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What is SEMANTIC FEATURE? What does SEMANTIC FEATURE mean? SEMANTIC FEATURE meaning & explanation
 
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What is SEMANTIC FEATURE? What does SEMANTIC FEATURE mean? SEMANTIC FEATURE meaning - SEMANTIC FEATURE definition - SEMANTIC FEATURE explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. SUBSCRIBE to our Google Earth flights channel - https://www.youtube.com/channel/UC6UuCPh7GrXznZi0Hz2YQnQ Semantic features represent the basic conceptual components of meaning for any lexical item. An individual semantic feature constitutes one component of a word's intension, which is the inherent sense or concept evoked. Linguistic meaning of a word is proposed to arise from contrasts and significant differences with other words. Semantic features enable linguistics to explain how words that share certain features may be members of the same semantic domain. Correspondingly, the contrast in meanings of words is explained by diverging semantic features. For example, father and son share the common components of 'human', 'kinship', 'male' and are thus part of a semantic domain of male family relations. They differ in terms of 'generation' and 'adulthood', which is what gives each its individual meaning. The analysis of semantic features is utilized in the field of linguistic semantics, more specifically the subfields of lexical semantics, and lexicology. One aim of these subfields is to explain the meaning of a word in terms of their relationships with other words. In order to accomplish this aim, one approach is to analyze the internal semantic structure of a word as composed of a number of distinct and minimal components of meaning. This approach is called componential analysis, also known as semantic decomposition. Semantic decomposition allows any given lexical item to be defined based on minimal elements of meaning, which are called semantic features. The term semantic feature is usually used interchangeably with the term semantic component. Additionally, semantic features/semantic components are also often referred to as semantic properties. The theory of componential analysis and semantic features is not the only approach to analyzing the semantic structure of words. An alternative direction of research that contrasts with componential analysis is prototype semantics.
Views: 1518 The Audiopedia
What is LEXICAL SEMANTICS? What does LEXICAL SEMANTICS mean? LEXICAL SEMANTICS meaning
 
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What is LEXICAL SEMANTICS? What does LEXICAL SEMANTICS mean? LEXICAL SEMANTICS meaning - LEXICAL SEMANTICS definition - LEXICAL SEMANTICS explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. Lexical semantics (also known as lexicosemantics), is a subfield of linguistic semantics. The units of analysis in lexical semantics are lexical units which include not only words but also sub-words or sub-units such as affixes and even compound words and phrases. Lexical units make up the catalogue of words in a language, the lexicon. Lexical semantics looks at how the meaning of the lexical units correlates with the structure of the language or syntax. This is referred to as syntax-semantic interface. The study of lexical semantics looks at: - the classification and decomposition of lexical items, - the differences and similarities in lexical semantic structure cross-linguistically, - the relationship of lexical meaning to sentence meaning and syntax. Lexical units, also referred to as syntactic atoms, can stand alone such as in the case of root words or parts of compound words or they necessarily attach to other units such as prefixes and suffixes do. The former are called free morphemes and the latter bound morphemes. They fall into a narrow range of meanings (semantic fields) and can combine with each other to generate new meanings. Lexical items contain information about category (lexical and syntactic), form and meaning. The semantics related to these categories then relate to each lexical item in the lexicon. Lexical items can also be semantically classified based on whether their meanings are derived from single lexical units or from their surrounding environment. Lexical items participate in regular patterns of association with each other. Some relations between lexical items include hyponymy, hypernymy, synonymy and antonymy, as well as homonymy.
Views: 6368 The Audiopedia
Introduction to Semantics
 
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Views: 45809 ASFCEngDept
What Are Semantic Networks?
 
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FINALLY DONE! :D
Views: 22970 Aidan Wood
Syntax Vs Semantics - Programming Languages
 
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This video is part of an online course, Programming Languages. Check out the course here: https://www.udacity.com/course/cs262.
Views: 56381 Udacity
Levels of Language for Discourse Analysis
 
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An overview of the various levels of linguistic analysis that discourse analysts use in their work. Includes discussion and examples of phonology, morphology, syntax, semantics, and pragmatics.
What is STRUCTURAL SEMANTICS? What does STRUCTURAL SEMANTICS mean?
 
