computer Sciences and Engineering, Vol.2, Issue.11, pp.120-125, 2014.
  [3] Sudhansu Ranjan Lenka and Bikram Keshari Rath , “HTTP service based Network Intrusion Detection System in Cloud Computing”, International Journal of Computer Sciences and Engineering, Vol.3, Issue.6, pp.118-123, 2015.
  [4] Mithilesh Mittal, Pradeep Sharma and Pankaj Kumar Gehlot, “A Comparative Study of Security Issues& Challenges of Cloud Computing”, International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.5, pp.9-15, 2013.
  [5] PK. Rajendran , “Hybrid intrusion detection algorithm for private cloud”, Indian Journal of Science and Technology, Vol.8, Issue.35, pp.1-10, 2015
  [6] HM. Alsafi , WM. Abduallah, “IDPS: An Integrated Intrusion Handling Model for Cloud Computing Environment”, International Journal of Computing and Information Technology, Vol.4, Issue.1, pp.1-6, 2014.
  [7] Amirreza Zarrabi, Alireza, “Internet Intrusion Detection System Service in a Cloud”, International Journal of Computer Science Issues, Vol.9, Issue.5, pp.308-315, 2012
  [8] Ahmed Patel, Mona Taghavi, “An intrusion detection and prevention system in cloud computing: A systematic review”, Journal of network and computer applications, Vol.36, Issue.1, pp.25-41, 2013.
  [9] Vineet Chaturvedi, Ashok Verma and Neha Agarwal, “A Systematic Approach for Ensuring Security and Efficiency in Cloud Computing”, International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.5, pp.16-20, 2013.
  [10] M. Chowdhary, S. Suri, M. Bhutani, “Comparative Study of Intrusion Detection System”, International Journal of Computer Sciences and Engineering, Vol.2, Issue.4, pp.197-200, 2014.
  

  Citation
  Prachi Tembhare, Neeraj Shukla, "An Integrated and Improved Scheme for Efficient Intrusion Detection in Cloud," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.74-78, 2017

• Open Access   Article

  Web Mining an Approach to Evaluate the Web

  AshirrK Kashyap, Iflah Naseem, Dheeraj Mandloi

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.3 , pp.79-85, Jun-2017

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  Abstract
  Web mining is a field of quite importance a s it include two of the most activated research fields, the data mining and the world wide web. The web mining is an application of data mining which extract the indexed information from the web and sorts them accordingly. In the absence internet, the advancement in technology would not have been possible. The information on the web is so voluminous and heterogeneous that it becomes a necessity to evaluate this available information and present it into a useful form according to the particular problem. Web mining helps in figuring out various patterns obtained in the activities of users and dealing with these interesting patterns developing usable abstracts from various sources. The paper will deal with the various categories of web data mining, its effectiveness in current arena of internet, its pros and cons along with the future it holds in the field of computer science.

  Key-Words / Index Term
  Web Usage Mining, Web Structure Mining, Web Data Mining, Web Content Mining

  References
  [1] R Kosala, H Blockeel, “Web mining Research: A survey”, ACM SIKGDD, Vol.2, Issue 1, pp. 1-2, 2000.
  [2] D. Jayalatchumy, P.Thambidurai, “Web Mining Research Issues and Future Directions – A Survey”, IOSR Journal of Computer Engineering (IOSR-JCE), Vol.4, Issue.3, pp.20-27, 2013.
  [3] V. Krishnaiah, G. Narsimha, N.S. Chandra, “Survey of Classification Techniques in Data Mining”, International Journal of Computer Sciences and Engineering, Vol.2, Issue.9, pp.65-74, 2014.
  [4] N Jain, V Srivastava, “Data mining techniques: a survey paper”, IJRET: International Journal of Research in Engineering and Technology, Vol.2 ,Issue.11, pp 116-119, Nov-2013.
  [5] P Mehtaa, B Parekh, K Modi, P. Solanki, “Web Personalization Using Web Mining: Concept and Research Issue”, International Journal of Information and Education Technology, Vol.2, Issue.5, pp.1-7, 2012.
  [6] R. Munilatha1 , K. Venkataramana, “A Study on issues and techniques of web mining”, International Journal of Computer Science and Mobile Computing, Vol.3, Issue.5, pp.331-341, 2014.
  [7] J Srivastava, P Desikan, V Kumar, “Web Mining— Concepts,Applications, and Research Directions”, Foundations and advances in data mining, Berlin, pp.275-307, 2003.
  [8] Siddu P. Algur, Prashant Bhat, “Abnormal Web Video Prediction Using RT and J48 Classification Techniques”, International Journal of Computer Sciences and Engineering, Vol.4, Issue.6, pp.101-107, 2016.
  [9] M. Aldekhail, “Application and Significance of Web Usage Mining in the 21st Century: A Literature Review”, International Journal of Computer Theory and Engineering, Vol. 8, No. 1, pp.1-6, 2016.
  [10] Rajesh Shah and Suresh Jain, “Web Mining Using Cloud Computing Technology”, International Journal of Scientific Research in Computer Science and Engineering, Vol.3, Issue.2, pp.21-25, 2015.
  

