Volume-5 , Issue-2 , Apr 2017, ISSN 2320-7639 (Online) Go Back

• Open Access   Article

  Twitter Data Streaming and apturing for Tourism Dashboard application

  H.S. Albusaidi, P.K. Udupi, V. Dattana

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.2 , pp.63-66, Apr-2017

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  Information and communication technology intervention, advancement in internet technology narrowed down the geographical barrier for information Interchange [1]. Tourism sector is one of the primary benefitted sector due to rapid changes of information technology. Introduction of smart tourism, online transactions, visually stunning virtual world creation of tourism places, availability of immediate information further accelerated the expansion of tourism sector and driven tourism sector from traditional environment to technology driven business environment. Social media usages, tourism dashboards, media streaming ensured to achieve greater success for tourism sectors [2]. This paper identifies and evaluates methods of information capturing and processing pertain to tourism sector. The paper also explores the possibility of social media data streaming, extraction and mining [3] with the future scope of research towards visualization of information through dashboards.

  Key-Words / Index Term
  Twitter API, Twitter sentiments analysis, Data analytic, Dash Board, Smart Tourism, Big data, Oman Tourism, Oman economic, Twitter, Twitter API, Twitter hashtag

  References
  [1] S. Dutta, T. Geiger, B. Lanvin, “The Global Information Technology Report 2015 ICTs for Inclusive Growth”, World Economic Forum, Vol. 1, No. 1, pp.80-85, 2015
  [2] K. A. Manap, “The Role of User Generated Content (UGC) in Social Media for Tourism Sector”, WEI International Academic Conference Proceedings , Turkey, pp 52-58, 2013.
  [3]A. Abbasi, T. H. Rashidi, M. Maghrebi, S. T. Waller , “Utilising Location Based Social Media in Travel Survey Methods:bringing Twitter data into the play”, Proceedings of the 8th ACM SIGSPATIAL International Workshop on Location-Based Social Networks, USA, pp.1-12, 2015
  [4] R. Turner, “Travel and tourism Economic Impact 2015 – world”, World Travel & Tourism Council, United Kingdom, pp.1-24, 2015.
  [5] S. Cerutti, E. Piva, “The Role of Tourists’ Feedback in the Enhancement of Religious Tourism Destinations”, International Journal of Religious Tourism and Pilgrimage, Vol.4, Issue.3, pp. 6-16, 2016.
  [6] K.M. Otto, R L. Cheng, “ Big Data Stream Analytics for Near Real-Time Sentiment Analysis”, Journal of Computer and Communications, Vol.3, Issue.5, pp. 189-195, 2015.
  [7] B. Liu, “Sentiment Analysis and Opinion Mining”,Synthesis Lectures on Human Language Technologies, Vol. 5, No. 1 , pp.1-167, 2012.
  [8] H. Kwak, C. Lee, H.Park, S.Moon, What is Twitter, a Social Network or a News Media?, World Wide Web Conference, USA, 2010.
  [9] A. Bifet, R. Cavalda, “Detecting Sentiment Change in Twitter Streaming Data”, Proceedings of the Second Workshop on Applications of Pattern Analysis, Spain, pp. 5-11,2011
  [10] C. Ashley, P. D. Brine, A. Lehr, H. Wilde, “The Role of the tourism sector in expanding economic opportunity”, The Role of the tourism sector in expanding economic opportunity, USA, pp. 1-56, 2007.
  

  Citation
  H.S. Albusaidi, P.K. Udupi, V. Dattana, "Twitter Data Streaming and apturing for Tourism Dashboard application," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.2, pp.63-66, 2017

• Open Access   Article

  A Survey on Sentiment Analysis

  C. Nanda, M. Dua

  Survey Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.2 , pp.67-70, Apr-2017

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  Sentiment analysis is an emerging area of Natural Language Processing and is observed as an interesting and challenging research problem as a result of remarkable growth of the numerous data on the web, social media present in each and every nook and corner in today’s world.Internet is the most basic platform for the users to give their opinion about any particular thing whether it is a product, news, blog, movie or anything else. Therefore sentiment analysis has got much attention in past few years to track what people think or feel about a product. It is used to tackle the problem of sentiment category polarization. This is a survey that how Semantic Analysis can be effectively taken in consideration for carrying out sentiment analysis.

