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Semantic Knowledge Representation for Information Retrieval

languages and intersystem relations, and explain their contribution to search functionalities in information retrieval scenarios. An example;

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Foundations of Large-Scale Multimedia Information Management and Retrieval

retrieval. These include feature selection/reduction, knowledge representation, semantic analysis, distance function formulation for measuring;

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Knowledge Graphs and Semantic Web

processing; description logics; information systems; query languages; world wide web; semantic web description languages; and information retrieval.;

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Foundations of Intelligent Systems

, recommender systems; machine learning; knowledge representation, semantic web; emotion recognition, music information retrieval; network analysis;

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Graph-Based Representation and Reasoning

, respectively. The topics covered are: conceptual structures, knowledge representation, reasoning, conceptual graphs, formal concept analysis, semantic;

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Multimedia Content And The Semantic Web

representation and querying for realizing semantics-driven applications Includes cutting-edge information on multimedia content description in MPEG-7;

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Foundations of Information and Knowledge Systems

constraint management; intelligent agents; knowledge discovery and information retrieval; knowledge representation, reasoning and planning; logics;

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Foundations of Information and Knowledge Systems

fusion; integrity and constraint management; intelligent agents; knowledge discovery and information retrieval; knowledge representation;

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Foundations of Information and Knowledge Systems

fusion, integrity and constraint management, intelligent agents, knowledge discovery and information retrieval, knowledge representation;

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Representation Learning for Natural Language Processing

network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and;

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Representation Learning for Natural Language Processing

network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and;

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Ontology-Based Information Retrieval for Healthcare Systems

volume of heterogeneous data over a long time span. This requirement demands effective ontology-based information retrieval approaches for;

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Semantic Web Personalization and Context Awareness

research in Semantic Web-based personalization as applied to the context of information systems. This book reviews knowledge engineering for;

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Information Seeking and Subject Representation

Information science has for a long time been drawing on the knowledge produced in psychology and related fields. This is reasonable, for;

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Semantic Technology

technologies and are organized in topical sections on ontology and data management; ontology reasoning; linked data and query; information retrieval;

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Statistical Language and Speech Processing

; information retrieval; knowledge representation and ontologies; lexicons and dictionaries; machine translation; multimodal technologies; natural;

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Statistical Language and Speech Processing

; information retrieval; knowledge representation and ontologies; lexicons and dictionaries; machine translation; multimodal technologies; natural;

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Knowledge Management and Representation

a management control view perspective, and knowledge representation formalism for semantic business process management.;

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Ontologies

retrieval of corporate information and knowledge and for enhanced Internet-based electronic commerce. In the second part of the book, the author;

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PRICAI 2016: Trends in Artificial Intelligence

submissions. Pricai covers a wide range of topics such as AI foundations; applications of AI; semantic web; information retrieval; constraint;

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Knowledge Graph and Semantic Computing: Knowledge Computing and Language Understanding

wide research fields including the knowledge graph, the semantic Web, linked data, NLP, information extraction, knowledge representation and;

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Information Retrieval

Text Categorisation and Genre in Information Retrieval Semantic Search The Role of Natural Language Processing in Information Retrieval: Search;

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Human Information Retrieval

. Warner presents a labor theoretic approach to information retrieval, building on his previously formulated distinction between semantic and;

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Multidisciplinary Information Retrieval

research areas: information retrieval, semantic web technologies for IR, natural language processing for IR, and large-scale or distributed;

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Automatic Ontology-Based Document Annotation

semantic search and Arabic document annotation and retrieval. In this research we propose an approach for enhancing the process of information;

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Ontological Engineering: With Examples from the Areas of Knowledge Management, E-Commerce and the Semantic Web. First Edition

information, information retrieval, integration of databases, b- informatics, and education; and in new emerging fields like the Semantic Web. Primary;

Vergelijkbare producten zoals Ontological Engineering: With Examples from the Areas of Knowledge Management, E-Commerce and the Semantic Web. First Edition

Ontological Engineering: With Examples from the Areas of Knowledge Management, E-Commerce and the Semantic Web. First Edition

information, information retrieval, integration of databases, b- informatics, and education; and in new emerging fields like the Semantic Web. Primary;

Vergelijkbare producten zoals Ontological Engineering: With Examples from the Areas of Knowledge Management, E-Commerce and the Semantic Web. First Edition