Semantic Domains in Computational Linguistics, Alfio Gliozzo; Carlo Strapparava
Автор: Fabien Gandon; Marta Sabou; Harald Sack; Claudia d Название: The Semantic Web. Latest Advances and New Domains ISBN: 3319188178 ISBN-13(EAN): 9783319188171 Издательство: Springer Рейтинг: Цена: 12298.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Vocabularies, Schemas, Ontologies.- Requirements for and Evaluation of User Support for Large-Scale Ontology Alignment.- RODI: A Benchmark for Automatic Mapping Generation in Relational-to-Ontology Data Integration.- VocBench: a Web Application for Collaborative Development of Multilingual Thesauri.- Leveraging and Balancing Heterogeneous Sources of Evidence in Ontology Learning.- Reasoning.- A Context-Based Semantics for SPARQL Property Paths over the Web.- Distributed and Scalable OWL EL Reasoning.- Large scale rule-based Reasoning using a Laptop.- RDF Digest: Efficient Summarization of RDF/S KBs.- Linked Data.- A Comparison of Data Structures to Manage URIs on the Web of Data.- Heuristics for Fixing Common Errors in Deployed schema.org Microdata.- Semantic Web and Web Science.- LOD-based Disambiguation of Named Entities in @tweets through Context enrichment.- Knowledge Enabled Approach to Predict the Location of Twitter Users.- Semantic Data Management, Big data, Scalability.- A Compact In-Memory Dictionary for RDF data.- Quality Assessment of Linked Datasets using Probabilistic Approximations.- Cooperative Techniques for SPARQL Query Relaxation in RDF Databases.- HDT-MR: A Scalable Solution for RDF Compression with HDT and MapReduce.- Processing Aggregate Queries in a Federation of SPARQL Endpoints.- A survey of HTTP caching implementations on the open Semantic Web.- Query Execution Optimization for Clients of Triple Pattern Fragments.- Natural Language Processing and Information Retrieval LIME: the Metadata Module for OntoLex.- Learning a Cross-Lingual Semantic Representation of Relations Expressed in Text.- HAWK Hybrid Question Answering using Linked Data.- Machine Learning.- Automating RDF Dataset Transformation and Enrichment.- Semi-supervised Instance Matching Using Boosted Classifiers.- Assigning Semantic Labels to Data Sources.- Inductive Classification through Evidence-based Models and their Ensembles.- Mobile Web, Internet of Things and Semantic Streams.- Standardized and Efficient RDF Encoding for Constrained Embedded Networks.- Services, Web APIs, and the Web of Things SPSC: Efficient Composition of Semantic Services in Unstructured P2P Networks.- Data as a Service: The Semantic Web Redeployed.- Cognition and Semantic Web.- On Coherent Indented Tree Visualization of RDF Graphs.- Gagg: A Graph Aggregation Operator.- FrameBase: Representing N-ary Relations using Semantic Frames.- Human Computation and Crowdsourcing.- Towards hybrid NER: a study of content and crowdsourcing-related performance factors.- Ranking Entities in the Age of Two Webs, An Application to Semantic Snippets.- In-Use Industrial Track.- Troubleshooting and Optimizing Named Entity Resolution Systems in the Industry.- Using Ontologies For Modeling Virtual Reality Scenarios.- Supporting Open Collaboration in Science through Explicit and Linked Semantic Description of Processes.- Crowdmapping Digital Social Innovation with Linked data.- Desperately searching for travel offers? Formulate better queries with some help from Linked Data.- Towards the Linked Russian Heritage Cloud: Data enrichment and Publishing.- From Symptoms to Diseases - Creating the Missing Link.- Using semantic web technologies for enterprise architecture analysis.- PADTUN - Using Semantic Technologies in Tunnel Diagnosis and Maintenance Domain.
Автор: Matthew Taylor Название: Transfer in Reinforcement Learning Domains ISBN: 3642018815 ISBN-13(EAN): 9783642018817 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Reinforcement Learning Background.- Related Work.- Empirical Domains.- Value Function Transfer via Inter-Task Mappings.- Extending Transfer via Inter-Task Mappings.- Transfer between Different Reinforcement Learning Methods.- Learning Inter-Task Mappings.- Conclusion and Future Work.
