Ecotourism Recommendations based on Sentiments Using Skyline Query and Apache-Spark

The selection of an ecotourism destination is a challenging service in online transaction. process must consider personal considerations, such as costs or distance and interesting eco-points like specific sceneries the rare unique picturesque landscapes. Only few tourists have required information for any particular local resources. A proposed recommender system solution to get advice on appropriate destinations based sentiments according their preferences. This work skyline query method Skyline Sort Filter algorithm Apache Spark cluster computing framework build recommendations. sentiment analysis using SentiStrength obtain accuracy 78.3% F-arithmetic 84.5%. These results indicate can detect positive responses from visitors ensure best recommendations with tourist. three computer nodes has 213.7 times faster execution time correlated data, 240 independent 288.1 anti-correlated data than single method.