Cross Lingual Word Embeddings For Knowledge Transfer In Less Represented Languages
DOWNLOAD
Download Cross Lingual Word Embeddings For Knowledge Transfer In Less Represented Languages PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Cross Lingual Word Embeddings For Knowledge Transfer In Less Represented Languages book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Cross Lingual Word Embeddings For Knowledge Transfer In Less Represented Languages
DOWNLOAD
Author : Tadej Škvorc (računalničar.)
language : en
Publisher:
Release Date : 2022
Cross Lingual Word Embeddings For Knowledge Transfer In Less Represented Languages written by Tadej Škvorc (računalničar.) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Cross Lingual Word Embeddings
DOWNLOAD
Author : Anders Søgaard
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Cross Lingual Word Embeddings written by Anders Søgaard and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
The majority of natural language processing (NLP) is English language processing, and while there is good language technology support for (standard varieties of) English, support for Albanian, Burmese, or Cebuano--and most other languages--remains limited. Being able to bridge this digital divide is important for scientific and democratic reasons but also represents an enormous growth potential. A key challenge for this to happen is learning to align basic meaning-bearing units of different languages. In this book, the authors survey and discuss recent and historical work on supervised and unsupervised learning of such alignments. Specifically, the book focuses on so-called cross-lingual word embeddings. The survey is intended to be systematic, using consistent notation and putting the available methods on comparable form, making it easy to compare wildly different approaches. In so doing, the authors establish previously unreported relations between these methods and are able to present a fast-growing literature in a very compact way. Furthermore, the authors discuss how best to evaluate cross-lingual word embedding methods and survey the resources available for students and researchers interested in this topic.
Eurowordnet A Multilingual Database With Lexical Semantic Networks
DOWNLOAD
Author : Piek Vossen
language : en
Publisher: Springer Science & Business Media
Release Date : 1998-10-31
Eurowordnet A Multilingual Database With Lexical Semantic Networks written by Piek Vossen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-10-31 with Computers categories.
Describes the main objective of EuroWordNet, which is the building of a multilingual database with lexical semantic networks or wordnets for several European languages. The six contributions look at: the linguistic design of the EuroWordNet database; the top-down strategy for building EuroWordNet: vocabulary coverage, base concepts and top ontology; applying EuroWordNet to cross-language text retrieval; and cross-linguistic alignment of Wordnets with an inter-lingual-index. Intended for scholars in the field and researchers in semantics and knowledge engineering. Reprinted from Computers and the Humanities, v.32, nos.2-3, 1998. Annotation copyrighted by Book News, Inc., Portland, OR
Ai Breakthroughs
DOWNLOAD
Author : Gopee Mukhopadhyay
language : en
Publisher: Educohack Press
Release Date : 2025-01-03
Ai Breakthroughs written by Gopee Mukhopadhyay and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.
The illustrations in this book are created by “Team Educohack”. AI Breakthroughs: Theories and Concepts for Today is designed to guide readers through the essential scientific and technological principles that make artificial intelligence (AI) possible. We aim to enhance understanding of AI's development and its pervasive role in our lives. We explore two fundamental questions: Should AI replicate human performance through machines, or should it emulate the way humans think and act? This book discusses "classical AI" and machine learning (ML), the two main approaches to AI. While classical AI, dating back to the 1960s, uses logic and representations to mimic human reasoning, ML, a newer method, focuses on manipulating numbers and statistical patterns to find answers. Drawing insights from Daniel Kahneman's Behavioral Economics, we demonstrate that purely rational AI, operating solely on logical symbols, does not reflect human thought processes. This book is crafted to support students, helping them grasp each concept in detail and ensuring they benefit from a thorough understanding of AI.
Multilingual Artificial Intelligence
DOWNLOAD
Author : Peng Wang
language : en
Publisher: Taylor & Francis
Release Date : 2025-04-29
Multilingual Artificial Intelligence written by Peng Wang and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-29 with Computers categories.
Multilingual Artificial Intelligence is a guide for non-computer science specialists and learners looking to explore the implementation of AI technologies to solve real-life problems involving language data. Focusing on multilingual, multicultural, pre-trained large language models and their practical use through fine-tuning and prompt engineering, Wang and Smith demonstrate how to apply this new technology in areas such as information retrieval, semantic webs, and retrieval augmented generation, to improve both human productivity and machine intelligence. Finally, they discuss the human impact of language technologies in the cultural context, and provide an AI competence framework for users to design their own learning journey. This innovative text is essential reading for all students, professionals, and researchers in language, linguistics, and related areas looking to understand how to integrate multilingual and multicultural artificial intelligence technology into their research and practice.
Further With Knowledge Graphs
DOWNLOAD
Author : M. Alam
language : en
Publisher: IOS Press
Release Date : 2021-09-23
Further With Knowledge Graphs written by M. Alam and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-23 with Computers categories.
