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

• Main Authors: Arun M, Sumitha T, Maria L, Rejin N R
• Format: Article
• Language: English
• Published: European Alliance for Innovation (EAI) 2021-09-01
• Series: EAI Endorsed Transactions on Energy Web
• Subjects: data analytics; prediction; decision making; autoregression analysis; aggregation; knowledge extraction; data scrabber; aggressive-data sampling
• Online Access: https://eudl.eu/pdf/10.4108/eai.27-1-2021.168503

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.