Word Embeddings Reliability Semantic Change

Author : J. Hellrich
Publisher : IOS Press
ISBN 13 : 1614999953
Total Pages : 190 pages
Book Rating : 4.59/5 ( download)

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Download or read book Word Embeddings: Reliability & Semantic Change written by J. Hellrich and published by IOS Press. This book was released on 2019-08-08 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Word embeddings are a form of distributional semantics increasingly popular for investigating lexical semantic change. However, typical training algorithms are probabilistic, limiting their reliability and the reproducibility of studies. Johannes Hellrich investigated this problem both empirically and theoretically and found some variants of SVD-based algorithms to be unaffected. Furthermore, he created the JeSemE website to make word embedding based diachronic research more accessible. It provides information on changes in word denotation and emotional connotation in five diachronic corpora. Finally, the author conducted two case studies on the applicability of these methods by investigating the historical understanding of electricity as well as words connected to Romanticism. They showed the high potential of distributional semantics for further applications in the digital humanities.

Author : Johannes Hellrich
Publisher :
ISBN 13 : 9783898387446
Total Pages : pages
Book Rating : 4.45/5 ( download)

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Download or read book Word Embeddings written by Johannes Hellrich and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Emil Hvitfeldt
Publisher : CRC Press
ISBN 13 : 1000461971
Total Pages : 402 pages
Book Rating : 4.78/5 ( download)

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Download or read book Supervised Machine Learning for Text Analysis in R written by Emil Hvitfeldt and published by CRC Press. This book was released on 2021-10-22 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : K. Sauerwald
Publisher : IOS Press
ISBN 13 : 164368325X
Total Pages : 368 pages
Book Rating : 4.56/5 ( download)

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Download or read book Semantics of Belief Change Operators for Intelligent Agents: Iteration, Postulates, and Realizability written by K. Sauerwald and published by IOS Press. This book was released on 2022-11-03 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the core problems in artificial intelligence is the modelling of human reasoning and intelligent behaviour. The representation of knowledge, and reasoning about it, are of crucial importance in achieving this. This book, Semantics of Belief Change Operators for Intelligent Agents: Iteration, Postulates, and Realizability, addresses a number of significant research questions in belief change theory from a semantic point of view; in particular, the connection between different types of belief changes and plausibility relations over possible worlds is investigated. This connection is characterized for revision over general classical logics, showing which relations are capturing AGM revision. In addition, those classical logics for which the correspondence between AGM revision and total preorders holds are precisely characterized. AGM revision in the Darwiche-Pearl framework for belief change over arbitrary sets of epistemic states is considered, demonstrating, especially, that for some sets of epistemic states, no AGM revision operator exists. A characterization of those sets of epistemic states for which AGM revision operators exist is presented. The expressive class of dynamic limited revision operators is introduced to provide revision operators for more sets of epistemic states. Specifications for the acceptance behaviour of various belief-change operators are examined, and those realizable by dynamic-limited revision operators are described. The iteration of AGM contraction in the Darwiche-Pearl framework is explored in detail, several known and novel iteration postulates for contraction are identified, and the relationships among these various postulates are determined. With a convincing presentation of ideas, the book refines and advances existing proposals of belief change, develops novel concepts and approaches, rigorously defines the concepts introduced, and formally proves all technical claims, propositions and theorems, significantly advancing the state-of-the-art in this field.

Author : Andreas Blank
Publisher : Walter de Gruyter
ISBN 13 : 3110804190
Total Pages : 320 pages
Book Rating : 4.95/5 ( download)

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Download or read book Historical Semantics and Cognition written by Andreas Blank and published by Walter de Gruyter. This book was released on 2013-03-25 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains revised papers from a September 1996 symposium which provided a forum for synchronically and diachronically oriented scholars to exchange ideas and for American and European cognitive linguists to confront representatives of different directions in European structural semantics. Papers are in sections on theories and models, descriptive categories, and case studies, and examine areas such as cognitive and structural semantics, diachronic prototype semantics, synecdoche as a cognitive and communicative strategy, and intensifiers as targets and sources of semantic change.

Author : L. Grumbach
Publisher : IOS Press
ISBN 13 : 1643683977
Total Pages : 340 pages
Book Rating : 4.73/5 ( download)

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Download or read book Flexible Workflows written by L. Grumbach and published by IOS Press. This book was released on 2023-07-07 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditional workflow management systems support the fulfillment of business tasks by providing guidance along a predefined workflow model. Due to the shift from mass production to customization, flexibility has become important in recent decades, but the various approaches to workflow flexibility either require extensive knowledge acquisition and modeling, or active intervention during execution. Pursuing flexibility by deviation compensates for these disadvantages by allowing alternative paths of execution at run time without requiring adaptation to the workflow model. This work, Flexible Workflows: A Constraint- and Case-Based Approach, proposes a novel approach to flexibility by deviation, the aim being to provide support during the execution of a workflow by suggesting items based on predefined strategies or experiential knowledge, even in case of deviations. The concepts combine two familiar methods from the field of AI - constraint satisfaction problem solving, and process-oriented case-based reasoning. The combined model increases the capacity for flexibility. The experimental evaluation of the approach consisted of a simulation involving several types of participant in the domain of deficiency management in construction. The book contains 7 chapters covering foundations; domains and potentials; prerequisites; constraint based workflow engine; case based deviation management; prototype; and evaluation, together with an introduction, a conclusion and 3 appendices. Demonstrating high utility values and the promise of wide applicability in practice, as well as the potential for an investigation into the transfer of the approach to other domains, the book will be of interest to all those whose work involves workflow management systems.

