A survey of exploratory search systems based on LOD resources

The fact that the existing Web allows people to effortlessly share data over the Internet has resulted in the accumulation of vast amounts of information available on the Web.Therefore, a powerful search technology that will allow retrieval of relevant information is one of the main requirements for the success of the Web which is complicated further due to use of many different formats for storing information. Semantic Web technology plays a major role in resolving this problem by permitting the search engines to retrieve meaningful information. Exploratory search system, a special information seeking and exploration approach, supports users who are unfamiliar with a topic or whose search goals are vague and unfocused to learn and investigate a topic through a set of activities. In order to achieve exploratory search goals Linked Open Data (LOD) can be used to help search systems in retrieving related data, so the investigation task runs smoothly.This paper provides an overview of the Semantic Web Technology, Linked Data and search strategies, followed by a survey of the state of the art Exploratory Search Systems based on LOD.Finally the systems are compared in various aspects such as algorithms, result rankings and explanations

3D Cadastres Best Practices, Chapter 5: Visualization and New Opportunities

This paper proposes a discussion on opportunities offered by 3D visualization to improve the understanding and the analysis of cadastre data. It first introduce the rationale of having 3D visualization functionalities in the context of cadastre applications. Second the publication outline some basic concepts in 3D visualization. This section specially addresses the visualization pipeline as a driven classification schema to understand the steps leading to 3D visualization. In this section is also presented a brief review of current 3D standards and technologies. Next is proposed a summary of progress made in the last years in 3D cadastral visualization. For instance, user’s requirement, data and semiotics, and platforms are highlighted as main actions performed in the development of 3D cadastre visualization. This review could be perceived as an attempt to structure and emphasise the best practices in the domain of 3D cadastre visualization and as an inventory of issues that still need to be tackled. Finally, by providing a review on advances and trends in 3D visualization, the paper initiates a discussion and a critical analysis on the benefit of applying these new developments to cadastre domain. This final section discusses about enhancing 3D techniques as dynamic transparency and cutaway, 3D generalization, 3D visibility model, 3D annotation, 3D data and web platform, augmented reality, immersive virtual environment, 3D gaming, interaction techniques and time

A reference architecture for big data systems

Over dozens of years, applying new IT technologies into organizations has always been a big concern for business. Big data certainly is a new concept exciting business. To be able to access more data and empower to analysis big data requires new big data platforms. However, there still remains limited reference architecture for big data systems. In this paper, based on existing reference architecture of big data systems, we propose new high level abstract reference architecture and related reference architecture notations, that better express the overall architecture. The new reference architecture is verified using one existing case and an additional new use case

3D Cadastre visualization and dissemination: Most recent progresses and future directions

The 3D Cadastre has been investigated from many viewpoints (including legal, organizational and technical). However, to date little research has focused specifically on visualizationrelated aspects despite the value-added of the third dimension. The paper first proposes an overview of progress made in the last five years in 3D cadastral visualization. The authors then summarize discussions at the 2014 3D Cadastre workshop regarding future research and development on the topic. This synthesis is complemented by a broad review of the most recent advances in 3D visualization beyond the 3D cadastral domain, with the goal of providing a number of important directions for further work, allowing researchers, developers and users to consolidate their respective activities, and encouraging collaboration

Argumentation Mining in User-Generated Web Discourse

The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal with actual Web data and take up the challenges given by the variety of registers, multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We bridge the gap between normative argumentation theories and argumentation phenomena encountered in actual data by adapting an argumentation model tested in an extensive annotation study. (iii) We create a new gold standard corpus (90k tokens in 340 documents) and experiment with several machine learning methods to identify argument components. We offer the data, source codes, and annotation guidelines to the community under free licenses. Our findings show that argumentation mining in user-generated Web discourse is a feasible but challenging task.Comment: Cite as: Habernal, I. & Gurevych, I. (2017). Argumentation Mining in User-Generated Web Discourse. Computational Linguistics 43(1), pp. 125-17

Deliverable D9.3 Final Project Report

This document comprises the final report of LinkedTV. It includes a publishable summary, a plan for use and dissemination of foreground and a report covering the wider societal implications of the project in the form of a questionnaire

Models to represent linguistic linked data

As the interest of the Semantic Web and computational linguistics communities in linguistic linked data (LLD) keeps increasing and the number of contributions that dwell on LLD rapidly grows, scholars (and linguists in particular) interested in the development of LLD resources sometimes find it difficult to determine which mechanism is suitable for their needs and which challenges have already been addressed. This review seeks to present the state of the art on the models, ontologies and their extensions to represent language resources as LLD by focusing on the nature of the linguistic content they aim to encode. Four basic groups of models are distinguished in this work: models to represent the main elements of lexical resources (group 1), vocabularies developed as extensions to models in group 1 and ontologies that provide more granularity on specific levels of linguistic analysis (group 2), catalogues of linguistic data categories (group 3) and other models such as corpora models or service-oriented ones (group 4). Contributions encompassed in these four groups are described, highlighting their reuse by the community and the modelling challenges that are still to be faced