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Multi
ISBN: 9780198890676 Year: 2024 Publisher: Oxford Oxford University Press
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Dissertation
Year: 2020 Publisher: Leuven KU Leuven. Faculteit Letteren
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A dictionary is a rather old idea and most of the widely used dictionaries have been compiled decades, if not centuries ago. Needless to say, the dictionaries are being constantly revised and updated, moreover, nowadays one can speak of dictionary creation as of a dynamic and ongoing process, hardly any dictionaries are being built from ground up. The logic and principles behind semantic distribution in the more classical dictionaries (which are the still quite widespread and used) are well hidden behind the veil of time. However, it is interesting to reconstruct these principles for many reasons, among which: • opportunity to find a better semantic distribution for a dictionary • possibility of achieving an objective means for comparing dictionaries • curiosity Distributional semantics suggests that words with similar meaning occur in similar contexts. Creating a decent semantic model of this kind distantly resembles the process of compiling a dictionary: both require a lot of data, both require some sort of initial categorization and both are inherently aimed at vocabulary organization by the same criterion, namely, meaning. This is, however, where the similarities end. The fundamental difference lies in the very idea of both a distributional semantic model and a dictionary. The first one organizes vocabulary in order to explore semantic phenomena such as polysemy in large coprora, when a dictionary serves the sole purpose of organizing vocabulary with the scope of semantic exploration being relatively small. The concrete steps of the study are following: 1. Choose two dictionaries and a word, extract the dictionary entries for the word; 2. Choose a corpus, create concordances of the word and annotate with semantic models from both dictionaries; 3. Create the model 4. Analyze both models and tweak the parameters in order to at least approximate the dictionary entries. After performing these steps, no alignment of dictionary models to statistically produced models has been found. The author suggests three possible reasons to why this is the case, namely diachronic in-congruence of used dictionaries and corpus; dictionaries failing to depict real-world semantic distribution; limited ability of model to deal with polysemous phenomena.
Book
ISBN: 9783110687279 9783110687156 3110687275 3110687151 Year: 2022 Publisher: Berlin Boston
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Contemporary data analytics involves extracting insights from data and translating them into action. With its turn towards empirical methods and convergent data sources, cognitive linguistics is a fertile context for data analytics. There are key differences between data analytics and statistical analysis as typically conceived. Though the former requires the latter, it emphasizes the role of domain-specific knowledge. Statistical analysis also tends to be associated with preconceived hypotheses and controlled data. Data analytics, on the other hand, can help explore unstructured datasets and inspire emergent questions.This volume addresses two key aspects in data analytics for cognitive linguistic work. Firstly, it elaborates the bottom-up guiding role of data analytics in the research trajectory, and how it helps to formulate and refine questions. Secondly, it shows how data analytics can suggest concrete courses of research-based action, which is crucial for cognitive linguistics to be truly applied. The papers in this volume impart various data analytic methods and report empirical studies across different areas of research and application. They aim to benefit new and experienced researchers alike.
Electronic data processing --- Business intelligence --- Big data --- Data sets, Large --- Large data sets --- Data sets --- Business espionage --- Competitive intelligence --- Corporate intelligence --- Economic espionage --- Espionage, Business --- Espionage, Economic --- Espionage, Industrial --- Industrial espionage --- Intelligence, Business --- Intelligence, Corporate --- Business ethics --- Competition, Unfair --- Industrial management --- Confidential business information --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Automation
Digital
ISBN: 9783110687279 9783110687347 9783110687156 Year: 2022 Publisher: Berlin ;; Boston De Gruyter Mouton
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Digital
ISBN: 9783110733945 9783110733976 9783110738513 Year: 2021 Publisher: Berlin ;; Boston De Gruyter Mouton
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