Author : L. Berov
Publisher : IOS Press
ISBN 13 : 1643683837
Total Pages : 362 pages
Book Rating : 4.36/5 ( download)

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Download or read book From Narratology to Computational Story Composition and Back written by L. Berov and published by IOS Press. This book was released on 2023-03-10 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although both deal with narratives, the two disciplines of Narrative Theory (NT) and Computational Story Composition (CSC) rarely exchange insights and ideas or engage in collaborative research. The former has its roots in the humanities, and attempts to analyze literary texts to derive an understanding of the concept of narrative. The latter is in the domain of Artificial Intelligence, and investigates the autonomous composition of fictional narratives in a way that could be deemed creative. The two disciplines employ different research methodologies at contradistinct levels of abstraction, making simultaneous research difficult, while a close exchange between the two disciplines would undoubtedly be desirable, not least because of the complementary approach to their object of study. This book, From Narratology to Computational Story Composition and Back, describes an exploratory study in generative modeling, a research methodology proposed to address the methodological differences between the two disciplines and allow for simultaneous NT and CSC research. It demonstrates how implementing narratological theories as computational, generative models can lead to insights for NT, and how grounding computational representations of narrative in NT can help CSC systems to take over creative responsibilities. It is the interplay of these two strands that underscores the feasibility and utility of generative modeling. The book is divided into 6 chapters: an introduction, followed by chapters on plot, fictional characters, plot quality estimation, and computational creativity, wrapped up by a conclusion. The book will be of interest to all those working in the fields of narrative theory and computational creativity.

Author : Nina Tahmasebi
Publisher : Language Science Press
ISBN 13 : 3961103127
Total Pages : 396 pages
Book Rating : 4.26/5 ( download)

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Download or read book Computational approaches to semantic change written by Nina Tahmasebi and published by Language Science Press. This book was released on 2021-08-30 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Semantic change — how the meanings of words change over time — has preoccupied scholars since well before modern linguistics emerged in the late 19th and early 20th century, ushering in a new methodological turn in the study of language change. Compared to changes in sound and grammar, semantic change is the least understood. Ever since, the study of semantic change has progressed steadily, accumulating a vast store of knowledge for over a century, encompassing many languages and language families. Historical linguists also early on realized the potential of computers as research tools, with papers at the very first international conferences in computational linguistics in the 1960s. Such computational studies still tended to be small-scale, method-oriented, and qualitative. However, recent years have witnessed a sea-change in this regard. Big-data empirical quantitative investigations are now coming to the forefront, enabled by enormous advances in storage capability and processing power. Diachronic corpora have grown beyond imagination, defying exploration by traditional manual qualitative methods, and language technology has become increasingly data-driven and semantics-oriented. These developments present a golden opportunity for the empirical study of semantic change over both long and short time spans. A major challenge presently is to integrate the hard-earned knowledge and expertise of traditional historical linguistics with cutting-edge methodology explored primarily in computational linguistics. The idea for the present volume came out of a concrete response to this challenge. The 1st International Workshop on Computational Approaches to Historical Language Change (LChange'19), at ACL 2019, brought together scholars from both fields. This volume offers a survey of this exciting new direction in the study of semantic change, a discussion of the many remaining challenges that we face in pursuing it, and considerably updated and extended versions of a selection of the contributions to the LChange'19 workshop, addressing both more theoretical problems — e.g., discovery of "laws of semantic change" — and practical applications, such as information retrieval in longitudinal text archives.

Author : Zhiyuan Liu
Publisher : Springer Nature
ISBN 13 : 9811555737
Total Pages : 319 pages
Book Rating : 4.32/5 ( download)

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Download or read book Representation Learning for Natural Language Processing written by Zhiyuan Liu and published by Springer Nature. This book was released on 2020-07-03 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.

Author : P. Welke
Publisher : IOS Press
ISBN 13 : 164368079X
Total Pages : 190 pages
Book Rating : 4.98/5 ( download)

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Download or read book Efficient Frequent Subtree Mining Beyond Forests written by P. Welke and published by IOS Press. This book was released on 2020-06-02 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: A common paradigm in distance-based learning is to embed the instance space into a feature space equipped with a metric and define the dissimilarity between instances by the distance of their images in the feature space. Frequent connected subgraphs are sometimes used to define such feature spaces if the instances are graphs, but identifying the set of frequent connected subgraphs and subsequently computing embeddings for graph instances is computationally intractable. As a result, existing frequent subgraph mining algorithms either restrict the structural complexity of the instance graphs or require exponential delay between the output of subsequent patterns, meaning that distance-based learners lack an efficient way to operate on arbitrary graph data. This book presents a mining system that gives up the demand on the completeness of the pattern set, and instead guarantees a polynomial delay between subsequent patterns. To complement this, efficient methods devised to compute the embedding of arbitrary graphs into the Hamming space spanned by the pattern set are described. As a result, a system is proposed that allows the efficient application of distance-based learning methods to arbitrary graph databases. In addition to an introduction and conclusion, the book is divided into chapters covering: preliminaries; related work; probabilistic frequent subtrees; boosted probabilistic frequent subtrees; and fast computation, with a further two chapters on Hamiltonian path for cactus graphs and Poisson binomial distribution.