Last edited by Bakus
Saturday, November 28, 2020 | History

1 edition of Semantics in Data and Knowledge Bases found in the catalog.

Semantics in Data and Knowledge Bases

5th International Workshop, SDKB 2011, Zürich, Switzerland, July 3, 2011, Revised Selected Papers

by Klaus-Dieter Schewe

  • 111 Want to read
  • 30 Currently reading

Published by Springer Berlin Heidelberg, Imprint: Springer in Berlin, Heidelberg .
Written in English

    Subjects:
  • Data Mining and Knowledge Discovery,
  • Database management,
  • Information storage and retrieval systems,
  • Information organization,
  • Simulation and Modeling,
  • Information retrieval,
  • Computer simulation,
  • Information Systems Applications (incl. Internet),
  • Computer science,
  • Data mining,
  • Artificial intelligence,
  • Artificial Intelligence (incl. Robotics)

  • About the Edition

    This book constitutes the thoroughly refereed post-conference proceedings of the 5th International Workshop on Semantics in Data and Knowledge Bases, SDKB 2011, held in July 2011 in Zürich, Switzerland. The 8 revised full papers presented were carefully selected from numerous submissions covering topics of formal models for data and knowledge bases, integrity constraints maintenance and dependency theory, formal methods for data and knowledge base design, reasoning about data and knowledge base dynamics, adaptivity for personalised data and knowledge bases view-centered data- and knowledge-intensive systems, information integration in data and knowledge bases, knowledge discovery in data and knowledge bases, validation and verification of data and knowledge base designs, formal linguistics for data and knowledge bases, logical and mathematical foundations of semantics, semantics in data- and knowledge-intensive applications.

    Edition Notes

    Statementedited by Klaus-Dieter Schewe, Bernhard Thalheim
    SeriesLecture Notes in Computer Science -- 7693
    ContributionsThalheim, Bernhard, SpringerLink (Online service)
    Classifications
    LC ClassificationsQA76.9.D3
    The Physical Object
    Format[electronic resource] :
    PaginationXII, 199 p. 18 illus.
    Number of Pages199
    ID Numbers
    Open LibraryOL27087026M
    ISBN 109783642360084


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Semantics in Data and Knowledge Bases by Klaus-Dieter Schewe Download PDF EPUB FB2

This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Semantics in Data and Knowledge Bases, SDKBheld in Bordeaux, France in July The 6 revised full papers presented together with an introductory survey by the volume editors were carefully reviewed and selected during two rounds of revision and : Paperback.

Buy Semantics in Data and Knowledge Bases: 5th International Workshop SDKBZürich, Switzerland, July 3,Revised Selected Papers (Lecture Notes in Computer Science) on FREE SHIPPING on qualified orders. This book constitutes the thoroughly refereed post-workshop proceedings of the Third International Workshop on Semantics in Data and Knolwedge Bases, SDKBheld in Nantes, France, on Ma The 6 revised full papers presented together.

This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Semantics in Data and Knowledge Bases, SDKBheld in Bordeaux, France in July The 6 revised full papers presented together with an introductory survey by the volume editors were carefully reviewed and selected during two rounds of revision and improvement.

Introduction This book constitutes the thoroughly refereed post-conference proceedings of the 5th International Workshop on Semantics in Data and Knowledge Bases book in Data and Knowledge Bases, SDKBheld in July in Zürich, Switzerland.

The SDKB workshop presented original contributions demonstrating the use of logic, discrete mathematics, combinatorics, domain theory and other mathematical theories of semantics for database and knowledge bases, computational linguistics and semiotics, and information and knowledge-based.

Semantics is the study of meaning, i.e. how meaning is constructed, interpreted, clarified, obscured, illustrated, simplified, negotiated, contradicted and paraphrased [Wan87]. It has been treated.

(ebook) Semantics in Data and Knowledge Bases () from Dymocks online store. This book constitutes the thoroughly refereed. We are open, in-store and online.

Some orders may experience a slight delay due to COVID restrictions. Semantic Search on Text and Knowledge Bases classifies this work according to two dimensions: the type of data (text, knowledge bases, combinations of these) and the kind of search (keyword.

Books on Semantic Web: Intro. This page contains information on books that are strictly on the Semantic Web and Linked are, of course, lots of other books on Knowledge Representation, Logic, XML, Databases, etc, that are all relevant for the Semantic Web, but adding these to this list would be counter productive.

