The vast amount of information creates a scientific and technological challenge: to develop innovative tools and applications which provide personalized and targeting tourism information to visitors by exploiting the aforementioned multiple information sources. The basic premise of the project “ΑΝΑΔΕΙΞΤΟ (PROMOTE)” is that such a personalized and targeted tourist information emerges as a solution of a optimization problem subject to proper constraints limitations within a big data framework maintaining protection of personal data.
Such a solution will be sought at the server side by leveraging a) hypergraphs, which can capture the correlations between the multiple heterogeneous sources, for tourism recommendation; and b) dynamic collaborative filtering models (e.g., Kalman filtering, dynamic factorization of hypergraphs) , which take into account the time evolution of each low-dimensional latent component, representing it as multidimensional Brownian motion. A connection between these two driving forces can be established through graphical models and approximate/variational inference. At the client side, it is necessary to develop mobile phone applications (e.g., i-phone/android apps) for applications for tablets that adhere to human-centered interaction within the truly multilingual tourism framework.
An open problem in such a human-centered interaction is keyword spotting (i.e., the detection of landmarks, proper names) in a noisy multi-lingual environment. In the project “ΑΝΑΔΕΙΞΤΟ (PROMOTE)”, a solution to this problem will be sought by employing deep neural networks. Deep neural networks are also suitable for text/speech generation to describe a landmark or attraction in language, missing from a Wikipedia entry. System integration will also address the minimization of the amount of data to be transferred between clients and serve, e.g., by enabling feature extraction from video, images, music clips at the client applications. At both server and client sides, the challenges to be addressed are challenges that will be addressed are important and timely, since the entire concept of the project embraces cutting edge research topics and technologies.
The enormous amount of information creates a scientific and technological challenge: to develop innovative tools and applications to suggest personalized and targeted tourist information to visitors by exploiting elements from the above-mentioned multiple sources of different texture. The basic premise of the project is that the personalized and targeted tourist information provided to visitors is a solution to a complex optimization problem with restrictions in a large compromise environment with the protection of personal data.
Subjective experiences, as recorded on videos, photos, music clips, tags, texts, ratings, geo-location traces, user profiles constitute indeed big data in terms of volume, veracity, velocity, but also added value for the tourism industry as well as individual visitors.