  Key-Words / Index Term
  Machine Learning, Natural Language Processing, opinion mining, Product reviews and Sentiment analysis

  References
  [1]. A. Das, S. Bandopadaya, “SentiWordnet for Bangla”, Knowledge Sharing Event-4:Task, Vol.2, pp.1-8, 2010.
  [2]. A. Das, S. Bandopadaya, “SentiWordnet for Indian Languages”, 8th Workshop on Asian Language Resources, China, pp.56-63, 2010.
  [3]. Y. Sharma, V. Mangat, M. Kaur, “A practical Approach to Semantic Analysis of Hindi tweets”, 1st International Conference on Next Generation Computing Technologies(NGCT-2015), India, pp.677-680, 2015.
  [4]. Y. Huangfu, Guoshiwu, Y. Li, P. Hu, “Än Improved Sentiment Analysis Algorithm for Chinese news”, 12th International Conference on Fuzzy Systems and Knowedge Discovery(FSKD), Zhangjiajie pp.1366-1371, 2015.
  [5]. P. Bhoir, S. Kolte, “Sentiment Analysis of Movie Reviews using Lexicon approach”, IEEE International Conference on Computational Intelligence and Computing Research, Madurai pp.1-6, 2015.
  [6]. X. Yan, T. Huang, “Tibentian Sentence sentiment analysis based on the maximum entropy model”,10th International Conference on Broadband and wireless Computing, Communication and Application, Krakow, pp 594-597, 2015.
  [7]. C.P. Gupta, B. Krishan, “Detecting Sentiment in Nepali texts: A bootstrap approach for Sentiment Analysis of texts in the Nepali language”, International Conference on Cognitive Computing and Information Processing (CCIP), Noida, pp 1-4, 2015.
  [8]. S.B. Moralwar, S.N. Deshmukh, “Different Approaches of Sentiment Analysis”, International Journal of Computer Sciences and Engineering, Vol.3, Issue.3, pp.160-165, 2015.
  [9]. C. Priyanka, D. Gupta, “Fine Grained Sentiment Classification of Customer Reviews Using Computational Intelligent Technique”, International Journal of Engineering and Technology, Vol.7, No.4, pp.1453-1468, 2015.
  [10]. D. Chafale, A. Pimpalkar, “Review on Developing Corpora for Sentiment Analysis Using Plutchik’s Wheel of Emotions with Fuzzy Logic”, International Journal of Computer Sciences and Engineering, Vol.2, Issue.10, pp.14-18, 2014.
  

  Citation
  C. Nanda, M. Dua, "A Survey on Sentiment Analysis," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.2, pp.67-70, 2017

• Open Access   Article

  A Comparative Based Review on Image Segmentation of Medical Image and its Technique

  P. Umorya, R. Singh

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.2 , pp.71-76, Apr-2017

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  This paper presents a survey on Image segmentation. In Image segmentation dividing an image into many regions is the segmentation process. Segmentation Process provides a way to find a particular region of point inside an image. This process provides help in understanding the process in a meaningful way. In this paper, a survey of various techniques of image segmentation their algorithm that helps in finding Medical images.

  Key-Words / Index Term
  Fuzzy C Means (FCFS); MRI; Region based segmentation; Line detection

  References
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  Citation
  P. Umorya, R. Singh, "A Comparative Based Review on Image Segmentation of Medical Image and its Technique," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.2, pp.71-76, 2017

• Open Access   Article

  Analysis of Different Software Testing Techniques

  Suresh Jat, Pradeep Sharma

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.2 , pp.77-80, Apr-2017

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  A Software testing is an action which is intended for estimate feature or an ability of a program and guarantee that it meets the necessary effect. Software produced will never be faultless without being tested and approved. This makes us discover a technique for testing concealed bugs at different stages by a superior technique. Testing is a procedure where we can spot concealed bugs, code faults or any unused code in certain software. Currently, there are lots of techniques being used for testing faults in software; among them, most proficient techniques for testing software are black-box testing, white-box testing, and gray-box testing. In sort to take testing, via various techniques involves extreme use of resources and time. Many techniques have resulted in duplication of effort because they locate the same kind of faults. For this intention, appropriate selection of testing techniques is essential. So there is required to evaluate testing techniques. Most of the empirical study had performed to estimate software testing techniques in terms of accuracy and efficiency. In this paper, we have illustrated and compared the three most common and frequently used software testing techniques for discovering errors; they are white-box testing, black box testing, and grey-box testing.