The field of semantic computing is highly diverse, linking areas such as artificial intelligence, data science, knowledge discovery and management, big data analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence, and enterprise vocabulary management. As such it forms an essential part of the computing technology that underpins all our lives today. This volume presents the proceedings of SEMANTiCS 2021, the 17th International Conference on Semantic Systems. As a result of the continuing Coronavirus restrictions, SEMANTiCS 2021 was held in a hybrid form in Amsterdam, the Netherlands, from 6 to 9 September 2021. The annual SEMANTiCS conference provides an important platform for semantic computing professionals and researchers, and attracts information managers, ITarchitects, software engineers, and researchers from a wide range of organizations, such as research facilities, NPOs, public administrations and the largest companies in the world. The subtitle of the 2021 conference’s was “In the Era of Knowledge Graphs”, and 66 submissions were received, from which the 19 papers included here were selected following a rigorous single-blind reviewing process; an acceptance rate of 29%. Topics covered include data science, machine learning, logic programming, content engineering, social computing, and the Semantic Web, as well as the additional sub-topics of digital humanities and cultural heritage, legal tech, and distributed and decentralized knowledge graphs. Providing an overview of current research and development, the book will be of interest to all those working in the field of semantic systems.
Intelligent Data Engineering And Automated Learning Ideal 2021
DOWNLOAD
Author : Hujun Yin
language : en
Publisher: Springer Nature
Release Date : 2021-11-23
Intelligent Data Engineering And Automated Learning Ideal 2021 written by Hujun Yin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-23 with Computers categories.
This book constitutes the refereed proceedings of the 22nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2021, which took place during November 25-27, 2021. The conference was originally planned to take place in Manchester, UK, but was held virtually due to the COVID-19 pandemic. The 61 full papers included in this book were carefully reviewed and selected from 85 submissions. They deal with emerging and challenging topics in intelligent data analytics and associated machine learning paradigms and systems. Special sessions were held on clustering for interpretable machine learning; machine learning towards smarter multimodal systems; and computational intelligence for computer vision and image processing.
Machine Translation
DOWNLOAD
Author : Tong Xiao
language : en
Publisher: Springer Nature
Release Date : 2022-12-08
Machine Translation written by Tong Xiao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-08 with Computers categories.
This book constitutes the refereed proceedings of the 18th China Conference on Machine Translation, CCMT 2022, held in Lhasa, China, during August 6–10, 2022. The 16 full papers were included in this book were carefully reviewed and selected from 73 submissions.
Word Sense Disambiguation
DOWNLOAD
Author : Eneko Agirre
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-11-16
Word Sense Disambiguation written by Eneko Agirre and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-16 with Language Arts & Disciplines categories.
Graeme Hirst University of Toronto Of the many kinds of ambiguity in language, the two that have received the most attention in computational linguistics are those of word senses and those of syntactic structure, and the reasons for this are clear: these ambiguities are overt, their resolution is seemingly essential for any prac- cal application, and they seem to require a wide variety of methods and knowledge-sources with no pattern apparent in what any particular - stance requires. Right at the birth of artificial intelligence, in his 1950 paper “Computing machinery and intelligence”, Alan Turing saw the ability to understand language as an essential test of intelligence, and an essential test of l- guage understanding was an ability to disambiguate; his example involved deciding between the generic and specific readings of the phrase a winter’s day. The first generations of AI researchers found it easy to construct - amples of ambiguities whose resolution seemed to require vast knowledge and deep understanding of the world and complex inference on this kno- edge; for example, Pharmacists dispense with accuracy. The disambig- tion problem was, in a way, nothing less than the artificial intelligence problem itself. No use was seen for a disambiguation method that was less than 100% perfect; either it worked or it didn’t. Lexical resources, such as they were, were considered secondary to non-linguistic common-sense knowledge of the world.
Natural Language Processing With Python
DOWNLOAD
Author : Dr. Bharti Salunke
language : en
Publisher: Xoffencerpublication
Release Date : 2024-11-06
Natural Language Processing With Python written by Dr. Bharti Salunke and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-06 with Computers categories.
Natural Language Processing (NLP) is a rapidly evolving field within artificial intelligence that focuses on the interaction between computers and human languages. It is concerned with the ability of machines to read, understand, and generate human language in a way that is both meaningful and contextually relevant. The integration of NLP with Python has revolutionized this domain, as Python's simplicity, versatility, and extensive libraries make it an ideal tool for developing NLP applications. This abstract delves into the essential aspects of NLP using Python, exploring key concepts, tools, and techniques that enable machines to process and analyze large amounts of natural language data. At its core, NLP involves several fundamental tasks, including tokenization, part-of-speech tagging, named entity recognition, syntactic parsing, and sentiment analysis. Python, with its rich ecosystem of libraries such as NLTK, spaCy, and transformers, provides an accessible and robust framework for tackling these tasks. Tokenization, for instance, breaks down text into smaller units such as words or sentences, which forms the foundation for many NLP applications. Part-of-speech tagging assigns grammatical labels to words, while named entity recognition identifies specific entities like names, dates, or locations within the text. Syntactic parsing helps in understanding the grammatical structure of sentences, and sentiment analysis enables machines to determine the emotional tone of a piece of text. One of the significant advancements in NLP is the application of machine learning techniques to language processing. Python’s libraries such as scikit-learn, TensorFlow, and PyTorch offer powerful tools for training models that can predict and classify language data. Deep learning models, particularly those based on neural networks, have led to major breakthroughs in tasks like machine translation, speech recognition, and question answering. Pre-trained models like BERT and GPT, implemented through Python frameworks, have set new benchmarks in NLP, allowing developers to build more sophisticated and accurate systems with minimal training data.