Search (15 results, page 1 of 1)

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Abstract

This book constitutes the thoroughly refereed post-conference proceedings of the First COST Action IC1302 International KEYSTONE Conference on semantic Keyword-based Search on Structured Data Sources, IKC 2015, held in Coimbra, Portugal, in September 2015. The 13 revised full papers, 3 revised short papers, and 2 invited papers were carefully reviewed and selected from 22 initial submissions. The paper topics cover techniques for keyword search, semantic data management, social Web and social media, information retrieval, benchmarking for search on big data.

Content

Inhalt: Professional Collaborative Information Seeking: On Traceability and Creative Sensemaking / Nürnberger, Andreas (et al.) - Recommending Web Pages Using Item-Based Collaborative Filtering Approaches / Cadegnani, Sara (et al.) - Processing Keyword Queries Under Access Limitations / Calì, Andrea (et al.) - Balanced Large Scale Knowledge Matching Using LSH Forest / Cochez, Michael (et al.) - Improving css-KNN Classification Performance by Shifts in Training Data / Draszawka, Karol (et al.) - Classification Using Various Machine Learning Methods and Combinations of Key-Phrases and Visual Features / HaCohen-Kerner, Yaakov (et al.) - Mining Workflow Repositories for Improving Fragments Reuse / Harmassi, Mariem (et al.) - AgileDBLP: A Search-Based Mobile Application for Structured Digital Libraries / Ifrim, Claudia (et al.) - Support of Part-Whole Relations in Query Answering / Kozikowski, Piotr (et al.) - Key-Phrases as Means to Estimate Birth and Death Years of Jewish Text Authors / Mughaz, Dror (et al.) - Visualization of Uncertainty in Tag Clouds / Platis, Nikos (et al.) - Multimodal Image Retrieval Based on Keywords and Low-Level Image Features / Pobar, Miran (et al.) - Toward Optimized Multimodal Concept Indexing / Rekabsaz, Navid (et al.) - Semantic URL Analytics to Support Efficient Annotation of Large Scale Web Archives / Souza, Tarcisio (et al.) - Indexing of Textual Databases Based on Lexical Resources: A Case Study for Serbian / Stankovic, Ranka (et al.) - Domain-Specific Modeling: Towards a Food and Drink Gazetteer / Tagarev, Andrey (et al.) - Analysing Entity Context in Multilingual Wikipedia to Support Entity-Centric Retrieval Applications / Zhou, Yiwei (et al.)

Date

1. 2.2016 18:25:22

LCSH

Text processing (Computer science)

Subject

Text processing (Computer science)

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Abstract

This book constitutes the refereed proceedings of the 8th Metadata and Semantics Research Conference, MTSR 2014, held in Karlsruhe, Germany, in November 2014. The 23 full papers and 9 short papers presented were carefully reviewed and selected from 57 submissions. The papers are organized in several sessions and tracks. They cover the following topics: metadata and linked data: tools and models; (meta) data quality assessment and curation; semantic interoperability, ontology-based data access and representation; big data and digital libraries in health, science and technology; metadata and semantics for open repositories, research information systems and data infrastructure; metadata and semantics for cultural collections and applications; semantics for agriculture, food and environment.

Content

Metadata and linked data.- Tools and models.- (Meta)data quality assessment and curation.- Semantic interoperability, ontology-based data access and representation.- Big data and digital libraries in health, science and technology.- Metadata and semantics for open repositories, research information systems and data infrastructure.- Metadata and semantics for cultural collections and applications.- Semantics for agriculture, food and environment.

LCSH

Text processing (Computer science)

Subject

Text processing (Computer science)

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Abstract

This book describes efficient and effective techniques for harnessing the power of Linked Data by tackling the various aspects of managing its growing volume: storing, querying, reasoning, provenance management and benchmarking. To this end, Chapter 1 introduces the main concepts of the Semantic Web and Linked Data and provides a roadmap for the book. Next, Chapter 2 briefly presents the basic concepts underpinning Linked Data technologies that are discussed in the book. Chapter 3 then offers an overview of various techniques and systems for centrally querying RDF datasets, and Chapter 4 outlines various techniques and systems for efficiently querying large RDF datasets in distributed environments. Subsequently, Chapter 5 explores how streaming requirements are addressed in current, state-of-the-art RDF stream data processing. Chapter 6 covers performance and scaling issues of distributed RDF reasoning systems, while Chapter 7 details benchmarks for RDF query engines and instance matching systems. Chapter 8 addresses the provenance management for Linked Data and presents the different provenance models developed. Lastly, Chapter 9 offers a brief summary, highlighting and providing insights into some of the open challenges and research directions. Providing an updated overview of methods, technologies and systems related to Linked Data this book is mainly intended for students and researchers who are interested in the Linked Data domain. It enables students to gain an understanding of the foundations and underpinning technologies and standards for Linked Data, while researchers benefit from the in-depth coverage of the emerging and ongoing advances in Linked Data storing, querying, reasoning, and provenance management systems. Further, it serves as a starting point to tackle the next research challenges in the domain of Linked Data management.

