One of the challenges brought on by the digital revolution of the recent decades is the mechanism by which information carried by texts can be extracted in order to access its contents. The processing of named entities remains a very active area of research, which plays a central role in natural language processing technologies and their applications. Named entity recognition, a tool used in information extraction tasks, focuses on recognizing small pieces of information in order to extract information on a larger scale. The authors use written text and examples in French and English to present the necessary elements for the readers to familiarize themselves with the main concepts related to named entities and to discover the problems associated with them, as well as the methods available in practice for solving these issues.

One of the challenges brought on by the digital revolution of the recent decades is the mechanism by which information carried by texts can be extracted in order to access its contents. The processing of named entities remains a very active area of research, which plays a central role in natural language processing technologies and their applications. Named entity recognition, a tool used in information extraction tasks, focuses on recognizing small pieces of information in order to extract information on a larger scale. The authors use written text and examples in French and English to present the necessary elements for the readers to familiarize themselves with the main concepts related to named entities and to discover the problems associated with them, as well as the methods available in practice for solving these issues.

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This book presents a synthetic analysis about the characteristics of time expressions and named entities, and some proposed methods for leveraging these characteristics to recognize time expressions and named entities from unstructured text. For modeling these two kinds of entities, the authors propose a rule-based method that introduces an abstracted layer between the specific words and the rules, and two learning-based methods that define a new type of tagging scheme based on the constituents of the entities, different from conventional position-based tagging schemes that cause the problem of inconsistent tag assignment. The authors also find that the length-frequency of entities follows a family of power-law distributions. This finding opens a door, complementary to the rank-frequency of words, to understand our communicative system in terms of language use.

This open access volume constitutes the refereed proceedings of the 27th biennial conference of the German Society for Computational Linguistics and Language Technology, GSCL 2017, held in Berlin, Germany, in September 2017, which focused on language technologies for the digital age. The 16 full papers and 10 short papers included in the proceedings were carefully selected from 36 submissions. Topics covered include text processing of the German language, online media and online content, semantics and reasoning, sentiment analysis, and semantic web description languages.

Recent years have seen much new research on the interface between artificial intelligence and law, looking at issues such as automated legal reasoning. This collection of papers represents the state of the art in this fascinating and highly topical field.

In the past few decades, sources of inspiration in the multidisciplinary field of cognitive science have widened. In addition to ongoing vital work in cognitive and affective neuroscience, important new work is being conducted at the intersection of psychology and the biological sciences in general. This volume offers an overview of the cross-disciplinary integration of evolutionary and developmental approaches to cognition in light of these exciting new contributions from the life sciences. This research has explored many cognitive abilities in a wide range of organisms and developmental stages, and results have revealed the nature and origin of many instances of the cognitive life of organisms. Each section of this book deals with a key domain of cognition: spatial cognition; the relationships among attention, perception, and learning, representations of numbers and economic values; and social cognition. Contributors discuss each topic from the perspectives of psychology and neuroscience, brain theory and modeling, evolutionary theory, ecology, genetics, and developmental science.