  Citation
  AshirrK Kashyap, Iflah Naseem, Dheeraj Mandloi, "Web Mining an Approach to Evaluate the Web," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.79-85, 2017

• Open Access   Article

  Data Mining and Information Security in Big Data

  S. Sathyamoorthy

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.3 , pp.86-91, Jun-2017

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  Abstract
  The growing popularity and development of data mining technologies bring serious threat to the security of individual`s sensitive information. An emerging research topic in data mining, known as privacy-preserving data mining (PPDM), has been extensively studied in recent years. The basic idea of PPDM is to modify the data in such a way so as to perform data mining algorithms effectively without compromising the security of sensitive information contained in the data. Current studies of PPDM mainly focus on how to reduce the privacy risk brought by data mining operations, while in fact, unwanted disclosure of sensitive information may also happen in the process of data collecting, data publishing, and information (i.e., the data mining results) delivering. In this paper, we view the privacy issues related to data mining from a wider perspective and investigate various approaches that can help to protect sensitive information. In particular, we identify four different types of users involved in data mining applications, namely, data provider, data collector, data miner, and decision maker. For each type of user, we focus on his privacy and how to protect sensitive information.

  Key-Words / Index Term
  Data Mining, Sensitive Information, Privacy-Preserving Data Mining Provenance, Anonymization , Privacy Auction, Antitracking

  References
  [1]. L. BrankovicRE, V. Estivill-Castro, "Privacy issues in knowledge discovery and data mining", in Proc. Austral. Inst.Comput. Ethics Conf., US, pp. 89-99, 1999.
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  [4]. Lei Xu, Chunxiao Jiang, Jian Wang, Jian Yuan, Yong Ren, "Information Security in Big Data: Privacy and Data Mining", Access, IEEE , vol.2, no.10, pp.1149,1176, 2014
  
  [5]. R. C.-W. Wong and A. W.-C. Fu, "Privacy-preserving data publishing: An overview", Synthesis Lectures Data Manage., vol. 2, no. 1, pp. 1-138, 2010.
  
  [6]. J. Xu, W. Wang, J. Pei, X. Wang, B. Shi, A. W.-C. Fu, "Utility-based anonymization for privacy preservation with less information loss", ACM SIGKDD Explorations Newslett., vol. 8, no.2, pp. 21-30, 2006.
  
  
  [7]. Tene and J. Polenetsky, "To track or „do not track‟: Advancing transparency and individual control in online behavioral advertising", Minnesota J. Law, Sci. Technol., Vol.5, no.1, pp. 281- 357, 2012.
  [8]. M.B. Malik, M.A. Ghazi, R. Ali, "Privacy preserving data mining techniques: Current scenario and future prospects", in Proc. 3rd Int. Conf. Computer Communication Technology, India, pp.26-32, 2012.
  
  [11]. S. Matwin, "Privacy-preserving data mining techniques: Survey and challenges", in Discrimination and Privacy in the Information Society, Berlin, pp. 209-221, 2013.
  
  [12]. E. Rasmusen, “Games and Information: An Introduction to Game Theory”, Cambridge University, USA, pp.1-347, 1994.
  
  [13]. V. Ciriani, S. De Capitani di Vimercati, S. Foresti, P. Samarati, "Microdata protection", in Secure Data Management in Decentralized Systems. USA, pp.291-321, 2007.
  
  [14]. D. C. Parkes, "Iterative combinatorial auctions: Achieving economic and computational efficiency", Ph.D. dissertation of Univeristy Pennsylvania, USA, pp.1-136, 2001.
  

