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Linked Data
The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including cov...
Efficient Optimization and Processing of Queries Over Text-rich Graph-structured Data
Many databases today capture both, structured and unstructured data. Making use of such hybrid data has become an important topic in research and industry. The efficient evaluation of hybrid data queries is the main topic of this thesis. Novel techniques are proposed that improve the whole processing pipeline, from indexes and query optimization to run-time processing. The contributions are evaluated in extensive experiments showing that the proposed techniques improve upon the state of the art.
Publishing and Consuming Linked Data
This dissertation addresses several problems in the context of publishing and consuming Linked Data. It describes these problems from the perspectives of three stakeholders: the Linked Data provider, developer and scientist. The Linked Data provider is faced with impractical data re-use and costly Linked Data hosting solutions. Developers face difficulties in finding, navigating and using Linked Datasets. Scientists lack the resources and methods to evaluate their work on Linked Data at large. This dissertation presents a number of novel approaches that address these issues, such as: - The LOD Laundromat: a centralized service that re-publishes cleaned, queryable and structurally annotated L...
Flexible Integration and Efficient Analysis of Multidimensional Datasets from the Web
If numeric data from the Web are brought together, natural scientists can compare climate measurements with estimations, financial analysts can evaluate companies based on balance sheets and daily stock market values, and citizens can explore the GDP per capita from several data sources. However, heterogeneities and size of data remain a problem. This work presents methods to query a uniform view - the Global Cube - of available datasets from the Web and builds on Linked Data query approaches.
Why Context Matters
In the last few years there has been a growing interest in using computers not only for quantitative but also for qualitative content analyses of various kinds of texts and unstructured interviews (Fielding and Lee 1993, Kelle 1998, Kuckartz 2001, Miles and Huberman 2005, Lewins and Silver 2007). This trend has given rise to the development of new software products such as MAXqda, NVivo, NUD. IST, and ATLAS. ti, which can be used for automatic coding, text retrieval, hyp- linking of related text segments, etc. Some of these programs such as ATLAS. ti or MAXqda even allow to represent the results of qualitative content analyses in graphical form as semantic networks of coded texts (Sowa 1984:...
Reasoning Techniques for the Web of Data
Linked Data publishing has brought about a novel “Web of Data”: a wealth of diverse, interlinked, structured data published on the Web. These Linked Datasets are described using the Semantic Web standards and are openly available to all, produced by governments, businesses, communities and academia alike. However, the heterogeneity of such data – in terms of how resources are described and identified – poses major challenges to potential consumers. Herein, we examine use cases for pragmatic, lightweight reasoning techniques that leverage Web vocabularies (described in RDFS and OWL) to better integrate large scale, diverse, Linked Data corpora. We take a test corpus of 1.1 billion RDF...
Concepts in Action
This open access book is a timely contribution in presenting recent issues, approaches, and results that are not only central to the highly interdisciplinary field of concept research but also particularly important to newly emergent paradigms and challenges. The contributors present a unique, holistic picture for the understanding and use of concepts from a wide range of fields including cognitive science, linguistics, philosophy, psychology, artificial intelligence, and computer science. The chapters focus on three distinct points of view that lie at the core of concept research: representation, learning, and application. The contributions present a combination of theoretical, experimental, computational, and applied methods that appeal to students and researchers working in these fields.
Reasoning Web
This book contains a collection of thoroughly revised tutorial papers based on lectures given by leading researchers at the 4th International Summer School on the Reasoning Web, held in Venice, Italy, in September 2008. The objective of the book is to provide a coherent introduction to semantic web methods and research issues with a particular focus on reasoning. The seven tutorial papers presented provide competent coverage of methods and major application areas such as social networks, semantic multimedia indexing and retrieval, bioinformatics, and semantic web services. They highlight which techniques are already being successfully applied for purposes such as improving the performance of information retrieval algorithms, enabling the interoperation of heterogeneous agents, modelling users profiles and social relations, and standardizing and improving the accuracy of very large and dynamic scientific databases.
The Semantic Web: Research and Applications
This book constitutes the refereed proceedings of the 9th Extended Semantic Web Conference, ESWC 2012, held in Heraklion, Crete, Greece, in May 2012. The 53 revised full papers presented were carefully reviewed and selected from 212 submissions. They are organized in tracks on linked open data, machine learning, natural language processing and information retrieval, ontologies, reasoning, semantic data management, services, processes, and cloud computing, social Web and Web science, in-use and industrial, digital libraries and cultural heritage, and e-government. The book also includes 13 PhD papers presented at the PhD Symposium.
Semantic Paths in Business Filings Analysis
Supporting competitive business analysis of financial reports through the automated analysis and interpretation of their natural language sections, presents specific challenges including information that can be ambiguous, camouflaged, or tacitly hidden within the narrative. These sections present terminology and structural challenges for information extraction that require the application of linguistic and heuristic based domain modelling to identify the information requirement. This thesis investigates a modelling approach that incrementally builds the business analysts information requirement as a series of Semantic Paths grounded in domain linguistic and user heuristics. A Competitive Ana...