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What is STRUCTURAL SEMANTICS? What does STRUCTURAL SEMANTICS mean? STRUCTURAL SEMANTICS meaning - STRUCTURAL SEMANTICS definition - STRUCTURAL SEMANTICS explanation. SUBSCRIBE to our Google Earth flights channel - https://www.youtube.com/channel/UC6UuCPh7GrXznZi0Hz2YQnQ Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. Logical positivism asserts that structural semantics is the study of relationships between the meanings of terms within a sentence, and how meaning can be composed from smaller elements. However, some critical theorists suggest that meaning is only divided into smaller structural units via its regulation in concrete social interactions; outside of these interactions, language may become meaningless. Structural semantics is that branch that marked the modern linguistics movement started by Ferdinand de Saussure at the break of the 20th century in his posthumous discourse titled "Cours De Linguistique Generale" (A Course in General Linguistics). He posits that language is a system of inter-related units and structures and that every unit of language is related to the others within the same system. His position later became the bedding ground for other theories such as componential analysis and relational predicates. Structuralism is a very efficient aspect of Semantics, as it explains the concordance in the meaning of certain words and utterances. The concept of sense relations as a means of semantic interpretation is an offshoot of this theory as well. Structuralism has revolutionized semantics to its present state, and it also aids to the correct understanding of other aspects of linguistics. The consequential fields of structuralism in linguistics are sense relations (both lexical and sentential) among others.
Views: 126 The Audiopedia
Text Analytics - Ep. 25 (Deep Learning SIMPLIFIED)
 
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Unstructured textual data is ubiquitous, but standard Natural Language Processing (NLP) techniques are often insufficient tools to properly analyze this data. Deep learning has the potential to improve these techniques and revolutionize the field of text analytics. Deep Learning TV on Facebook: https://www.facebook.com/DeepLearningTV/ Twitter: https://twitter.com/deeplearningtv Some of the key tools of NLP are lemmatization, named entity recognition, POS tagging, syntactic parsing, fact extraction, sentiment analysis, and machine translation. NLP tools typically model the probability that a language component (such as a word, phrase, or fact) will occur in a specific context. An example is the trigram model, which estimates the likelihood that three words will occur in a corpus. While these models can be useful, they have some limitations. Language is subjective, and the same words can convey completely different meanings. Sometimes even synonyms can differ in their precise connotation. NLP applications require manual curation, and this labor contributes to variable quality and consistency. Deep Learning can be used to overcome some of the limitations of NLP. Unlike traditional methods, Deep Learning does not use the components of natural language directly. Rather, a deep learning approach starts by intelligently mapping each language component to a vector. One particular way to vectorize a word is the “one-hot” representation. Each slot of the vector is a 0 or 1. However, one-hot vectors are extremely big. For example, the Google 1T corpus has a vocabulary with over 13 million words. One-hot vectors are often used alongside methods that support dimensionality reduction like the continuous bag of words model (CBOW). The CBOW model attempts to predict some word “w” by examining the set of words that surround it. A shallow neural net of three layers can be used for this task, with the input layer containing one-hot vectors of the surrounding words, and the output layer firing the prediction of the target word. The skip-gram model performs the reverse task by using the target to predict the surrounding words. In this case, the hidden layer will require fewer nodes since only the target node is used as input. Thus the activations of the hidden layer can be used as a substitute for the target word’s vector. Two popular tools: Word2Vec: https://code.google.com/archive/p/word2vec/ Glove: http://nlp.stanford.edu/projects/glove/ Word vectors can be used as inputs to a deep neural network in applications like syntactic parsing, machine translation, and sentiment analysis. Syntactic parsing can be performed with a recursive neural tensor network, or RNTN. An RNTN consists of a root node and two leaf nodes in a tree structure. Two words are placed into the net as input, with each leaf node receiving one word. The leaf nodes pass these to the root, which processes them and forms an intermediate parse. This process is repeated recursively until every word of the sentence has been input into the net. In practice, the recursion tends to be much more complicated since the RNTN will analyze all possible sub-parses, rather than just the next word in the sentence. As a result, the deep net would be able to analyze and score every possible syntactic parse. Recurrent nets are a powerful tool for machine translation. These nets work by reading in a sequence of inputs along with a time delay, and producing a sequence of outputs. With enough training, these nets can learn the inherent syntactic and semantic relationships of corpora spanning several human languages. As a result, they can properly map a sequence of words in one language to the proper sequence in another language. Richard Socher’s Ph.D. thesis included work on the sentiment analysis problem using an RNTN. He introduced the notion that sentiment, like syntax, is hierarchical in nature. This makes intuitive sense, since misplacing a single word can sometimes change the meaning of a sentence. Consider the following sentence, which has been adapted from his thesis: “He turned around a team otherwise known for overall bad temperament” In the above example, there are many words with negative sentiment, but the term “turned around” changes the entire sentiment of the sentence from negative to positive. A traditional sentiment analyzer would probably label the sentence as negative given the number of negative terms. However, a well-trained RNTN would be able to interpret the deep structure of the sentence and properly label it as positive. Credits Nickey Pickorita (YouTube art) - https://www.upwork.com/freelancers/~0147b8991909b20fca Isabel Descutner (Voice) - https://www.youtube.com/user/IsabelDescutner Dan Partynski (Copy Editing) - https://www.linkedin.com/in/danielpartynski Marek Scibior (Prezi creator, Illustrator) - http://brawuroweprezentacje.pl/ Jagannath Rajagopal (Creator, Producer and Director) - https://ca.linkedin.com/in/jagannathrajagopal
Views: 42644 DeepLearning.TV
ASL 4 REDO Semantic Structure
 
