Knowledge Extraction Using Auto Regression Method - A Tourist Information Extraction and Analytics

Arun M; Sumitha T; Maria L; Rejin N R

Research Article

Knowledge Extraction Using Auto Regression Method - A Tourist Information Extraction and Analytics

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@ARTICLE{10.4108/eai.27-1-2021.168503,
    author={Arun Manicka Raja M and Sumitha T and Maria Michael Visuwasam L and Rejin Paul N R},
    title={Knowledge Extraction Using Auto Regression Method - A Tourist Information Extraction and Analytics},
    journal={EAI Endorsed Transactions on Energy Web: Online First},
    volume={},
    number={},
    publisher={EAI},
    journal_a={EW},
    year={2021},
    month={1},
    keywords={Data Analytics, Prediction, Decision Making, Autoregression analysis, Aggregation, Knowledge Extraction, Data Scrabber, Aggressive-data sampling},
    doi={10.4108/eai.27-1-2021.168503}
}

Arun Manicka Raja M
Sumitha T
Maria Michael Visuwasam L
Rejin Paul N R
Year: 2021
Knowledge Extraction Using Auto Regression Method - A Tourist Information Extraction and Analytics
EW
EAI
DOI: 10.4108/eai.27-1-2021.168503

Arun Manicka Raja M¹, Sumitha T², Maria Michael Visuwasam L³^,*, Rejin Paul N R¹

1: Assistant Professor, Department of Computer Science and Engineering, R.M.K College of Engineering and Technology, Chennai, India
2: Assistant Professor, Department of Computer Science and Engineering, R.M.K Engineering College, Chennai, India
3: Assistant Professor, Department of Computer Science and Engineering, Rajalakshmi Institute of Technology, Chennai, India

*Contact email: micael_vm@yahoo.co.in

Abstract

Data analytics is played a vital role in Information Technology and Information Technology essential services ITeS for making effective decisions. The demand for tourism and prediction of tourist arrivals are important for tourism organisation. In this paper, we analyse tourist and extract information using data analytics process. The web data are processed using travellers’ details and applying an aggregate function to calculate the searching index. Here, we use the autoregression analytics method for accurate prediction. The tourist information is recorded and creates a system log for processing and extracting information. The interaction between each record and their logs are used for data processing and analytics model. This paper uses a recommendation system for the data analytics process and compares the results with existing models. Our proposed method provides good and accurate results for tourism organisation.

Keywords: Data Analytics, Prediction, Decision Making, Autoregression analysis, Aggregation, Knowledge Extraction, Data Scrabber, Aggressive-data sampling

Received: 2020-12-10
Accepted: 2021-01-15
Published: 2021-01-27
Publisher: EAI

: http://dx.doi.org/10.4108/eai.27-1-2021.168503

Copyright © 2021 Arun Manicka Raja M et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.