  Key-Words / Index Term
  Software Testing; Black Box Testing, Grey Box Testing, White Box Testing

  References
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  [2] S. Kumar, H. Trivedi, “Software Testing Techniques”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume-2, pp. 433-438, Oct 2012
  [3] B. Beizer, “Software Testing Techniques” ,DreamTech Publisher , Edition-II ,India, pp. 13-247,2009,
  [4] C. Sharma, S. Sabharwal, R. Sibal , “A Surveyon Software Testing Techniques using Genetic Algorithm”, International Journal of Computer Science,Voume-10,Issue-1,pp.381-393,2013.
  [5] S. Kannan, T. Pushparaj, "A study on variations of Bottlenecks in Software Testing", International Journal of Computer Sciences and Engineering, Vol.2, Issue.5, pp.8-14, 2014.
  [6] M. Tyagi, S. Malhotra, “A Review of Empirical Evaluation of Software Testing Techniques with Subjects”, International Journal of Advanced Research in Computer Engineering & Technology, Volume-3, Issue 2,pp.519-523, 2014.
  [7] N. Juristo, S. Vegas, M. Solari, S. Abrahao and I. Ramos, “Comparing the effectiveness of equivalence partitioning, branch testing and code reading by stepwise abstraction applied by subjects” ,IEEE Conference on Software Testing, Volume-1, pp. 330-339, 2012.
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  [13] M.E. Khan, F. Khan, “A Comparative Study of White Box, Black Box and Grey Box Testing Techniques”, International Journal of Advanced Computer Science and Applications, volume-3, Issue-6, pp.22-25, 2012
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  Citation
  Suresh Jat, Pradeep Sharma, "Analysis of Different Software Testing Techniques," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.2, pp.77-80, 2017

• Open Access   Article

  Investigation of Manual and Automation Testing using Assorted Approaches

  Shruti Malve, Pradeep Sharma

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.2 , pp.81-87, Apr-2017

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  Abstract
  Testing means “revealing a person`s capabilities by putting them under strain; challenging”. Software testing exist a vast domain, but it may be classify into two way: manual testing and automated testing. In manual testing, test cases are executed (run) manually without any help from tools/scripts, but with automated testing, test cases are executed (run) with the help of tools, scripts, and software. Software testing is expensive, labor intensive and consume more time in a software development life cycle. There was forever a need in software testing to decrease the testing time. The type of testing (manual or automated) depends on various factors, adding project need, budget, timeline, expertise, and suitability. Three fundamental factors of any project are of course time, cost, and quality – the objective of any successful project is to diminish the cost and time required to complete it successfully while maintaining quality output. When it comes to testing, one type may accomplish this goal better than the other. This paper presents the concept of automation and manual testing and problem with manual testing and benefit of automatic testing. The main objective of this paper is to conduct a comparative study of Manual and Automation testing Method based on Accuracy, Bug detection, Efforts, cost and Time.

  Key-Words / Index Term
  Software Testing, Manual Testing, Automation Testing

  References
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  Citation
  Shruti Malve, Pradeep Sharma, "Investigation of Manual and Automation Testing using Assorted Approaches," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.2, pp.81-87, 2017

• Open Access   Article

  Scrutiny to Effectiveness of Various Software Process Model

  Chetna Sisodiya, Pradeep Sharma

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.2 , pp.88-93, Apr-2017

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  Abstract
  A software process model is summarized representation of a process. There are different software process models. It is very difficult to choose a model for the project and the developer choose the best effective model for the software. Developer phase many problem to develop a software, they confuse between different software model, which model is best to develop a software. This research describe five generic software process model and represent the effectiveness of different software process models according to the defects and features of each models. Various software models have been analyzed here with different techniques and the five software process models are waterfall, Agile, V-shaped, spiral and Iterative model. Therefore, this research goal is to represent effectiveness of different software process models and estimate best effective software process models according to the defects and features of each model. The main problem are, which model is more effective. How do we suggest one model for development and which method we use to compare all these models? Which is depend some features of a model. Methodology has been used to solve this problem here and the research methodology consists of five different methods combined. A combination of methods is used to provide a wide scope of information and opinions within the research. In this analysis the effectiveness of these models is also explained on the basis of requirement, planning, design and implementation.

  Key-Words / Index Term
  Software process models, Waterfall model, Iteration model, V-shaped model, spiral model and agile model, requirement, planning, design and implementation

  References
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  Citation
  Chetna Sisodiya, Pradeep Sharma, "Scrutiny to Effectiveness of Various Software Process Model," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.2, pp.88-93, 2017