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Semantice Structure re-do
Views: 11 Elizabeth Luszczyk
SEM101 - Word Semantics
 
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How are lexemes and objects related? How can we define the relationships between the lexemes of a language? These questions are central to word semantics and defineits main branches reference and sense. This E-Lecture provides an overview of these main areas of word semantics.
English Semantics are Hard
 
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An introduction, with examples, to some of the problems that arise when we try to translate English sentences into logical statements.
Artificial Intelligence 40 Semantic Network (Week Slot and Filler Structure) in ai
 
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Artificial Intelligence 40 Semantic Network (Week Slot and Filler Structure) in ai semantic network are alternative to predicate logic in knowledge representation.
Views: 22442 Sanjay Pathak
Syntax vs Semantics (Philosophical Distinctions)
 
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An explication of the difference between syntax and semantics in philosophy of language, linguistics, and computer science. Information for this video gathered from The Stanford Encyclopedia of Philosophy, The Internet Encyclopedia of Philosophy, The Cambridge Dictionary of Philosophy, The Oxford Dictionary of Philosophy and more! Information for this video gathered from The Stanford Encyclopedia of Philosophy, The Internet Encyclopedia of Philosophy, The Cambridge Dictionary of Philosophy, The Oxford Dictionary of Philosophy and more! (#Syntax #Semantics)
Views: 51388 Carneades.org
An Introduction to Cohesion in Academic Writing
 
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In this video for the NUST MISiS Academic Writing Center, English Language Fellow John Kotnarowski provides a brief introduction to the concept of cohesion in academic writing. Defining cohesion as “the grammatical and lexical links within a text”, the video outlines the importance of cohesion in academic writing and offers examples of several useful cohesive devices.
Views: 56356 AWUC
Syntax (Part 1)
 
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A brief overview of lexical categories, phrase structure rules, and syntactic tree structures.
Views: 228034 Evan Ashworth
Robust Shallow Semantic Parsing of Text
 
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In this talk, I will focus on data-driven models for semantic structure prediction following frame semantics (Fillmore, 1982), a linguistic theory that describes predicate-argument relationships and emphasizes the abstraction of predicate meaning into semantic frames. Our method exploits rich information provided by linguists in the form of a lexicon (Fillmore and Baker, 2010), as well as a small amount of annotated data, to automatically ?nd disambiguated semantic frames of lexical predicates present in a sentence. A frame represents semantic knowledge and requires semantic roles that are fulfilled by arguments, in the form of words and phrases within the sentence. After disambiguating each predicate to the frame it evokes, our method finds the frame's arguments collectively via joint inference, making use of dual decomposition. Large amounts of annotated data for this task are unavailable; to this end, we model latent structure and apply semi-supervised learning, resulting in more robust models with broader coverage. Frame semantics is richer than the representation used in popular semantic role labeling systems (Kingsbury and Palmer, 2002) but less domain-specific than semantic parsers based on logical form (Ge and Mooney, 2005; Zettlemoyer and Collins, 2005); it represents a viable "middle ground" for data-driven semantic analysis of text. Compared to previous work, our method makes fewer independence assumptions and significantly outperforms past state of the art.
Views: 1026 Microsoft Research
Semantics - Wikipedia
 