  Citation
  S. Sathyamoorthy, "Data Mining and Information Security in Big Data," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.86-91, 2017

• Open Access   Article

  A Big Data Analytical Approach for Analyzing Temperature Dataset using Machine Learning Techniques

  J.V.N. Lakshmi, Ananthi Sheshasaayee

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.3 , pp.92-97, Jun-2017

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  Machine Learning algorithms are used to predictive analytics. These algorithms are put into practice for measuring the temperature data. To capture these data spark framework is being exploited. Machine learning applications are increasingly deployed not only to serve predictions using static models, but also as tightly-integrated components of feedback loops involving dynamic, real-time decision making. These applications pose a new set of requirements, none of which are difficult to achieve in isolation, but the combination of which creates a challenge for existing distributed execution frameworks: computation with millisecond latency at high throughput, adaptive construction of arbitrary task graphs, and execution of heterogeneous kernels over diverse sets of resources. We assert that a new distributed execution framework is needed for such ML applications. This paper describes evaluation of these algorithms on Hadoop, an open-source for spark implementation. The proposed methodology uses a temperature data set for analyzing the machine learning algorithms on spark data frame.

  Key-Words / Index Term
  Big Data; Machine Learning; HADOOP; Spark; Linear Regression; Gradient Boosting Tree

  References
  [1] J.V.N. Lakshmi, S. Ananthi, “A Theoretical Model for Big data Analytics using Machine Learning Algorithms”, In the Proceedings of the 2015 International Conference (WCI/ICACCI 2015), India, pp.632-636, 2015.
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  [3] J.V.N. Lakshmi “Hadoop Spark Framework For Machine Learning Using Python”, In the proceedings of the 2016 National Conference on ACSE conference, India, pp.9-14, 2017 .
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  [6] Walisa, Wichan, “An Adaptive ML on Map Reduce for improving performance of large scale data analysis 2013 Eleventh International Conference on ICT and Knowledge Engineering, Bangkok, pp.1-7, 2013
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  [10] M. Dhivya, D. Ragupathi, V.R. Kumar, “Hadoop Mapreduce Outline in Big Figures Analytics”, International Journal of Computer Sciences and Engineering, Vol.2, Issue.9, pp.100-104, 2014.
  

  Citation
  J.V.N. Lakshmi, Ananthi Sheshasaayee, "A Big Data Analytical Approach for Analyzing Temperature Dataset using Machine Learning Techniques," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.92-97, 2017

• Open Access   Article

  Analytical Study on Watershed Segmentation of the Pulmonary Lobes from Chest CT Scan Images

  K.K. Thanammal

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.3 , pp.98-103, Jun-2017

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  Abstract
  Medical imaging is the technique that is used to produce images of human body parts for clinical purpose. The CT images provide thorough information of structure of lungs, which could be used for better surgical preparation for treating lung diseases. This work proposes a method for segmentation from the given CT images. The lungs lobar markers are calculated by an analysis of the automatically labeled bronchial tree and lobes information from several anatomical features. The water shed segmentation method is analyzed for radiologists to give early diagnosing report of lung diseases.

  Key-Words / Index Term
  Image segmentation, Image analysis, Medical Image Segmentation, CT scan

  References
  [1]Stefano Diciotti, “The LOG Characteristic scale : A Consistent Measurement of Lung Nodule Size in CT imaging”, IEEE Transactions on Medical Imaging, Vol.29, No.2, pp.4-9, 2010.
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  [4]W. Michael, “Robust 3-D Airway Tree Segmentation for Image-Guided Peripheral Bronchoscopy,” IEEE Transactions on Medical Imaging, Vol.29, No.4, pp.4-9, 2010.
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  [6]Rui Shen, Student Member IEEE, Irene Cheng, Senior Member, IEEE and Anup Basu, Senior Member IEEE,“A Hybrid Knowledge-Guided Detection Technique for Screening of Infectious Pulmonary Tuberculosis from Chest Radiographs” ,IEEE Transactions on Biomedical Engineering, Vol. 57, No.11,November 2010.
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  [13]Yu Yang, Zhao Hong and Shenyang, “Medical Segmentation Using Sobolev Optical Flow”,IEEE 2007.
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  [15]Yoshinori Itali, Hyoungscop Kim, Seiji ishikawa, Shigehiko Katsuragawa, Takayuki Ishida, Katsumi Nakamuara and Akiyoshi Yamamoto, “Automatic Segmentation of Lung Areas Based on SNAKES and extraction of abnormal areas”, IEEE International Conference on Tools with Artificial Intelligence 2005.
  [16]Seiji Mori, Hyoungecop Kim, Seiji Ishijkawa, Nakamura and Akiyashi Yamamoto, “Segmentation of Lung Area and Extraction of Abnormal Area on CT Images of the Thorax”, IEEE Industrial Electronics Society, November 2-6,2004, Busan, Korea.
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  [20]Omid Talakoub, Javad Alirezaie and Paul Babyn, “Lung Segmentation in Pulmonary CT Images using Wavelet Transform”, ICASSP 2007.
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  Citation
  K.K. Thanammal, "Analytical Study on Watershed Segmentation of the Pulmonary Lobes from Chest CT Scan Images," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.98-103, 2017