LCSH

Linked data

RSWK

Linked Data

Subject

Linked Data
Linked data

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Content

The papers are organized in several sessions and tracks: general track on ontology evolution, engineering, and frameworks, semantic Web and metadata extraction, modelling, interoperability and exploratory search, data analysis, reuse and visualization; track on digital libraries, information retrieval, linked and social data; track on metadata and semantics for open repositories, research information systems and data infrastructure; track on metadata and semantics for agriculture, food and environment; track on metadata and semantics for cultural collections and applications; track on European and national projects.

LCSH

Text processing (Computer science)

Subject

Text processing (Computer science)

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Abstract

This book constitutes the thoroughly refereed post-conference proceedings of the Second COST Action IC1302 International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources, IKC 2016, held in Cluj-Napoca, Romania, in September 2016. The 15 revised full papers and 2 invited papers are reviewed and selected from 18 initial submissions and cover the areas of keyword extraction, natural language searches, graph databases, information retrieval techniques for keyword search and document retrieval.

Content

Inhalt: Retrieval, Crawling and Fusion of Entity-centric Data on the Web / Dietze, Stefan - Data Multiverse: The Uncertainty Challenge of Future Big Data Analytics / Tudoran, Radu (et al.) - Experiments with Document Retrieval from Small Text Collections Using Latent Semantic Analysis or Term Similarity with Query Coordination and Automatic Relevance Feedback / Layfield, Colin (et al.) - Unsupervised Extraction of Conceptual Keyphrases from Abstracts / Ludwig, Philipp (et al.) - Back to the Sketch-Board: Integrating Keyword Search, Semantics, and Information Retrieval / Azzopardi, Joel (et al.) - Topic Detection in Multichannel Italian Newspapers / Po, Laura (et al.) - Random Walks Analysis on Graph Modelled Multimodal Collections / Sabetghadam, Serwah (et al.) - A Software Processing Chain for Evaluating Thesaurus Quality / Lacasta, Javier (et al.) - Comparison of Collaborative and Content-Based Automatic Recommendation Approaches in a Digital Library of Serbian PhD Dissertations / Azzopardi, Joel (et al.) - Keyword-Based Search on Bilingual Digital Libraries / Stankovic, Ranka (et al.) - Network-Enabled Keyword Extraction for Under-Resourced Languages / Beliga, Slobodan (et al.) - Making Sense of Citations / Koulouri, Xenia (et al.) - An Ontology-Based Approach to Information Retrieval / Mestrovic, Ana (et al.) - Game with a Purpose for Verification of Mappings Between Wikipedia and WordNet / Boinski, Tomasz - TB-Structure: Collective Intelligence for Exploratory Keyword Search / Terziyan, Vagan (et al.) - Using Natural Language to Search Linked Data / Rozinajová, Viera (et al.) - The Use of Semantics in the CrossCult H2020 Project / Bampatzia, Stavroula (et al.) Vgl. auch: http://www.keystone-cost.eu/ikc2016/program.php.

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LCSH

Data mining

RSWK

Data Mining / Kongress / Cochin <Kerala, 2010>

Subject

Data Mining / Kongress / Cochin <Kerala, 2010>
Data mining

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Abstract

Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.

Content

Inhalt: An Introduction to Text Mining.- Information Extraction from Text.- A Survey of Text Summarization Techniques.- A Survey of Text Clustering Algorithms.- Dimensionality Reduction and Topic Modeling.- A Survey of Text Classification Algorithms.- Transfer Learning for Text Mining.- Probabilistic Models for Text Mining.- Mining Text Streams.- Translingual Mining from Text Data.- Text Mining in Multimedia.- Text Analytics in Social Media.- A Survey of Opinion Mining and Sentiment Analysis.- Biomedical Text Mining: A Survey of Recent Progress.- Index.

