Abstract Next location prediction has recently gained great attention from researchers due to its importance in different application areas. Recent growth of location-based service applications vast domain influence such as traffic-flow prediction, weather forecast, and network resource optimization. Nowadays, the explosive increasing positioning sensor devices, big trajectory data are produced...

In this paper we present GeoVAQA, a Restricted Domain Spoken Question Answering system in the scope of the Spanish geography. The system consists of a webbased application that allows speech input questions about Spanish geography and sends back a concise textual answer. In our system, spoken questions are recognised by an automatic speech recognition (ASR) system. We have used RAMSES, a Spanis...

Archaeology is often defined as the study of past through material culture. As we enter Anthropocene, however, two parts this definition increasingly diverge. In Anthropocene archaeological record ceases to be observed from a distance, but something exist within. It not an assemblage culture, hyperobject vast temporal and geographical scope, in which ecofacts increase prominence role artefacts ...

The PAC-learning model is distribution-independent in the sense that the learner must reach a learning goal with a limited number of labeled random examples without any prior knowledge of the underlying domain distribution. In order to achieve this, one needs generalization error bounds that are valid uniformly for every domain distribution. These bounds are (almost) tight in the sense that the...

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If species' ranges are randomly shuffled within a bounded geographical domain free of environmental gradients, ranges overlap increasingly toward the center of the domain, creating a "mid-domain" peak of species richness. This "mid-domain effect" (MDE) has been controversial both in concept and in application. Empirical studies assess the degree to which the evolutionary, ecological, and histor...

The proliferation of remote sensing satellites has resulted in a massive amount images. However, due to human and material resource constraints, the vast majority images remain unlabeled. As result, it cannot be applied currently available deep learning methods. To fully utilize remaining unlabeled images, we propose Geographical Knowledge-driven Representation (GeoKR) method for improving netw...

This paper describes a proposal for OCL (Object Constraint Language) by adding geographical features to assist the geographical data modeling. OCL can be used to complement the diagrams when the UML constructors do not allow the specification of all requirements related to the application domain. The objective is to complement and validate conceptual data diagrams built with constructors of the...