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Semantic Keyword-based Search on Structured Data Sources

Conference on semantic Keyword-based Search on Structured Data Sources, IKC 2015, held in Coimbra, Portugal, in September 2015. The 13 revised;

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Semantic Keyword-Based Search on Structured Data Sources

Conference on Semantic Keyword-Based Search on Structured Data Sources, IKC 2016, held in Cluj-Napoca, Romania, in September 2016. The 15 revised;

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Semantic Keyword-Based Search on Structured Data Sources

on Semantic Keyword-Based Search on Structured Data Sources, IKC 2017, held in Gdansk, Poland, in September 2017. The 13 revised full;

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Peer-to-Peer Data Management

systems that enable document search based both on the textual content and the document structure. Finally, we introduce semantic overlay networks;

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Keyword Search in Databases

like Google search. This book surveys the recent developments on keyword search over databases, and focuses on finding structural information;

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Peer-to-Peer Data Management

systems that enable document search based both on the textual content and the document structure. Finally, we introduce semantic overlay networks;

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Database and Expert Systems Applications

; Database and Information System Architectures; Query Answering and Optimization; Information Retrieval, and Keyword Search; Data Modelling, and;

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Database and Expert Systems Applications

; Database and Information System Architectures; Query Answering and Optimization; Information Retrieval, and Keyword Search; Data Modelling, and;

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Keyword Search Based on Lexical Relationships in the Text

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Structured Search for Big Data

Data are arguably the most notable. Structured Search paradigm connects them via a fundamental concept of key-objects evolving out of keywords;

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Semantic Search over the Web

huge amount of information. Search on the Web has been traditionally based on textual and structural similarities, ignoring to a large degree;

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Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources

ontology relations. It combines corpus-based techniques with reasoning on Semantic Web data. Corpus-based methods apply vector space similarity;

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Ontology-Based Information Retrieval for Healthcare Systems

following areas: Semantic data integration in e-health care systems Keyword-based medical information retrieval Ontology-based query;

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Mastering Structured Data on the Semantic Web

-world humans and objects) rather than documents meaningless to computers. Mastering Structured Data on the Semantic Web explains the practical;

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Operational Risk Management

unstructured, semantic-based data, and numeric data, in Operational Risk Management (OpR) data analysis. Key Features: * The book is presented in four;

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HCPR multiplied with TFIDF for Effective Search Method

A large type of data contains in various geographic locations and these huge amounts of data create a data ocean. Information Retrieval (IR;

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Towards the Multilingual Semantic Web

information needs in any language with regard to semantically structured data available on the Semantic Web and Linked Open Data (LOD) cloud, (2;

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Search Engine Optimization and Marketing

and setting up * Query-based search While other books are focused on the traditional explanation of digital marketing, theoretical;

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Semantic IoT: Theory and Applications

understanding of data that will enable analysis across (systematically growing) ecosystems? (ii) How to build ecosystems based on data flows? (iii) How;

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XML Databases and the Semantic Web

today's corporations. With so much data on the Web, managing it with conventional tools is becoming almost impossible. New tools and techniques;

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Natural Language Processing for the Semantic Web

technologies enables structured and unstructured data to merge seamlessly. Semantic Web technologies aim to convert unstructured data to meaningful;

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Natural Language Processing for the Semantic Web

technologies enables structured and unstructured data to merge seamlessly. Semantic Web technologies aim to convert unstructured data to meaningful;

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Database Systems for Advanced Applications

selected from a total of 159 submissions. The topics covered are query processing and optimization, data semantics, XML and semi-structured data;

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Solr in Action

DESCRIPTION Whether handling big data, building cloud-based services, or developing multi-tenant web applications, it's vital to;

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Semantic Web and Web Science

cutting edge technologies, such as: linked data, social semantic web, semantic web search, smart data integration, semantic web mining and web;

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Phonetic Search Methods for Large Speech Databases

Phonetic Search Methods for Large Databases focuses on Keyword Spotting (KWS) within large speech databases. The brief will begin by;

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Big Data in Complex Systems

semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. Data analysis;

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