Automated Taxonomy Discovery and Exploration, Shen
Автор: Rajendra Prasath; Alexander Gelbukh Название: Mining Intelligence and Knowledge Exploration ISBN: 3319581295 ISBN-13(EAN): 9783319581293 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Accepted papers were grouped into various subtopics including information retrieval, machine learning, pattern recognition, knowledge discovery, classification, clustering, image processing, network security, speech processing, natural language processing, language, cognition and computation, fuzzy sets, and business intelligence.
Автор: Nikos Pelekis; Yannis Theodoridis Название: Mobility Data Management and Exploration ISBN: 1493903918 ISBN-13(EAN): 9781493903917 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This text integrates different mobility data handling processes, from database management to multi-dimensional analysis and mining, into a unified presentation driven by the spectrum of requirements raised by real-world applications.
Автор: Rajendra Prasath; Philip O`Reilly; T. Kathirvalava Название: Mining Intelligence and Knowledge Exploration ISBN: 3319138162 ISBN-13(EAN): 9783319138169 Издательство: Springer Рейтинг: Цена: 8944.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The papers cover topics such as information retrieval, feature selection, classification, clustering, image processing, network security, speech processing, machine learning, recommender systems, natural language processing, language, cognition and computation, and business intelligence.
Автор: Piotr S. Szczepaniak; Javier Segovia; Lotfi A. Zad Название: Intelligent Exploration of the Web ISBN: 3790825190 ISBN-13(EAN): 9783790825190 Издательство: Springer Рейтинг: Цена: 26552.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Web is the nervous system of information society. The articles that comprise lEW address many basic problems ranging from structure analysis of Internet documents and Web dialogue management to intelligent Web agents for extraction of information, and bootstrapping an ontology-based information extraction system.
Автор: Hovy Dirk Название: Text Analysis in Python for Social Scientists ISBN: 1108819826 ISBN-13(EAN): 9781108819824 Издательство: Cambridge Academ Рейтинг: Цена: 2851.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Text is a fantastic resource for social scientists, but because it is so abundant, and so variable, it can be difficult to extract the information we want. Many basic text analysis methods are available as Python implementations: this Element will teach you when to use which method, how it works, and the Python code to implement it.
Автор: Bissett Название: Automated Data Analysis Using Excel, Second Edition ISBN: 1482250136 ISBN-13(EAN): 9781482250138 Издательство: Taylor&Francis Рейтинг: Цена: 10411.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This new edition includes some key topics relating to the latest version of MS Office, including use of the ribbon, current Excel file types, Dashboard, and basic Sharepoint integration. It shows how to automate operations, such as curve fitting, sorting, filtering, and analyzing data from a variety of sources.
Автор: Tao Li; Mitsunori Ogihara; George Tzanetakis Название: Music Data Mining ISBN: 1439835527 ISBN-13(EAN): 9781439835524 Издательство: Taylor&Francis Рейтинг: Цена: 16843.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles, artists, lyrics, and reviews. Bringing together an interdisciplinary array of top researchers, Music Data Mining presents a variety of approaches to successfully employ data mining techniques for the purpose of music processing.
The book first covers music data mining tasks and algorithms and audio feature extraction, providing a framework for subsequent chapters. With a focus on data classification, it then describes a computational approach inspired by human auditory perception and examines instrument recognition, the effects of music on moods and emotions, and the connections between power laws and music aesthetics. Given the importance of social aspects in understanding music, the text addresses the use of the Web and peer-to-peer networks for both music data mining and evaluating music mining tasks and algorithms. It also discusses indexing with tags and explains how data can be collected using online human computation games. The final chapters offer a balanced exploration of hit song science as well as a look at symbolic musicology and data mining.
The multifaceted nature of music information often requires algorithms and systems using sophisticated signal processing and machine learning techniques to better extract useful information. An excellent introduction to the field, this volume presents state-of-the-art techniques in music data mining and information retrieval to create novel ways of interacting with large music collections.
