The wine industry has evolved thanks to the introduction of digital technologies in every aspect of the wine production chain and the emerging need of the food industry for qualitative, sustainable, ...and safe products. As a result, the incorporation of digital services that facilitate access to related data of wine products is crucial for wine enterprises to increase their competitiveness, customer loyalty, and market share in this highly competitive domain. In this work, we present the Message-in-a-Bottle (MiB) ecosystem, which exploits multi-dimensional and multi-sourced data for creating engaging and interactive stories around wine labels. We especially focus on the sustainability and safety issues in the wine industry and showcase how MiB addresses them. The ecosystem is developed in the context of the MiB project and has already started to be available in the market through the Lyrarakis wine enterprise.
Faceted exploration of RDF/S datasets: a survey Tzitzikas, Yannis; Manolis, Nikos; Papadakos, Panagiotis
Journal of intelligent information systems,
04/2017, Letnik:
48, Številka:
2
Journal Article
Recenzirano
The amounts of available Semantic Web (SW) data (including Linked Open Data) constantly increases. Users would like to browse and explore effectively such information spaces without having to be ...acquainted with the various vocabularies and query language syntaxes. This paper discusses the work that has been done in the area for the case of RDF/S datasets, with emphasis on session-based interaction schemes for exploratory search. In particular, it surveys the related works according to various aspects, such as assumed user goals, structuring of the underlying information space, generality and configuration requirements, and various (state space-based) features of the navigation structure. Subsequently it introduces a small but concise formal model of the interaction (that captures the core functionalities) which is used as reference model for describing what the existing systems support. Finally the paper describes the evaluation methods that have been used. Overall, the presented analysis aids the understanding and comparison of the various different approaches that have been proposed so far.
Biodiversity data is characterized by its cross-disciplinary character, the extremely broad range of data types and structures, and the variety of semantic concepts that it encompasses. Furthermore ...there is a plethora of different data sources providing resources for the same piece of information in a heterogeneous way. Even if we restrict our attention to Greek biodiversity domain, it is easy to see that biodiversity data remains unconnected and widely distributed among different sources.
To cope with these issues, in the context of the LifeWatch Greece project, i) we supported cataloguing and publishing of all the relevant metadata information of the Greek biodiversity domain, ii) we integrated data from heterogeneous sources by supporting the definitions of appropriate models, iii) we provided means for efficiently discovering biodiversity data of interest and iv) we enabled the answering of complex queries that could not be answered from the individual sources. This work has been exploited, evaluated and scientificaly confirmed by the biodiversity community through the services provided by the LifeWatch Greece portal.
Theophrastus is a system that supports the automatic annotation of (web) documents through entity mining and provides exploration services by exploiting Linked Open Data (LOD), in real-time and only ...when needed. The system aims at assisting biologists in their research on species and biodiversity. It was based on requirements coming from the biodiversity domain and was awarded the first prize in the Blue Hackathon 2013. Theophrastus has been designed to be highly configurable regarding a number of different aspects like entities of interest, information cards and external search systems. As a result it can be exploited in different contexts and other areas of interest. The provided experimental results show that the proposed approach is efficient and can be applied in real-time.
Gravitational waves (GWs) were observed for the first time in 2015, one century after Einstein predicted their existence. There is now growing interest to extend the detection bandwidth to low ...frequency. The scientific potential of multi-frequency GW astronomy is enormous as it would enable to obtain a more complete picture of cosmic events and mechanisms. This is a unique and entirely new opportunity for the future of astronomy, the success of which depends upon the decisions being made on existing and new infrastructures. The prospect of combining observations from the future space-based instrument LISA together with third generation ground based detectors will open the way toward multi-band GW astronomy, but will leave the infrasound (0.1-10 Hz) band uncovered. GW detectors based on matter wave interferometry promise to fill such a sensitivity gap. We propose the European Laboratory for Gravitation and Atom-interferometric Research (ELGAR), an underground infrastructure based on the latest progress in atomic physics, to study space-time and gravitation with the primary goal of detecting GWs in the infrasound band. ELGAR will directly inherit from large research facilities now being built in Europe for the study of large scale atom interferometry and will drive new pan-European synergies from top research centers developing quantum sensors. ELGAR will measure GW radiation in the infrasound band with a peak strain sensitivity of 3.3×10−22/Hz at 1.7 Hz. The antenna will have an impact on diverse fundamental and applied research fields beyond GW astronomy, including gravitation, general relativity, and geology.
Current proposals for preference-based information access seem to ignore that users should be acquainted with the information space and the available choices for describing effectively their ...preferences. Furthermore users rarely formulate complex (preference or plain) queries. The interaction paradigm of Faceted Dynamic Taxonomies (FDT) allows users to explore an information space and to restrict their focus without having to formulate queries. Instead the users can restrict their focus (object set, or set of choices in general) gradually through a simple set of actions, each corresponding to a more refined query (formulated on-the-fly) which can be enacted by a simple click. In this paper we extend this interaction paradigm with actions that allow users to dynamically express their preferences. The proposed model supports progressive preference elicitation, inherited preferences and scope-based resolution of conflicts over single or multi-valued attributes with hierarchically organized values. Finally we elaborate on the algorithmic perspective and the applicability of the model over large information bases.
Automatic deception detection is a crucial task that has many applications both in direct physical and in computer-mediated human communication. Our focus is on automatic deception detection in text ...across cultures. In this context, we view culture through the prism of the individualism/collectivism dimension, and we approximate culture by using country as a proxy. Having as a starting point recent conclusions drawn from the social psychology discipline, we explore if differences in the usage of specific linguistic features of deception across cultures can be confirmed and attributed to cultural norms in respect to the individualism/collectivism divide. In addition, we investigate if a universal feature set for cross-cultural text deception detection tasks exists. We evaluate the predictive power of different feature sets and approaches. We create culture/language-aware classifiers by experimenting with a wide range of n-gram features from several levels of linguistic analysis, namely phonology, morphology and syntax, other linguistic cues like word and phoneme counts, pronouns use, etc., and token embeddings. We conducted our experiments over eleven data sets from five languages (English, Dutch, Russian, Spanish, and Romanian), from six countries (United States of America, Belgium, India, Russia, Mexico, and Romania), and we applied two classification methods, namely logistic regression and fine-tuned BERT models. The results showed that the undertaken task is fairly complex and demanding. Furthermore, there are indications that some linguistic cues of deception have cultural origins and are consistent in the context of diverse domains and data set settings for the same language. This is more evident for the usage of pronouns and the expression of sentiment in deceptive language. The results of this work show that the automatic deception detection across cultures and languages cannot be handled in unified manners and that such approaches should be augmented with knowledge about cultural differences and the domains of interest.
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