• Open Access   Article

  Improved Consistency of Digital Image Watermarking Using RDWT and SVD

  M. Jamal, S. Mudassar, F. S. Mehmood, M. R. Rehman

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.3 , pp.104-106, Jun-2017

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  Abstract
  Digital Image Watermarking (DIW) is such a technique designed specifically for the protection of the images or data from illicit transformations. One of the best suited methods for patent protection and owner authentication is watermarking. In this document, a non-blind Digital Image Watermarking method was proposed that is the fusion of two different techniques i.e “Redundant Discrete Wavelet Transform (RDWT) and Singular Value Decomposition (SVD)” in YCbCr color space. A consistent way of protection was introduced as it showed more resistance than that of different wavelet based techniques. The proposed scheme was tested against different geometrical transformations (median filtering, noise addition, cropping etc) and provided better extraction of the watermark. The performance is increased that are shown using these parametric values i.e Mean Square Error (MSE), Normalized Correlation (NC) and Peak Signal-to-noise Ratio (PSNR), RMSE(Root Mean Square Error), NPCR(No. of Pixel change rate), SSIM(Structural Similarity Index).

  Key-Words / Index Term
  Redundant Discrete Wavelet Transform,Singular Value Decomposition,YCbCr Color Space

  References
  [1] Palanivel M, Shanmugam A, “Improved performance by parametrizing wavelet filters for digital image watermarking”, Signal & Image Processing, Vol.3, Issue.1, pp.2-9, 2012.
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  [6] A. Shahid, S. Badsha, R. Kabeer, “A Non-Blind Watermarking Scheme for Gray Scale Images in Discrete Wavelet Transform Domain using Two Subbands”, IJCSI, Vol. 9, Issue.5, pp.101-109, 2012.
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  Citation
  M. Jamal, S. Mudassar, F. S. Mehmood, M. R. Rehman, "Improved Consistency of Digital Image Watermarking Using RDWT and SVD," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.104-106, 2017

• Open Access   Article

  Identification of Factors and Techniques to Design and Develop Component Based Reliability Model

  Chander Diwaker, Pradeep Tomar

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.3 , pp.107-114, Jun-2017

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  Abstract
  As the industrial development grow, the number of developing software product also increases. The technologies change at very fast rate. It’s a problem to produce new software again and again with rapid change in market. With help of CBSE, the time of producing new software can be reduced, since the main factor in CBSE is reusability. More percentage use of reusable part may be used for producing new products without spending more cost and effort. This paper presents survey of different architecture based reliability models and the important parameters considered in making a reliability model. The paper covers different performance parameters such as failure rate, reliability and testing of failure that helps in measuring the performance of various component based reliability models.

  Key-Words / Index Term
  CBSE, Reliability Models, software reliability parameters

  References
  [1]. Manjula. C. M. Prasad, Lilly Flowrence, C.V. Srikrishna, “Overview of Software Reliability Models”, International Journal of Engineering and Management Research, Vol. 3, Issue.5, pp. 11-15, 2013.
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  Citation
  Chander Diwaker, Pradeep Tomar, "Identification of Factors and Techniques to Design and Develop Component Based Reliability Model," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.107-114, 2017

• Open Access   Article

  Use of Cloud Computing for Implementation of e-Governance Services

  Anand More, Priyesh Kanungo

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.3 , pp.115-118, Jun-2017

  Abstract

  Full-Text HTML

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  Citation

  Abstract
  E-Governance enables use of Information and Communication Technologies (ICT) for smooth working of government by providing transparency efficient working in immediate response to end the citizens in cost effective manner. The exiting e-Governance is server centric and is not able to address all users including rural and urban citizens. Governments today are still facing challenges like lack of financial and technological resources, digital divide, poor IT infrastructure and lack of management in delivering core services to their citizens. Cloud Computing is a new way of delivering Services to the customer using pay-per-use model which not only involves less capital expenditure with minimum upfront cost, but is also more user and environmental friendly. This paper presents a cloud based model for implementation of e-Governance services. We found that the implementation of cloud-based e-government architecture cost-saving of Information and Communication Technology (ICT) investment in our country.