LCSH

Data mining

Subject

Data mining

Theme

Data Mining

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Abstract

This volume contains the lecture notes of the 13th Reasoning Web Summer School, RW 2017, held in London, UK, in July 2017. In 2017, the theme of the school was "Semantic Interoperability on the Web", which encompasses subjects such as data integration, open data management, reasoning over linked data, database to ontology mapping, query answering over ontologies, hybrid reasoning with rules and ontologies, and ontology-based dynamic systems. The papers of this volume focus on these topics and also address foundational reasoning techniques used in answer set programming and ontologies.

Content

Neumaier, Sebastian (et al.): Data Integration for Open Data on the Web - Stamou, Giorgos (et al.): Ontological Query Answering over Semantic Data - Calì, Andrea: Ontology Querying: Datalog Strikes Back - Sequeda, Juan F.: Integrating Relational Databases with the Semantic Web: A Reflection - Rousset, Marie-Christine (et al.): Datalog Revisited for Reasoning in Linked Data - Kaminski, Roland (et al.): A Tutorial on Hybrid Answer Set Solving with clingo - Eiter, Thomas (et al.): Answer Set Programming with External Source Access - Lukasiewicz, Thomas: Uncertainty Reasoning for the Semantic Web - Calvanese, Diego (et al.): OBDA for Log Extraction in Process Mining

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Content

Introduction.- Ontology Development.- Compliance using Metadata.- Variety Management for Big Data.- Text Mining in Economics.- Generation of Natural Language Texts.- Sentiment Analysis.- Building Concise Text Corpora from Web Contents.- Ontology-Based Modelling of Web Content.- Personalized Clinical Decision Support for Cancer Care.- Applications of Temporal Conceptual Semantic Systems.- Context-Aware Documentation in the Smart Factory.- Knowledge-Based Production Planning for Industry 4.0.- Information Exchange in Jurisdiction.- Supporting Automated License Clearing.- Managing cultural assets: Implementing typical cultural heritage archive's usage scenarios via Semantic Web technologies.- Semantic Applications for Process Management.- Domain-Specific Semantic Search Applications.

LCSH

Data mining
Data Mining and Knowledge Discovery

RSWK

Data Mining

Subject

Data Mining
Data mining
Data Mining and Knowledge Discovery

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Content

Inhalt: Acknowledgments; Abstract; Zusammenfassung; Contents; List of Figures; List of Tables; List of Acronyms; Chapter 1 Introduction ; 1.1 Research Questions; 1.2 Thesis Outline; Part I Fundamentals ; Chapter 2 Information Retrieval for Young Users ; 2.1 Basics of Information Retrieval; 2.1.1 Architecture of an IR System; 2.1.2 Relevance Ranking; 2.1.3 Search User Interfaces; 2.1.4 Targeted Search Engines; 2.2 Aspects of Child Development Relevant for Information Retrieval Tasks; 2.2.1 Human Cognitive Development; 2.2.2 Information Processing Theory; 2.2.3 Psychosocial Development 2.3 User Studies and Evaluation2.3.1 Methods in User Studies; 2.3.2 Types of Evaluation; 2.3.3 Evaluation with Children; 2.4 Discussion; Chapter 3 State of the Art ; 3.1 Children's Information-Seeking Behaviour; 3.1.1 Querying Behaviour; 3.1.2 Search Strategy; 3.1.3 Navigation Style; 3.1.4 User Interface; 3.1.5 Relevance Judgement; 3.2 Existing Algorithms and User Interface Concepts for Children; 3.2.1 Query; 3.2.2 Content; 3.2.3 Ranking; 3.2.4 Search Result Visualisation; 3.3 Existing Information Retrieval Systems for Children; 3.3.1 Digital Book Libraries; 3.3.2 Web Search Engines 3.4 Summary and DiscussionPart II Studying Open Issues ; Chapter 4 Usability of Existing Search Engines for Young Users ; 4.1 Assessment Criteria; 4.1.1 Criteria for Matching the Motor Skills; 4.1.2 Criteria for Matching the Cognitive Skills; 4.2 Results; 4.2.1 Conformance with Motor Skills; 4.2.2 Conformance with the Cognitive Skills; 4.2.3 Presentation of Search Results; 4.2.4 Browsing versus Searching; 4.2.5 Navigational Style; 4.3 Summary and Discussion; Chapter 5 Large-scale Analysis of Children's Queries and Search Interactions; 5.1 Dataset; 5.2 Results; 5.3 Summary and Discussion Chapter 6 Differences in Usability and Perception of Targeted Web Search Engines between Children and Adults 6.1 Related Work; 6.2 User Study; 6.3 Study Results; 6.4 Summary and Discussion; Part III Tackling the Challenges ; Chapter 7 Search User Interface Design for Children ; 7.1 Conceptual Challenges and Possible Solutions; 7.2 Knowledge Journey Design; 7.3 Evaluation; 7.3.1 Study Design; 7.3.2 Study Results; 7.4 Voice-Controlled Search: Initial Study; 7.4.1 User Study; 7.5 Summary and Discussion; Chapter 8 Addressing User Diversity ; 8.1 Evolving Search User Interface 8.1.1 Mapping Function8.1.2 Evolving Skills; 8.1.3 Detection of User Abilities; 8.1.4 Design Concepts; 8.2 Adaptation of a Search User Interface towards User Needs; 8.2.1 Design & Implementation; 8.2.2 Search Input; 8.2.3 Result Output; 8.2.4 General Properties; 8.2.5 Configuration and Further Details; 8.3 Evaluation; 8.3.1 Study Design; 8.3.2 Study Results; 8.3.3 Preferred UI Settings; 8.3.4 User satisfaction; 8.4 Knowledge Journey Exhibit; 8.4.1 Hardware; 8.4.2 Frontend; 8.4.3 Backend; 8.5 Summary and Discussion; Chapter 9 Supporting Visual Searchers in Processing Search Results 9.1 Related Work

