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Handbook of Natural Language Processing
The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.New to the Second EditionGreater
Text Mining
Data mining is a mature technology. The prediction problem, looking for predictive patterns in data, has been widely studied. Strong me- ods are available to the practitioner. These methods process structured numerical information, where uniform measurements are taken over a sample of data. Text is often described as unstructured information. So, it would seem, text and numerical data are different, requiring different methods. Or are they? In our view, a prediction problem can be solved by the same methods, whether the data are structured - merical measurements or unstructured text. Text and documents can be transformed into measured values, such as the presence or absence of words, and the same methods that have proven successful for pred- tive data mining can be applied to text. Yet, there are key differences. Evaluation techniques must be adapted to the chronological order of publication and to alternative measures of error. Because the data are documents, more specialized analytical methods may be preferred for text. Moreover, the methods must be modi?ed to accommodate very high dimensions: tens of thousands of words and documents. Still, the central themes are similar.
Persian Computational Linguistics and NLP
In this series, Iranian languages and linguistics take centre stage. Each volume is dedicated to a key topic and brings together leading experts from around the globe.
Predictive Data Mining
This book is the first technical guide to provide a complete, generalized road map for developing data-mining applications, together with advice on performing these large-scale, open-ended analyses for real-world data warehouses.
Multiword expressions in lexical resources
This volume contains chapters that paint the current landscape of the multiword expressions (MWE) representation in lexical resources, in view of their robust identification and computational processing. Both large-size general lexica and smaller MWE-centred ones are included, with special focus on the representation decisions and mechanisms that facilitate their usage in Natural Language Processing tasks. The presentations go beyond the morpho-syntactic description of MWEs, into their semantics. One challenge in representing MWEs in lexical resources is ensuring that the variability along with extra features required by the different types of MWEs can be captured efficiently. In this respect, recommendations for representing MWEs in mono- and multilingual computational lexicons have been proposed; these focus mainly on the syntactic and semantic properties of support verbs and noun compounds and their proper encoding thereof.
Support-verb constructions in the corpora of Greek
This volume brings together corpora that span more than 3,000 years of the history of the Greek language, from Ittzés' chapter on the proto-language to Giouli's chapter on the modern language. The authors take wider or narrower approaches with regard to the form and function of the type of construction that they include in the group of support-verb constructions: while all would agree that English to take initiative is a support-verb construction, opinions differ on English to take wing. The chapters reflect a fascinating diversity of approaches to support-verb constructions, including Natural Language Processing, Comparative Philology, New Testament Exegesis, Coptology, and General Linguistics. The volume is structured along the three interfaces that support-verb constructions sit on, the syntax-lexicon, the syntax-semantics, and the syntax-pragmatics interfaces. We finish with four concrete avenues for further research. Faced with the diversity of approaches and the magnitude of disagreements arising from them when working with as internally diverse a group of constructions as support-verb constructions, we strive for in varietate unitas.
Artificial Intelligence in Economics and Managment
In the past decades several researchers have developed statistical models for the prediction of corporate bankruptcy, e. g. Altman (1968) and Bilderbeek (1983). A model for predicting corporate bankruptcy aims to describe the relation between bankruptcy and a number of explanatory financial ratios. These ratios can be calculated from the information contained in a company's annual report. The is to obtain a method for timely prediction of bankruptcy, a so ultimate purpose called "early warning" system. More recently, this subject has attracted the attention of researchers in the area of machine learning, e. g. Shaw and Gentry (1990), Fletcher and Goss (1993), and Tam and Kiang (1992). This r...
Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision
Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision provides an overview of general deep learning methodology and its applications of natural language processing (NLP), speech, and computer vision tasks. It simplifies and presents the concepts of deep learning in a comprehensive manner, with suitable, full-fledged examples of deep learning models, with an aim to bridge the gap between the theoretical and the applications using case studies with code, experiments, and supporting analysis. Features: Covers latest developments in deep learning techniques as applied to audio analysis, computer vision, and natural language processing. Introduces contemporary applications of deep learning techniques as applied to audio, textual, and visual processing. Discovers deep learning frameworks and libraries for NLP, speech, and computer vision in Python. Gives insights into using the tools and libraries in Python for real-world applications. Provides easily accessible tutorials and real-world case studies with code to provide hands-on experience. This book is aimed at researchers and graduate students in computer engineering, image, speech, and text processing.
Discovery Science
This book constitutes the refereed proceedings of the 9th International Conference on Discovery Science, DS 2006, held in Barcelona, Spain in October 2006, co-located with the 17th International Conference on Algorithmic Learning Theory, ALT 2006. The 23 revised long papers and the 18 revised regular papers presented together with five invited papers were carefully reviewed and selected from 87 submissions.
Case-Based Reasoning Research and Development
This book constitutes the refereed proceedings of the First International Conference on Case-Based Reasoning, ICCBR-95, held in Sesimbra, Portugal, in October 1995. The 52 revised papers included are classified as scientific papers , application papers , and posters . All current aspects of research and development aiming at industrial applications in CBR are addressed. Among the topical sections are case and knowledge representation, case retrieval, nearest neighbour methods, case adaption and learning, cognitive modelling, integrated reasoning methods, and application-oriented methods: planning, decision making, diagnosis, interpretation, design, etc.