This book focuses on the following issues of the Semantic Web: the theory aspect of the Semantic Web and ontology, data management and processing in the Semantic Web, ontology and knowledge management, and Semantic Web-based applications, aiming at providing a single account of technologies and practices in the Semantic Web for knowledge and data management.

Semantic data model is a high-level semantics-based database description and structuring formalism for databases. This database model is designed to capture more of the meaning of an application environment than is possible with contemporary database models.

An SDM specification describes a database in terms of the kinds of entities that exist in the application environment, the classifications and groupings of those entities, and the structural interconnections among them. SDM. Semantic Web Technologies A set of technologies and frameworks that enable the Web of Data: Resource Description Framework (RDF) A variety of data interchange formats (e.g.

RDF/XML,N3,Turtle,N-Triples) Notations such as RDF Schema (RDFS) and the Web Ontology Language (OWL) All are intended to provide a formal. Semantic Catalogs One particular architecture that is gaining popularity in the semantic space is the semantic data catalog (SDC), which can be.

Semantic Search on Text and Knowledge Bases classifies this work according to two dimensions: the type of data (text, knowledge bases, combinations of these) and the kind of search (keyword, structured, natural language). All nine combinations are considered.

The focus is on fundamental techniques, concrete systems, and benchmarks. Fig. 2 gives an overview of the Linked Open Data enabled knowledge discovery pipeline.

Given a set of local data (such as a relational database), the first step is to link the data to the corresponding LOD concepts from the chosen LOD dataset (cf. Section 5). 1 Once the local data is linked to a LOD dataset, we can explore the existing links in the dataset pointing to the related entities in.

Knowledge graphs have now been “officially” announced to be on the rise by Gartner’s Hype Cycle for Artificial Intelligence. As we take pride in SEMANTiCS being one of the platforms to help “pulling knowledge graphs to the surface" (as Gartner calls it), we take this opportunitý to share a contribution recently published via LinkedIN Pulse by SEMANTiCS Conference’s co-founder.

Give us 5 minutes and we will show you the best book to read today. This is it, the research methods the essential knowledge base that will be your best choice for better reading book.

Your five times will not spend wasted by reading this website. You can take the book as a source to make better concept. Referring the books that can be situated with your needs is sometime difficult. This book constitutes the thoroughly refereed post-workshop proceedings of the Third International Workshop on Semantics in Data and Knolwedge Bases, SDKBheld in Nantes, France, on Ma   Enriching semantic knowledge bases such as SenticNet with information on (i) potentially ambiguous sentiment terms, (ii) positive and negative context terms and (iii) the grounding of these interpretations to common-sense and common knowledge paves the way for adapting sentiment analysis components to address these ambiguities in a systematic.

Using Semantics and Statistics to Turn Data into Knowledge Jay Pujara, Hui Miao, Lise Getoor, William W. Cohen n Many information-extraction and knowledge base construction systems are addressing the challenge of deriving knowledge from text.

A key problem in constructing these knowledge bases from sources like the web is overcoming. Knowledge Data Science is the resolution to Business / Organizations problems through mathematics, programming, scientific method and semantic technologies that involves the creation of hypotheses, experiments and tests through the analysis of data and the generation of predictive models inside of a knowledge representation system.

However, recent advances in psychology and neuropsychology have led to the development of a scientific approach to analysing the cognitive bases of semantic knowledge and semantic representations. Indeed, theory and data on the organisation and structure of semantic knowledge have now become central and hotly debated topics in contemporary.

Web Semantics & Ontology provides an excellent overview of current research and development activities, while covering an extensive range of topics including ontological modeling, enterprise systems, querying and knowledge discovery, and a wide range of applications. Each chapter contains a thorough study of the topic, systematic proposed work, and a comprehensive list of   Among the best semantic analysis tools, natural language processing and text mining applications play a key role in today enterprise world.

Driven by an increasing need to effectively manage big data, business documents that contain unstructured information as well as social media interactions etc., the market of this kind of semantic analysis tools remains strong (for example, estimates show.

Semantics in Data and Knowledge Bases: Third International Workshop, SdkbNantes, France, MaRevised Selected Papers by Klaus-Dieter Schewe (Editor), Bernhard Thalheim (Editor) starting at $ YAGO - A Multilingual Knowledge Base from Wikipedia, Wordnet, and Geonames International Semantic Web Conference (ISWC ) Farzaneh Mahdisoltani, Joanna Biega, Fabian M.

