The papers in this volume investigate the semantics of aspect from both a theoretical and a crosslinguistic point of view, in a wide range of languages from a number of different language families. The papers are all informed by the belief that a thorough exposure to the expression of aspect crosslinguistically is crucial for progress in understanding how the semantics of aspect works and what the semantic basis of aspectual distinctions is. The languages discussed include Russian, English, Dutch, Hebrew, Mandarin, Japanese and Kalaallisut. The issues discussed in this volume include the centrality of measuring and counting in an understanding of telicity; the importance of the singular/plural distinction in the study of aspect; the importance of homogeneity as a property of event types; the flexibility of lexical classes; and the interaction between expressions of aspect and the particular morphosyntactic structure of a language.

This book is focused on an emerging area, i.e. combination of IoT and semantic technologies, which should enable breaking the silos of local and/or domain-specific IoT deployments. Taking into account the way that IoT ecosystems are realized, several challenges can be identified. Among them of definite importance are (this list is, obviously, not exhaustive): (i) How to provide common representation and/or shared understanding of data that will enable analysis across (systematically growing) ecosystems? (ii) How to build ecosystems based on data flows? (iii) How to track data provenance? (iv) How to ensure/manage trust? (v) How to search for things/data within ecosystems? (vi) How to store data and assure its quality? Semantic technologies are often considered among the possible ways of addressing these (and other, related) questions. More precisely, in academic research and in industrial practice, semantic technologies materialize in the following contexts (this list is, also, not exhaustive, but indicates the breadth of scope of semantic technology usability): (i) representation of artefacts in IoT ecosystems and IoT networks, (ii) providing interoperability between heterogeneous IoT artefacts, (ii) representation of provenance information, enabling provenance tracking, trust establishment, and quality assessment, (iv) semantic search, enabling flexible access to data originating in different places across the ecosystem, (v) flexible storage of heterogeneous data. Finally, Semantic Web, Web of Things, and Linked Open Data are architectural paradigms, with which the aforementioned solutions are to be integrated, to provide production-ready deployments.

One of the few scholarly attempts to reconcile a generatively-based approach to the structure of the lexicon with the cognitive approach of Cognitive Grammar

This book discusses key issues of corpus linguistics like the definition of the corpus, primary features of a corpus, and utilization and limitations of corpora. It presents a unique classification scheme of language corpora to show how they can be studied from the perspective of genre, nature, text type, purpose, and application. A reference to parallel translation corpus is mandatory in the discussion of corpus generation, which the authors thoroughly address here, with a focus on Indian language corpora and English. Web-text corpus, a new development in corpus linguistics, is also discussed with elaborate reference to Indian web text corpora. The book also presents a short history of corpus generation and provides scenarios before and after the advent of computer-generated digital corpora. This book has several important features: it discusses many technical issues of the field in a lucid manner; contains extensive new diagrams and charts for easy comprehension; and presents discussions in simplified English to cater to the needs of non-native English readers. This is an important resource authored by academics who have many years of experience teaching and researching corpus linguistics. Its focus on Indian languages and on English corpora makes it applicable to students of graduate and postgraduate courses in applied linguistics, computational linguistics and language processing in South Asia and across countries where English is spoken as a first or second language.

Dictionary of Scientific Principles presents a unique and timeless collection of (almost) all known rules or laws commonly called principles, identified throughout the history of scientific development, their definition, and use. Exploring a broad range of disciplines, the book first lists more than 2,000 principles organized in a standard alphabetical order, then provides a list of subject headings for which related principles are identified. A staple addition to every library, the dictionary will also be of interest to scientists and general readers.

This book introduces the semantic aspects of natural language processing and its applications. Topics covered include: measuring word meaning similarity, multi-lingual querying, and parametric theory, named entity recognition, semantics, query language, and the nature of language. The book also emphasizes the portions of mathematics needed to under