Date

1. 2.2016 18:25:22

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LCSH

Data mining

Subject

Data mining

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Abstract

Beim Corporate Semantic Web betrachtet man Semantic Web-Anwendungen, die innerhalb eines Unternehmens oder einer Organisation - kommerziell und nicht kommerziell - eingesetzt werden, von Mitarbeitern, von Kunden oder Partnern. Die Autoren erläutern prägende Erfahrungen in der Entwicklung von Semantic Web-Anwendungen. Sie berichten über Software-Architektur, Methodik, Technologieauswahl, Linked Open Data Sets, Lizenzfragen etc. Anwendungen aus den Branchen Banken, Versicherungen, Telekommunikation, Medien, Energie, Maschinenbau, Logistik, Touristik, Spielwaren, Bibliothekswesen und Kultur werden vorgestellt. Der Leser erhält so einen umfassenden Überblick über die Semantic Web-Einsatzbereiche sowie konkrete Umsetzungshinweise für eigene Vorhaben.

Content

Kapitel 1; Corporate Semantic Web; 1.1 Das Semantic Web; 1.2 Semantische Anwendungen im Unternehmenseinsatz; 1.3 Bereitstellen von Linked Data reicht nicht; 1.4 Eine global vernetzte Wissensbasis -- Fiktion oder Realität?; 1.5 Semantik)=)RDF?; 1.6 Richtig vorgehen; 1.7 Modellieren ist einfach (?!); 1.8 Juristische Fragen; 1.9 Semantische Anwendungen stiften Nutzen in Unternehmen -- nachweislich!; 1.10 Fazit; Literatur; Kapitel 2; Einordnung und Abgrenzung des Corporate Semantic Webs; 2.1 Grundlegende Begriffe; 2.2 Corporate Semantic Web 2.3 Public Semantic Web2.4 Social Semantic Web 3.0; 2.5 Pragmatic Web; 2.6 Zusammenfassung und Ausblick "Ubiquitous Pragmatic Web 4.0"; Literatur; Kapitel 3; Marktstudie: Welche Standards und Tools werden in Unternehmen eingesetzt?; 3.1 Einleitung; 3.2 Semantische Suche in Webarchiven (Quantinum AG); 3.2.1 Kundenanforderungen; 3.2.2 Technische Umsetzung; 3.2.3 Erfahrungswerte; 3.3 Semantische Analyse und Suche in Kundenspezifikationen (Ontos AG); 3.3.1 Kundenanforderungen; 3.3.2 Technische Umsetzung; 3.3.3 Erfahrungswerte 3.4 Sicherheit für Banken im Risikomanagement (VICO Research & Consulting GmbH)3.4.1 Kundenanforderungen; 3.4.2 Technische Umsetzung; 3.4.3 Erfahrungswerte; 3.5 Interaktive Fahrzeugdiagnose (semafora GmbH); 3.5.1 Kundenanforderungen; 3.5.2 Technische Umsetzung; 3.5.3 Erfahrungswerte; 3.6 Quo Vadis?; 3.7 Umfrage-Ergebnisse; 3.8 Semantic Web Standards & Tools; 3.9 Ausblick; Literatur; Kapitel 4; Modellierung des Sprachraums von Unternehmen; 4.1 Hintergrund; 4.2 Eine Frage der Bedeutung; 4.3 Bedeutung von Begriffen im Unternehmenskontext; 4.3.1 Website-Suche bei einem Industrieunternehmen 4.3.2 Extranet-Suche bei einem Marktforschungsunternehmen4.3.3 Intranet-Suche bei einem Fernsehsender; 4.4 Variabilität unserer Sprache und unseres Sprachgebrauchs; 4.4.1 Konsequenzen des Sprachgebrauchs; 4.5 Terminologiemanagement und Unternehmensthesaurus; 4.5.1 Unternehmensthesaurus; 4.5.2 Mut zur Lücke: Arbeiten mit unvollständigen Terminologien; 4.6 Pragmatischer Aufbau von Unternehmensthesauri; 4.6.1 Begriffsanalyse des Anwendungsbereichs; 4.6.2 Informationsquellen; 4.6.3 Häufigkeitsverteilung; 4.6.4 Aufwand und Nutzen; Literatur; Kapitel 5 Schlendern durch digitale Museen und Bibliotheken5.1 Einleitung; 5.2 Anwendungsfall 1: Schlendern durch das Digitale Museum; 5.3 Anwendungsfall 2: Literatur in Bibliotheken finden; 5.4 Herausforderungen; 5.5 Die Anforderungen treiben die Architektur; 5.5.1 Semantic ETL; 5.5.2 Semantic Logic; 5.5.3 Client; 5.6 Diskussion; 5.7 Empfehlungen und Fazit; Literatur; Kapitel 6; Semantische Suche im Bereich der Energieforschungsförderung; 6.1 Das Projekt EnArgus®; 6.2 Die Fachontologie; 6.2.1 Semantische Suche; 6.2.2 Repräsentation der semantischen Relationen in der Fachontologie