Описание: This book explains the word association thematic analysis method, with examples, and gives practical advice for using it. It is primarily intended for social media researchers and students, although the method is applicable to any collection of short texts.
Many research projects involve analyzing sets of texts from the social web or elsewhere to get insights into issues, opinions, interests, news discussions, or communication styles. For example, many studies have investigated reactions to Covid-19 social distancing restrictions, conspiracy theories, and anti-vaccine sentiment on social media. This book describes word association thematic analysis, a mixed methods strategy to identify themes within a collection of social web or other texts. It identifies these themes in the differences between subsets of the texts, including female vs. male vs. nonbinary, older vs. newer, country A vs. country B, positive vs. negative sentiment, high scoring vs. low scoring, or subtopic A vs. subtopic B. It can also be used to identify the differences between a topic-focused collection of texts and a reference collection.
The method starts by automatically finding words that are statistically significantly more common in one subset than another, then identifies the context of these words and groups them into themes. It is supported by the free Windows-based software Mozdeh for data collection or importing and for the quantitative analysis stages.
Автор: Ganter Bernhard, Obiedkov Sergei Название: Conceptual Exploration ISBN: 366256999X ISBN-13(EAN): 9783662569993 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Generalizations that handle incomplete, faulty, orimprecise data are discussed, but the focus lies on knowledge extraction from areliable information source.The method is based on Formal Concept Analysis, a mathematical theory ofconcepts and concept hierarchies, and uses its expressive diagrams.
Автор: Hoyt Robert, Muenchen Robert Название: Data Preparation and Exploration: Applied to Healthcare Data ISBN: 0988752972 ISBN-13(EAN): 9780988752979 Издательство: Неизвестно Рейтинг: Цена: 4876.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Data scientists spend more than two-thirds of their time cleaning, preparing, exploring, and visualizing data before it is ready for modeling and mining. This textbook covers the important steps of data preparation and exploration that anyone who deals with data should know. This textbook is an excellent companion text for our other textbook Introduction to Biomedical Data Science. The data preparation and exploration methods we include are spreadsheet and statistics package approaches, as well as the programming languages R and Python. The reader is introduced to the free stat packages Jamovi and BlueSky Statistics. Multiple techniques for data visualization are presented. Medical datasets are used for demonstrations and student exercises. Importantly, chapter content is supplemented with YouTube videos. Chapters are well referenced (100]) and there is a chapter on health data resources so the reader can find data to prepare and explore on their own. Prominent issues such as how to handle missing data and imbalanced datasets are covered along with sections on descriptive statistics, visualization, correlations, handling duplicates and outliers, scaling, standardization, and much more. A downloadable Data Checklist is available on https: //www.informaticseducation.org
Описание: Part I, Foundations.- AI Sculpture.- Make Me Learn.- Images and Sequences.- Why AI Works.- Learning to Sculpt.- Unleashing the Power of Generation.- The Road Most Rewarded.- The Classical World.- Part II, Applications.- To See is to Believe.- Read, Read, Read.- Lend Me Your Ear.- Create Your Shire and Rivendell.- Math to Code to Petaflops.- AI and Business.- Part III, Road Ahead.- Keep Marching on.- Benevolent AI for All.- Am I Looking at Myself?.- App. A, Solutions.- Further Reading.- Acronyms.- Glossary.- References.- Index.
Автор: Chbeir Название: Mining Intelligence and Knowledge Exploration ISBN: 3031215168 ISBN-13(EAN): 9783031215162 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes revised selected papers from the refereed proceedings of the 9th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2021, which took place in Hammamet, Tunisia, in November 2021. The 22 full papers included in this book were carefully reviewed and selected from 61 submissions. They deal with topics such as evolutionary computation, knowledge exploration in IoT, artificial intelligence, machine learning, data mining and information retrieval, medical image analysis, pattern recognition and computer vision, speech / signal processing, text mining and natural language processing, intelligent security systems, Smart and Intelligent Systems, etc.
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