Описание: The Handbook provides a comprehensive overview of the concepts, methodologies, and applications being undertaken today in computational linguistics and natural language processing.
Автор: Alexander Gelbukh Название: Computational Linguistics and Intelligent Text Processing ISBN: 354078134X ISBN-13(EAN): 9783540781349 Издательство: Springer Рейтинг: Цена: 16070.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: G?rard Huet; Amba Kulkarni; Peter Scharf Название: Sanskrit Computational Linguistics ISBN: 3642001548 ISBN-13(EAN): 9783642001543 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed post-conference proceedings of the First and Second International Symposia on Sanskrit Computational Linguistics, held in Rocquencourt, France, in October 2007 and in Providence, RI, USA, in May 2008 respectively. This title presents the 11 revised full papers of the first and the 12 revised papers of the second symposium.
Автор: Damien Nouvel, Maud Ehrmann, Sophie Rosset Название: Named Entities for Computational Linguistics ISBN: 1848218389 ISBN-13(EAN): 9781848218383 Издательство: Wiley Рейтинг: Цена: 22010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
One of the challenges brought on by the digital revolution of the recent decades is the mechanism by which information carried by texts can be extracted in order to access its contents.
The processing of named entities remains a very active area of research, which plays a central role in natural language processing technologies and their applications. Named entity recognition, a tool used in information extraction tasks, focuses on recognizing small pieces of information in order to extract information on a larger scale.
The authors use written text and examples in French and English to present the necessary elements for the readers to familiarize themselves with the main concepts related to named entities and to discover the problems associated with them, as well as the methods available in practice for solving these issues.
Описание: The Handbook provides a comprehensive overview of the concepts, methodologies, and applications being undertaken today in computational linguistics and natural language processing.
Автор: Adam Przepi?rkowski; Maciej Piasecki; Krzysztof Ja Название: Computational Linguistics ISBN: 3642343988 ISBN-13(EAN): 9783642343988 Издательство: Springer Рейтинг: Цена: 19591.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This presentation of the latest developments in computational linguistics covers the fast-moving field of information extraction, with papers from the CLA `11 conference held in Poland including recent successes in developing intelligent personal assistants.
Автор: Harald Sack; Eva Blomqvist; Mathieu d`Aquin; Chiar Название: The Semantic Web. Latest Advances and New Domains ISBN: 3319341286 ISBN-13(EAN): 9783319341286 Издательство: Springer Рейтинг: Цена: 13416.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The 47 revised full papers presented together with three invited talks were carefully reviewed and selected from 204 submissions. In addition, the PhD Symposium program included 10 contributions, selected out of 21 submissions. The core tracks of the research conference were complemented with new tracks focusing on linked data;
Описание: This book introduces a new paradigm called ‘Optimization in Changeable Spaces’ (OCS) as a useful tool for decision making and problem solving. It illustrates how OCS incorporates, searches, and constructively restructures the parameters, tangible and intangible, involved in the process of decision making. The book elaborates on OCS problems that can be modeled and solved effectively by using the concepts of competence set analysis, Habitual Domain (HD) and the mental operators called the 7-8-9 principles of deep knowledge of HD. In addition, new concepts of covering and discovering processes are proposed and formulated as mathematical tools to solve OCS problems. The book also includes reformulations of a number of illustrative real-life challenging problems that cannot be solved by traditional optimization techniques into OCS problems, and details how they can be addressed. Beyond that, it also includes perspectives related to innovation dynamics, management, artificial intelligence, artificial and e-economics, scientific discovery and knowledge extraction. This book will be of interest to managers of businesses and institutions, policy makers, and educators and students of decision making and behavior in DBA and/or MBA.
Описание: This book presents and develops new reinforcement learning methods that enable fast and robust learning on robots in real-time. It presents a novel model-based reinforcement learning algorithm.
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