Suchanek YAGO3: A Knowledge Base from Multilingual Wikipedias Conference on Innovative Data Systems Research (CIDR ).

Joanna Biega, Erdal Kuzey, Fabian M. Suchanek. Key observation: Practitioners in the data warehousing industry frequently confuse construction of the semantic data model, logical data model, and physical data model. •A semantic data model (SDM) captures the business view of information for a specific knowledge worker community or.

Abstract: The evolution of the Web of documents into a Web of services and data has resulted in an increased availability of data from almost any domain. For example, general domain knowledge bases such as DBpedia or Wikidata, or domain specific Web sources like the Oxford Art archive, allow for accessing knowledge about a wide variety of entities including people, organizations, or art paintings.

ISBN: OCLC Number: Description: ix, pages: illustrations ; 24 cm: Contents: An informal and efficient approach for obtaining semantic constraints using sample data and natural language processing / Meike Albrecht [and others] --Achievements of relational database schema design theory revisited / Joachim Biskup --Semantics of database transformations.

Collective Entity Disambiguation Based on Hierarchical Semantic Similarity: /IJDWM Entity disambiguation involves mapping mentions in texts to the corresponding entities in a given knowledge base.

Most previous approaches were based on. Augmented Post systems (APS) are string-operating Prolog-like knowledge representation, affiliated with the “Set of Strings” Framework (SSF). APS descriptive and logical inference capabilities provide natural integration of Big Data with online analytic processing.

This chapter is dedicated to strict formal definition of APS syntax, mathematical and operational semantics, and to its. Lexicon specifies the semantics and syntax of basic expressions. Syntactic rules correspond to semantic rules (e.g.

function application may correspond to function application) 4 Other things about semantics Things modern semantics studies • tense and aspect – different languages use different tenses/aspects to express the same.

Abstract: Translating natural language questions to semantic representations such as SPARQL is a core challenge in open-domain question answering over knowledge bases (KB-QA). Existing methods rely on a clear separation between an offline training phase, where a model is learned, and an online phase where this model is deployed to answer users.

Semantic DEVELOPMENT: Strategies for Parents. Labeling and elaborating throughout the day: These types of conversations do not need to happen just during joint book reading, but can also occur when you and your child are in the car together, watching television, or looking at a billboard.

Semantic warehousing is different from search engine in that semantic information base from text data is stored in the database.(Though data is most important word in computing era, it can not explain human knowledge well yet.

Data(numeric data) is key element of computing systems for certain organization (especially companies, enterprises. YAGO - a huge semantic knowledge base.

Currently, YAGO knows more than 2 million entities (like persons, organizations, cities, etc.). It knows 20 million facts about these entities. Unlike many other automatically assembled knowledge bases, YAGO has a manually confirmed accuracy of 95%. The goal of the project "The Map as Knowledge Base" is to specify feature semantics for richer topographic and geospatial data models.

New data models and associated knowledge organization systems for The National Map can translate traditional topographic information into a flexible spatiotemporal knowledge base that can serve many different application areas, improve. The Journal of Web Semantics is an interdisciplinary journal based on research and applications of various subject areas that contribute to the development of a knowledge-intensive and intelligent service Web.

These areas include: knowledge technologies, ontology, agents, databases and the semantic grid, obviously disciplines like information retrieval, language technology, human-computer.

Semantic Knowledge Graphs will grow with your needs. Standards-based semantics provide yet another advantage: it is becoming increasingly simpler to hire skilled people who have been working with standards like RDF, SKOS or SPARQL before. Even so, experienced knowledge engineers and data scientists are a comparatively rare species.

data resource (neuroscience data or findings) database (datasets) atlas (spatially-organized data) knowledge base (findings/knowledge derived from data) clinical knowledge base (diagnosis/treatment) bibliographic resource (library/publisher or literature access) software resource (software for acquisition, analysis, display or modeling) data.Knowledge Architectures reviews traditional approaches to managing information and explains why they need to adapt to support twenty-first century information management and discovery.

Exploring the rapidly changing environment in which information is being managed and accessed, the book considers how to use knowledge architectures, the basic structures and designs that underlie all of the.This book contains revised and significantly extended versions of selected papers from three workshops on Uncertainty Reasoning for the Semantic Web (URSW), held at the International Semantic Web Conf.