Data Filtering Using Cross Lingual Word Embeddings
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| Author | : Anders Søgaard |
| Publisher | : Springer Nature |
| Total Pages | : 120 |
| Release | : 2022-05-31 |
| Genre | : Computers |
| ISBN | : 3031021711 |
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.
| Author | : Emil Hvitfeldt |
| Publisher | : CRC Press |
| Total Pages | : 402 |
| Release | : 2021-10-22 |
| Genre | : Computers |
| ISBN | : 1000461971 |
Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance using tools from the tidyverse and tidymodels ecosystem. Models like these can be used to make predictions for new observations, to understand what natural language features or characteristics contribute to differences in the output, and more. If you are already familiar with the basics of predictive modeling, use the comprehensive, detailed examples in this book to extend your skills to the domain of natural language processing. This book provides practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate unstructured text data into their modeling pipelines. Learn how to use text data for both regression and classification tasks, and how to apply more straightforward algorithms like regularized regression or support vector machines as well as deep learning approaches. Natural language must be dramatically transformed to be ready for computation, so we explore typical text preprocessing and feature engineering steps like tokenization and word embeddings from the ground up. These steps influence model results in ways we can measure, both in terms of model metrics and other tangible consequences such as how fair or appropriate model results are.
| Author | : Gloria Corpas Pastor |
| Publisher | : Springer Nature |
| Total Pages | : 460 |
| Release | : 2019-09-18 |
| Genre | : Computers |
| ISBN | : 3030301354 |
This book constitutes the refereed proceedings of the Third International Conference on Computational and Corpus-Based Phraseology, Europhras 2019, held in Malaga, Spain, in September 2019. The 31 full papers presented in this book were carefully reviewed and selected from 116 submissions. The papers in this volume cover a number of topics including general corpus-based approaches to phraseology, phraseology in translation and cross-linguistic studies, phraseology in language teaching and learning, phraseology in specialized languages, phraseology in lexicography, cognitive approaches to phraseology, the computational treatment of multiword expressions, and the development, annotation, and exploitation of corpora for phraseological studies.
| Author | : Ngoc Hoang Thanh Dang |
| Publisher | : Springer Nature |
| Total Pages | : 738 |
| Release | : 2022-05-18 |
| Genre | : Computers |
| ISBN | : 3030976106 |
The book presents studies related to artificial intelligence (AI) and its applications to process and analyze data and big data to create machines or software that can better understand business behavior, industry activities, and human health. The studies were presented at “The 2021 International Conference on Artificial Intelligence and Big Data in Digital Era” (ICABDE 2021), which was held in Ho Chi Minh City, Vietnam, during December 18-19, 2021. The studies are pointing toward the famous slogan in technology “Make everything smarter,” i.e., creating machines that can understand and can communicate with humans, and they must act like humans in different aspects such as vision, communication, thinking, feeling, and acting. “A computer would deserve to be called intelligent if it could deceive a human into believing that it was human” —Alan Turing
| Author | : Piek Vossen |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 180 |
| Release | : 2013-11-11 |
| Genre | : Computers |
| ISBN | : 9401714916 |
This book describes the main objective of EuroWordNet, which is the building of a multilingual database with lexical semantic networks or wordnets for several European languages. Each wordnet in the database represents a language-specific structure due to the unique lexicalization of concepts in languages. The concepts are inter-linked via a separate Inter-Lingual-Index, where equivalent concepts across languages should share the same index item. The flexible multilingual design of the database makes it possible to compare the lexicalizations and semantic structures, revealing answers to fundamental linguistic and philosophical questions which could never be answered before. How consistent are lexical semantic networks across languages, what are the language-specific differences of these networks, is there a language-universal ontology, how much information can be shared across languages? First attempts to answer these questions are given in the form of a set of shared or common Base Concepts that has been derived from the separate wordnets and their classification by a language-neutral top-ontology. These Base Concepts play a fundamental role in several wordnets. Nevertheless, the database may also serve many practical needs with respect to (cross-language) information retrieval, machine translation tools, language generation tools and language learning tools, which are discussed in the final chapter. The book offers an excellent introduction to the EuroWordNet project for scholars in the field and raises many issues that set the directions for further research in semantics and knowledge engineering.
| Author | : Le-Minh Nguyen |
| Publisher | : Springer Nature |
| Total Pages | : 525 |
| Release | : 2020-07-01 |
| Genre | : Computers |
| ISBN | : 9811561680 |
This book constitutes the refereed proceedings of the 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, held in Hanoi, Vietnam, in October 2019. The 28 full papers and 14 short papers presented were carefully reviewed and selected from 70 submissions. The papers are organized in topical sections on text summarization; relation and word embedding; machine translation; text classification; web analyzing; question and answering, dialog analyzing; speech and emotion analyzing; parsing and segmentation; information extraction; and grammar error and plagiarism detection.
| Author | : Serge Sharoff |
| Publisher | : Springer Nature |
| Total Pages | : 138 |
| Release | : 2023-08-23 |
| Genre | : Computers |
| ISBN | : 3031313844 |
This book provides a comprehensive overview of methods to build comparable corpora and of their applications, including machine translation, cross-lingual transfer, and various kinds of multilingual natural language processing. The authors begin with a brief history on the topic followed by a comparison to parallel resources and an explanation of why comparable corpora have become more widely used. In particular, they provide the basis for the multilingual capabilities of pre-trained models, such as BERT or GPT. The book then focuses on building comparable corpora, aligning their sentences to create a database of suitable translations, and using these sentence translations to produce dictionaries and term banks. Then, it is explained how comparable corpora can be used to build machine translation engines and to develop a wide variety of multilingual applications.
| Author | : Alexander Sychev |
| Publisher | : Springer Nature |
| Total Pages | : 231 |
| Release | : 2021-07-15 |
| Genre | : Computers |
| ISBN | : 3030812006 |
This book constitutes the post-conference proceedings of the 22nd International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2020, held in Voronezh, Russia, in October 2020*. The 16 revised full papers and two keynotes were carefully reviewed and selected from 60 submissions. The papers are organized in the following topical sections: data Integration, conceptual models and ontologies; data management in semantic web; data analysis in medicine; data analysis in astronomy; information extraction from text. * The conference was held virtually due to the COVID-19 pandemic.
| Author | : Mohammad Taher Pilehvar |
| Publisher | : Morgan & Claypool Publishers |
| Total Pages | : 177 |
| Release | : 2020-11-13 |
| Genre | : Computers |
| ISBN | : 1636390226 |
Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP). Encoding information into a low-dimensional vector representation, which is easily integrable in modern machine learning models, has played a central role in the development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures, such as knowledge bases, to other types of textual content, such as sentences and documents. This book provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings. The book also provides an overview of recent developments in contextualized representations (e.g., ELMo and BERT) and explains their potential in NLP. Throughout the book, the reader can find both essential information for understanding a certain topic from scratch and a broad overview of the most successful techniques developed in the literature.
| Author | : Alexei Pozanenko |
| Publisher | : Springer Nature |
| Total Pages | : 272 |
| Release | : 2022-07-25 |
| Genre | : Computers |
| ISBN | : 3031122852 |
This book constitutes the post-conference proceedings of the 23rd International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2021, held in Moscow, Russia, in October 2021*. The 16 revised full papers were carefully reviewed and selected from 61 submissions. The papers are organized in the following topical sections: problem solving infrastructures, experiment organization, and machine learning applications; data analysis in astronomy; data analysis in material and earth sciences; information extraction from text * The conference was held virtually due to the COVID-19 pandemic.
