Download or read book Approaching Language Transfer Through Text Classification written by Scott Jarvis and published by Multilingual Matters. This book was released on 2012 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume explains the detection-based approach to investigating crosslinguistic influence and illustrates the value of the approach through a collection of five empirica studies that use the approach to quantify, evaluate, and isolate the influences of learners' native-language backgrounds on their English writing.

Download or read book Approaching Language Transfer Through Text Classification written by Scott Jarvis and published by Multilingual Matters. This book was released on 2012-03-14 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains the detectionbased approach to investigating crosslinguistic influence and illustrates the value of the approach through a collection of five empirical studies that use the approach to quantify, evaluate, and isolate the subtle and complex influences of learners’ nativelanguage backgrounds on their English writing.

Download or read book Cross Lingual Word Embeddings written by Anders Søgaard and published by Springer Nature. This book was released on 2022-05-31 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Crosslinguistic Influence and Distinctive Patterns of Language Learning written by Anne Golden and published by Multilingual Matters. This book was released on 2017-09-22 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book details patterns of language use that can be found in the writing of adult immigrant learners of Norwegian as a second language (L2). Each study draws its data from a single corpus of texts written for a proficiency test of L2 Norwegian by learners representing 10 different first language (L1) backgrounds. The participants of the study are immigrants to Norway and the book deals with the varying levels and types of language difficulties faced by such learners from differing backgrounds. The studies examine the learners’ use of Norwegian in relation to the morphological, syntactic, lexical, semantic and pragmatic patterns they produce in their essays. Nearly all the studies in the book rely on analytical methods specifically designed to isolate the effects of the learners’ L1s on their use of L2 Norwegian, and every chapter highlights patterns that distinguish different L1 groups from one another.

Download or read book Practical Natural Language Processing written by Sowmya Vajjala and published by O'Reilly Media. This book was released on 2020-06-17 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective

Download or read book Natural Language Processing Practical Approach written by Syed Muzamil Basha and published by MileStone Research Publications. This book was released on 2023-02-26 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: The "Natural Language Processing Practical Approach" is a textbook that provides a practical introduction to the field of Natural Language Processing (NLP). The goal of the textbook is to provide a hands-on, practical guide to NLP, with a focus on real-world applications and use cases. The textbook covers a range of NLP topics, including text preprocessing, sentiment analysis, named entity recognition, text classification, and more. The textbook emphasizes the use of algorithms and models to solve NLP problems and provides practical examples and code snippets in various programming languages, including Python. The textbook is designed for students, researchers, and practitioners in NLP who want to gain a deeper understanding of the field and build their own NLP projects. The current state of NLP is rapidly evolving with advancements in machine learning and deep learning techniques. The field has seen a significant increase in research and development efforts in recent years, leading to improved performance and new applications in areas such as sentiment analysis, text classification, language translation, and named entity recognition. The future prospects of NLP are bright, with continued development in areas such as reinforcement learning, transfer learning, and unsupervised learning, which are expected to further improve the performance of NLP models. Additionally, increasing amounts of text data available through the internet and growing demand for human-like conversational interfaces in areas such as customer service and virtual assistants will likely drive further advancements in NLP. The benefits of a hands-on, practical approach to natural language processing include: 1. Improved understanding: Practical approaches allow students to experience the concepts and techniques in action, helping them to better understand how NLP works. 2. Increased motivation: Hands-on approaches to learning can increase student engagement and motivation, making the learning process more enjoyable and effective. 3. Hands-on experience: By working with real data and implementing NLP techniques, students gain hands-on experience in applying NLP techniques to real-world problems. 4. Improved problem-solving skills: Practical approaches help students to develop problem-solving skills by working through real-world problems and challenges. 5. Better retention: When students have hands-on experience with NLP techniques, they are more likely to retain the information and be able to apply it in the future. A comprehensive understanding of NLP would include knowledge of its various tasks, techniques, algorithms, challenges, and applications. It also involves understanding the basics of computational linguistics, natural language understanding, and text representation methods such as tokenization, stemming, and lemmatization. Moreover, hands-on experience with NLP tools and libraries like NLTK, Spacy, and PyTorch would also enhance one's understanding of NLP.

