Book Chapter10.1007/978-3-319-07443-6_58
Combining Linked Data and Statistical Information Retrieval
Ricardo Usbeck
- 25 May 2014
- pp 845-854
TL;DR: In this paper, the authors outline an approach for creating a web-scale, precise and efficient information system capable of understanding keyword, entity and natural language queries by using Semantic Web methods and Linked Data.
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Abstract: Being a part of the Information Age, users are challenged with a tremendously growing amount of Web data which generates a need for more sophisticated information retrieval systems The Semantic Web provides necessary procedures to augment the highly unstructured Web with suitable metadata in order to leverage search quality and user experience In this article, we will outline an approach for creating a web-scale, precise and efficient information system capable of understanding keyword, entity and natural language queries By using Semantic Web methods and Linked Data the doctoral work will present how the underlying knowledge is created and elaborated searches can be performed on top
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Citations
Exploratory querying of SPARQL endpoints in space and time
Simon Scheider,Simon Scheider,Auriol Degbelo,Rob Lemmens,Corné P. J. M. van Elzakker,Peter Zimmerhof,Nemanja Kostic,Jim Jones,Gautam Banhatti +8 more
TL;DR: This article proposes design principles for SPEX (Spatio-temporal content explorer), a tool which helps people unfamiliar with the content of SPARQL endpoints or their syntax to explore the latter in space and time, and proposes a way to deal with challenges by interactive visual query construction.
•Posted Content
Towards an Interoperable Ecosystem of AI and LT Platforms: A Roadmap for the Implementation of Different Levels of Interoperability
Georg Rehm,Dimitrios Galanis,Penny Labropoulou,Stelios Piperidis,Martin Welß,Ricardo Usbeck,Joachim Köhler,Miltos Deligiannis,Katerina Gkirtzou,Johannes Fischer,Christian Chiarcos,Nils Feldhus,Julián Moreno-Schneider,Florian Kintzel,Elena Montiel,Víctor Rodríguez Doncel,John P. McCrae,David Laqua,Irina Patricia Theile,Christian Dittmar,Kalina Bontcheva,Ian Roberts,Andrejs Vasiljevs,Andis Lagzdiņš +23 more
TL;DR: This work devise five different levels (of increasing complexity) of platform interoperability that are suggested to implement in a wider federation of AI/LT platforms.
23
Contextual Data Collection for Smart Cities.
Henrique Santos,Vasco Furtado,Paulo Pinheiro,Deborah L. McGuinness +3 more
- 01 Jan 2015
TL;DR: In this paper, the authors leverage the Human-Aware Sensor Network Ontology (HASNetO) to build an architecture for data collected in urban environments and discuss the use of HASNetO and the supporting infrastructure to manage both data and metadata in support of the City of Fortaleza.
A service-oriented search framework for full text, geospatial and semantic search
Andreas Both,Axel-Cyrille Ngonga Ngomo,Ricardo Usbeck,Denis Lukovnikov,Christiane Lemke,Maximilian Speicher +5 more
- 04 Sep 2014
TL;DR: This paper describes search services that provide specific search functionality via a generalized interface inspired by RDF and introduces an application layer on top of these services that enables to query them in a unified way.
Human-Aware Sensor Network Ontology: Semantic Support for Empirical Data Collection.
Paulo Pinheiro,Deborah L. McGuinness,Henrique Santos +2 more
- 01 Jan 2015
TL;DR: The Human-Aware Sensor Network Ontology (HasNetO) as mentioned in this paper is a comprehensive alignment and integration of a sensing infrastructure ontology and a provenance ontology, which has been under development for more than one year and has been reviewed, shared and used by multiple scientific communities.
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