  Key-Words / Index Term
  E-governance, Cloud computing, IaaS Cloud, Service Oriented Architecture (SOA), Virtualization, Web Enabled Technology, Cloud datacenter

  References
  [1]. A. More, P. Kanungo, “Various e-Governance Applications, Computing Architecture and Implementation Barriers”, Proceedings of the International Congress on Information and Communication Technology, Singapore pp.635-643, 2016.
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  [3]. C. Awasthi, P. Kanungo, “Resource Allocation Strategy for Cloud Computing Environment”, International Conference on Computer, Communication and Control (IC4), Indore, pp.1-5, 2015.
  [4]. H. K. Mehta, M. Chandwani, P. Kanungo, “On trust management and reliability of distributed scheduling algorithms”, ICoAC 2010, Chennai, pp.46-50, 2010.
  [5]. H.K. Mehta, P. Pawar, P. Kanungo, “A Two Level Broker System for Infrastructure as a Service Cloud”, Wireless Personal Communication, Vol.90, Issue.3, pp.1135–1147, 2016.
  [6]. Mohd.A. Salam, A.C. Pandey, “Mobile Cloud Computing: Taking Web-Based Mobile Applications to the Cloud”, International Journal of Computer Sciences and Engineering, Vol.2, Issue.1, pp.35-42, 2014.
  [7]. M. Ahmad, Z.A. Hasibuan, “Government Services Integration Based on Cloud Technology”, Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services, India, pp.303-306, 2012.
  [8]. P. Kanungo, “Efficient Resource Management in Cloud Computing Using Virtualization”, International Journal of Advanced Research in Computer and Communication Engineering. Vol.5, Issue.4, pp.650-652, 2016.
  [9]. R. Sharma, P. Kanungo, “An Intelligent Cloud Computing Architecture Supporting e-Governance”, 17th International Conference on Automation and Computing, Huddersfield, pp.1-5, 2011.
  [10]. N.B. Wagh, M. Kolhekar, "A Novel Approach utilizing Permutation Polynomials over integer rings as a Cryptological Application for Effective Encryption of Digital Images", International Journal of Computer Sciences and Engineering, Vol.5, Issue.1, pp.14-21, 2017.
  [11]. P. Kanungo, “Design Issues in Federated Cloud Architectures”, International Journal of Advanced Research in Computer and Communication Engineering Vol.5, Issue.5, pp.937-939, 2016.
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  Citation
  Anand More, Priyesh Kanungo, "Use of Cloud Computing for Implementation of e-Governance Services," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.115-118, 2017

• Open Access   Article

  Prediction of User Interest and Behaviour using Markov Model

  Neetu Anand, Tapas Kumar

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.3 , pp.119-123, Jun-2017

  Abstract

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  Citation

  Abstract
  Data mining techniques are foreseeable to be a more expedient tool for analysing user behaviour. A main research area in Web mining focused on learning Web users and their interactions within Websites is Web usage mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole.Children and youngsters have embraced the Internet in conducting their daily activities, and therefore, they use the Internet in ways that differ from elders. While elders tend to use the Internet to check for news, sports, weather, or research products and services, children and young adults are more likely to use the Internet to complete school assignments or play games. And while very high proportions of all age groups – adults and children alike – use e-mail; older children and young adults are doing so at much higher levels. Students are living their lives immersed in technology, ‘surrounded by and using computers, videogames, digital music players, video cams, cell phones, and all the other playthings and tools of the digital age’. So it becomes very important to analyze the pattern of access of internet usage of child to identify the next page in the access series which in turn help in behavioural analysis of children.

  Key-Words / Index Term
  Web mining, System monitoring, Behaviour pattern, Markov Model, Pre-processing

  References
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  Citation
  Neetu Anand, Tapas Kumar, "Prediction of User Interest and Behaviour using Markov Model," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.119-123, 2017