This book examines contemporary American ethnic novels through the lens of affect studies, focusing on the political and cultural implications of negative affects in literary representation.Analysing works by Native American, African American, Jewish American, Latinx, and Asian American writers since the Civil Rights era, it explores how affects such as anxiety, irritation, and alienation illuminate the predicaments of marginalised communities, including racial inequality, cultural...

This book explores Vladimir Nabokov's literary thoughts, which blend Russian traditions, American values, European heritage, and multiculturalism, manifesting the cosmopolitan character of his writings and aesthetic ideas.Nabokov’s literary thoughts and writings inherit the legacies of various cultural traditions. This book explores four major facets of Nabokov’s intellectual and artistic origins: “Russianness,” “Americanness,” “Europeanness,” and multiculturalism. It discusses his...

Focusing on the poetry and cultural practice of Frank O’Hara, the great urban poet of the New York School during the 1950s and 1960s, this books explores the interwoven relationship between his urban poetics and the urban culture of New York, seeking to shed light on poetic concept and its cultural relevance.The poetry of Frank O’Hara is deeply rooted in and nourished by his urban experience as a metropolitan and an active participant in the vibrant cultural scene of New York. Ther...

This unique compendium provides a novel research on how time influences the conversions of advertising and product recommendation in E-commerce. It proposes time-aware conversion prediction models to solve the problem — what products should be recommended for a given period to maximize conversion? The volume also presents a series of researches on how to build data-driven attribution models to allocate the time-sensitive contribution of advertisements to the conversion. This must-have refe...

This book provides a comprehensive introduction on opinion analysis for online reviews. It offers the newest research on opinion mining, including theories, algorithms and datasets. A new feature presentation method is highlighted for sentiment classification. Then, a three-phase framework for sentiment classification is proposed, where a set of sentiment classifiers are selected automatically to make predictions. Such predictions are integrated via ensemble learning. Finally, to solve the...

In plain, uncomplicated language, and using detailed examples to explain the key concepts, models, and algorithms in vertical search ranking, Relevance Ranking for Vertical Search Engines teaches readers how to manipulate ranking algorithms to achieve better results in real-world applications. This reference book for professionals covers concepts and theories from the fundamental to the advanced, such as relevance, query intention, location-based relevance ranking, and cross-property ranki...

This successful textbook on predictive text mining offers a unified perspective on a rapidly evolving field, integrating topics spanning the varied disciplines of data science, machine learning, databases, and computational linguistics. Serving also as a practical guide, this unique book provides helpful advice illustrated by examples and case studies. This highly anticipated second edition has been thoroughly revised and expanded with new material on deep learning, graph models, mining so...

This book provides a systematic and comparative description of the vast number of research issues related to the quality of data and information. It does so by delivering a sound, integrated and comprehensive overview of the state of the art and future development of data and information quality in databases and information systems.To this end, it presents an extensive description of the techniques that constitute the core of data and information quality research, including record ...

One consequence of the pervasive use of computers is that most documents originate in digital form. Widespread use of the Internet makes them readily available. Text mining – the process of analyzing unstructured natural-language text – is concerned with how to extract information from these documents. Developed from the authors’ highly successful Springer reference on text mining, Fundamentals of Predictive Text Mining is an introductory textbook and guide to this rapidly evolving field. ...

Recommender systems are one of the recent inventions to deal with the ever-growing information overload in relation to the selection of goods and services in a global economy. Collaborative Filtering (CF) is one of the most popular techniques in recommender systems. The CF recommends items to a target user based on the preferences of a set of similar users known as the neighbors, generated from a database made up of the preferences of past users. In the absence of these ratings, trust betw...

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using...

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing imp...