LCSH

Data mining

Subject

Data mining

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LCSH

Text processing (Computer science)

Subject

Text processing (Computer science)

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LCSH

Document Preparation and Text Processing

Subject

Document Preparation and Text Processing

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Abstract

Dieses Buch präsentiert ein breites Spektrum aktueller Methoden zur Repräsentation und Verarbeitung (un)sicheren Wissens in maschinellen Systemen in didaktisch aufbereiteter Form. Neben symbolischen Ansätzen des nichtmonotonen Schließens (Default-Logik, hier konstruktiv und leicht verständlich mittels sog. Default-Bäume realisiert) werden auch ausführlich quantitative Methoden wie z.B. probabilistische Markov- und Bayes-Netze vorgestellt. Weitere Abschnitte beschäftigen sich mit Wissensdynamik (Truth Maintenance-Systeme), Aktionen und Planen, maschinellem Lernen, Data Mining und fallbasiertem Schließen.In einem vertieften Querschnitt werden zentrale alternative Ansätze einer logikbasierten Wissensmodellierung ausführlich behandelt. Detailliert beschriebene Algorithmen geben dem Praktiker nützliche Hinweise zur Anwendung der vorgestellten Ansätze an die Hand, während fundiertes Hintergrundwissen ein tieferes Verständnis für die Besonderheiten der einzelnen Methoden vermittelt . Mit einer weitgehend vollständigen Darstellung des Stoffes und zahlreichen, in den Text integrierten Aufgaben ist das Buch für ein Selbststudium konzipiert, eignet sich aber gleichermaßen für eine entsprechende Vorlesung. Im Online-Service zu diesem Buch werden u.a. ausführliche Lösungshinweise zu allen Aufgaben des Buches angeboten.Zahlreiche Beispiele mit medizinischem, biologischem, wirtschaftlichem und technischem Hintergrund illustrieren konkrete Anwendungsszenarien. Von namhaften Professoren empfohlen: State-of-the-Art bietet das Buch zu diesem klassischen Bereich der Informatik. Die wesentlichen Methoden wissensbasierter Systeme werden verständlich und anschaulich dargestellt. Repräsentation und Verarbeitung sicheren und unsicheren Wissens in maschinellen Systemen stehen dabei im Mittelpunkt. In der vierten, verbesserten Auflage wurde die Anzahl der motivierenden Selbsttestaufgaben mit aktuellem Praxisbezug nochmals erweitert. Ein Online-Service mit ausführlichen Musterlösungen erleichtert das Lernen.