Delve into the depths of Semantic Web technologies with a focus on RDFa, GRDDL, and POWDER through the guidance of Dr. Nicholas Gibbins. Learn about embedding Semantic Web data, republishing embedded data, and the usage of GRDDL for XML transformations.

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Explore the semantic properties of English verbs through various examples and classifications. Discover how verbs like hit, kiss, and touch share common properties, while verbs like make, create, imagine, and build belong to different classes based on their semantic relationships. Delve into the gra

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Explore how Vector-Space (Distributional) Lexical Semantics represent word meanings as points in a high-dimensional space. Learn about Semantic similarity, creating sample lexical vector spaces, and using word vectors to measure semantic relatedness. Discover how other contextual features and featur

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The lecture series at the University of Leuven explores Diachronic Prototype Semantics and its implications for Variational Linguistics. It delves into semasiological, conceptual onomasiological, and formal onomasiological variation in linguistic meaning, emphasizing the role of variability in the e

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Semantic Web technologies such as RDF, RDFS, OWL, and SPARQL form the basis of a web of data designed for machine understanding. Knowledge representation languages play a crucial role in AI, with Semantic Web languages like OWL leading the current generation. Contrasting database and knowledge base

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Using a Dynamic Semantic Parser approach, the research focuses on Sequential Question Answering (SQA) by structuring queries based on semantic parses of tables as single-table databases. The goal is to generate structured queries for questions by defining formal query languages and actions for trans

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Different types of lexical relations such as synonymy, antonyms, hyponymy, homophony, and homonymy play a crucial role in understanding the nuances of language. Synonyms have closely related meanings, antonyms have opposite meanings, while hyponymy and hypernymy show hierarchical relationships betwe

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Introduction to Chapter 5 Lecture 4.1 discusses the nature of word meaning, major problems of lexical semantics, and different approaches. It explains the concept of a word, prototypical words, lexical roots, lexemes, and word forms, highlighting the importance of the word as a lexeme in lexical sem

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The study explores how the functional load of phoneme contrasts affects the trajectory of phoneme system changes over time. Researchers examine phoneme mergers in nine languages, finding an inverse correlation between the number of minimal pairs and mergers. The model is refined to investigate diffe

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Investigating the impact of semantic knowledge and similarity on verbal short-term memory, this study delves into how imageability of words influences recall. Key findings highlight the influence of semantic relatedness and the imageability effect on memory retention, shedding light on the mechanism

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Polarity-Inducing Latent Semantic Analysis (PILSA) introduces a novel vector space model that distinguishes antonyms from synonyms. By encoding polarity information, synonyms cluster closely while antonyms are positioned at opposite ends of a unit sphere. Existing models struggle with finer distinct

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Utilizing enhanced lexical semantic models, this study presents approaches for sentence selection in question answering tasks, emphasizing tree-based techniques like tree edit-distance and quasi-synchronous grammar to match dependency trees. It discusses challenges in dependency tree matching, compu

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Language users rely on semantic principles like open choice and idiom to understand utterances, while syntactic analysis helps in grasping sentence structure. The interplay between lexical and phraseological features shapes language comprehension, showcasing tensions like in aspectual and idiomatic

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This research delves into multimodal semantic indexing methods for image retrieval, focusing on extending Latent Semantic Indexing (LSI) and probabilistic LSI to a multi-modal setting. Contributions include the refinement of graph models and partitioning algorithms to enhance image retrieval from tr

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Presentation by Fred van Blommestein on the EN16931-1 semantic data model of core elements in electronic invoicing, covering invoice processes, core invoice design, semantic model details, business rules, and invoicing principles. The model includes 160 elements in 33 groups, with mandatory elements

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Lexical semantics explores the relationships words have with each other and with our understanding of reality. It delves into reference and sense, naming theory, synonymy, and more. Reference focuses on how words relate to objects, while sense deals with relationships between lexical items. Naming t

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Aphasia often involves semantic breakdown, and Semantic Feature Analysis (SFA) is a foundational technique for various treatments addressing semantic impairments. This presentation explores the effectiveness of SFA in improving naming, generalization to spontaneous speech, and treatment goals beyond

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Explore the core concepts in Information Retrieval (IR) including lexical gaps like 'say' vs. 'said', semantic gaps, ranking models vs. retrieval methods, special data structures for efficient access, and algorithms for finding relevant documents. Understand the differences between IR and databases,

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The workshop on integrated reporting held on 1st December 2022 focused on enhancing proposals, planning JBRC setup, data dictionary governance, semantic integration, and more. The roadmap for 2023 includes topics like data granularity, governance, and continuous work on semantic and syntactic layers

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Explore the study on modeling semantic relations expressed by prepositions conducted by Vivek Srikumar and Dan Roth from the University of Illinois, Urbana-Champaign. The research delves into prepositions triggering relations, ontology of preposition relations, examples of preposition relations, pre

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Explore the intricate world of word sense disambiguation in computational lexical semantics, covering supervised and unsupervised techniques, lexical sample and all-words tasks, and various approaches such as knowledge-based and machine learning. Delve into the complexities of interpreting different

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This chapter delves into semantic issues in translation, aiming to assist students in annotating their translations from a semantic viewpoint. It emphasizes using semantic information to aid in translating data accurately while maintaining communicative effectiveness. The story discussed highlights

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Examples provided demonstrate how to access FrameNet data in Python using functions like frames(), frame(), lus(), and lu(). You can search for specific frames, get details of individual frames, lexical units, and roles in FrameNet. The content showcases how to retrieve information on medical frames

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Introduction to compiler principles with a focus on lexical analysis, parsing, abstract syntax, semantic analysis, activation records, translating into intermediate code, and other key aspects related to bindings in the Tiger compiler. The content covers topics like semantic analysis, name spaces, t

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Lexical relations play a crucial role in understanding the meanings of words in any language. They encompass relationships like entailment, paraphrase, and contradiction, shedding light on how lexemes are interconnected. Additionally, lexical fields and kinship systems offer further insights into ho

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Investigating the functional and lexical distribution of Indo-European verb classes, this research delves into the mi- and xa-conjugations in Proto-Indo-European, new discoveries in the preterit of the xa-conjugation, paradigms in Hittite, perfect and middle endings in Late Indo-European, and the ch

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An exploration of how semantic technologies facilitate data management, knowledge extraction, and understanding in the realm of big data. Topics covered include semantic graphs, content information extraction, and the impact of semantic models on enhancing data value and relationships. The importanc

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Explore the critical aspects of semantic interoperability in biobanking, highlighting the need for formal ontologies, comprehensive annotations, and model of meaning data. The (Generalized) Biomedical Retrieval Scenario underscores the importance of effective resource retrieval based on content-base

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