Download or read book An Efficient Approach to Machine Learning Based Text Classification Through Distributed Computing written by Raghu Nandan Immaneni and published by . This book was released on 2015 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Text classification is one of the classical problems in computer science, which is primarily used for categorizing data, spam detection, anonymization, information extraction, text summarization etc. Given the large amounts of data involved in the above applications, automated and accurate training models and approaches to classify data efficiently are needed. In this thesis, an extensive study of the interaction between natural language processing, information retrieval and text classification has been performed. A case study named "keyword extraction" that deals with 'identifying keywords and tags from millions of text questions' is used as a reference. Different classifiers are implemented using MapReduce paradigm on the case study and the experimental results are recorded using two newly built distributed computing Hadoop clusters. The main aim is to enhance the prediction accuracy, to examine the role of text pre-processing for noise elimination and to reduce the computation time and resource utilization on the clusters.

Download or read book An Evolutionary Approach to Text Classification written by and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Inductive Inference for Large Scale Text Classification written by Catarina Silva and published by Springer. This book was released on 2010-04-30 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text classification is becoming a crucial task to analysts in different areas. In the last few decades, the production of textual documents in digital form has increased exponentially. Their applications range from web pages to scientific documents, including emails, news and books. Despite the widespread use of digital texts, handling them is inherently difficult - the large amount of data necessary to represent them and the subjectivity of classification complicate matters. This book gives a concise view on how to use kernel approaches for inductive inference in large scale text classification; it presents a series of new techniques to enhance, scale and distribute text classification tasks. It is not intended to be a comprehensive survey of the state-of-the-art of the whole field of text classification. Its purpose is less ambitious and more practical: to explain and illustrate some of the important methods used in this field, in particular kernel approaches and techniques.

Download or read book Knowledge Transfer between Computer Vision and Text Mining written by Radu Tudor Ionescu and published by Springer. This book was released on 2016-04-25 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: This ground-breaking text/reference diverges from the traditional view that computer vision (for image analysis) and string processing (for text mining) are separate and unrelated fields of study, propounding that images and text can be treated in a similar manner for the purposes of information retrieval, extraction and classification. Highlighting the benefits of knowledge transfer between the two disciplines, the text presents a range of novel similarity-based learning (SBL) techniques founded on this approach. Topics and features: describes a variety of SBL approaches, including nearest neighbor models, local learning, kernel methods, and clustering algorithms; presents a nearest neighbor model based on a novel dissimilarity for images; discusses a novel kernel for (visual) word histograms, as well as several kernels based on a pyramid representation; introduces an approach based on string kernels for native language identification; contains links for downloading relevant open source code.

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.

Download or read book Graph theoretic Approaches to Text Classification written by Niloofer Shanavas and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Data Augmentation Approach to Short Text Classification written by RYAN ROBERT ROSARIO and published by . This book was released on 2017 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text classification typically performs best with large training sets, but short texts are very common on the World Wide Web. Can we use resampling and data augmentation to construct larger texts using similar terms? Several current methods exist for working with short text that rely on using external data and contexts, or workarounds. Our focus is to test a new preprocessing approach that uses resampling, inspired by the bootstrap, combined with data augmentation, by treating each short text as a population and sampling similar words from a semantic space to create a longer text. We use blog post titles collected from the Technorati blog aggregator as experimental data with each title appearing in one of ten categories. We first test how well the raw short texts are classified using a variant of SVM designed specifically for short texts as well as a supervised topic model and an SVM model that uses semantic vectors as features. We then build a semantic space and augment each short text with related terms under a variety of experimental conditions. We test the classifiers on the augmented data and compare performance to the aforementioned baselines. The classifier performance on augmented test sets outperformed the baseline classifiers in most cases.

Download or read book Multilingual Text Classification Using Information theoretic Features written by Zahurul Islam and published by . This book was released on 2015 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Text Classification Method Review written by A. Mahinovs and published by . This book was released on 2005 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Bible Translator written by and published by . This book was released on 1984 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Toward a Multi sensor based Approach to Automatic Text Classification written by Venugopala Rao Dasigi and published by . This book was released on 1995 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: