An Ontology for Service Semantic Interoperability in the Smartphone-Based Tourist Trip Planning System

This paper presents an ontology-based approach for semantic interoperability tourist trip planning services. The proposed ontology describes a tourist, an attraction route and context information about tourist and his/her environment. This ontology is developed within the Tourist Trip Planning System, which consists of a set of interacting services. All services work accordingly to the proposed ontology which leads to service semantic interoperability and allows to increase interaction speed between them

Marketing of Tourism Destination in the Context of Tiger Safari

Tiger tourism plays a significant role in the overall scenario of Indian tourism. The forest destination managers face a major challenge in satisfying their visitors since tigers are elusive by nature and most of the time tourists return dissatisfied without sighting a tiger after a forest safari. This paper is the first scientific study of its kind based on empirical data in the context of tiger tourism and proposed a model to identify the optimum path in the forest with a higher probability of tiger sighting

Context-Driven Tour Planning Service: An Approach Based on Synthetic Coordinates Recommendation

The paper presents a hybrid context/model-based tour planning service aimed at recommendation generation by providing the tourists the sequence of attractions that are more interesting for him/her based on previous activity with the service. The service is developed based on SCoR recommender system that is aimed at recommendation generation based on calculating the synthetic coordinate between tourists of the service in according with their ratings. SCoR is a model-based collaborative filtering algorithm, constructing a model based on the user's personal ratings as well as exploiting collaborative information from the ratings of the rest of the users. One of the main advantages of SCoR's model is its ability to incorporate additional training information (new ratings) without having to perform the training process from the beginning. The prototype has been implemented for Android-based smartphone and has been evaluated for St. Petersburg city. For the evaluation the attraction database has been formed that includes attraction location information from OpenStreeMaps platform, location description and media from Wikipedia, and ratings from Google Place