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http://en.wikipedia.org/wiki/Semantics Semantics (from Ancient Greek: σημαντικός sēmantikós) is the study of meaning. It focuses on the relation between signifiers, like words, phrases, signs, and symbols, and what they stand for, their denotation. Linguistic semantics is the study of meaning that is used for understanding human expression through language. Other forms of semantics include the semantics of programming languages, formal logics, and semiotics. The word semantics itself denotes a range of ideas, from the popular to the highly technical. It is often used in ordinary language for denoting a problem of understanding that comes down to word selection or connotation. This problem of understanding has been the subject of many formal enquiries, over a long period of time, most notably in the field of formal semantics. In linguistics, it is the study of interpretation of signs or symbols used in agents or communities within particular circumstances and contexts. Within this view, sounds, facial expressions, body language, and proxemics have semantic (meaningful) content, and each comprises several branches of study. In written language, things like paragraph structure and punctuation bear semantic content; other forms of language bear other semantic content. The formal study of semantics intersects with many other fields of inquiry, including lexicology, syntax, pragmatics, etymology and others, although semantics is a well-defined field in its own right, often with synthetic properties. In philosophy of language, semantics and reference are closely connected. Further related fields include philology, communication, and semiotics. The formal study of semantics is therefore complex. Semantics contrasts with syntax, the study of the combinatorics of units of a language (without reference to their meaning), and pragmatics, the study of the relationships between the symbols of a language, their meaning, and the users of the language.
Views: 919 SemantiCure
SEM114 - Theories of Word Meaning
 
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In this E-Lecture Prof. Handke discusses several approaches towards the definition of word meaning, among them semantic fiels, componential analysis, meaning postulates and cognitive approaches, such as semantic networks and frames.
Learning to Extract Semantic Structure From Documents | Spotlight 3-1A
 
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Xiao Yang; Ersin Yumer; Paul Asente; Mike Kraley; Daniel Kifer; C. Lee Giles We present an end-to-end, multimodal, fully convolutional network for extracting semantic structures from document images. We consider document semantic structure extraction as a pixel-wise segmentation task, and propose a unified model that classifies pixels based not only on their visual appearance, as in the traditional page segmentation task, but also on the content of underlying text. Moreover, we propose an efficient synthetic document generation process that we use to generate pretraining data for our network. Once the network is trained on a large set of synthetic documents, we fine-tune the network on unlabeled real documents using a semi-supervised approach. We systematically study the optimum network architecture and show that both our multimodal approach and the synthetic data pretraining significantly boost the performance.
What's Semantics?
 
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This video provides an introduction to "Semantics" and "Semantic Features"
Views: 485 Alaa Ahmed Usama
definition syntax for adjectives following semantic feature analysis
 
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This video is a sample from my paid program for SLPs, Language Therapy Advance. In this video, I walk you through a way you can help your students define adjectives after doing semantic feature analysis. For more information on the Language Therapy Advance program, go here: https://karen-dudek-brannan.mykajabi.com/store/2VLBETyW
Views: 386 Karen Dudek-Brannan
Analysis of Semantic Function in Teaching Grammar - Two Case Studies
 
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1.Semantic Function •1.0 Meaning of Vocabulary : Meaning of content words实词 and meaning of functional words虚词 •1.1 Meaning of words interaction: between a content word and a content word; a functional word and a content word. •1.2 In addition to the Content words--Noun/pronoun, Verb and adjective etc , the functional words play an important role in Chinese grammar . They are Preposition, Particles, Adverbs, Conjunctive, Interjection and Onomatopoeia etc. •1.3 A Chinese teacher must pay his attention to and let students know the importance of word collocation in addition to the regular relation of words in a sentence. •1.4 A functional word can produces a grammatical pattern in Chinese . 2.0 •Chinese grammar is dealing with an isolated language which is very weak with morphology and realized by adding words or elements 成分 and arranging of word order 词序. •2.1 •A sentence often contains two kinds of elements A and B. Element A is conveying the basic message that are playing by Nouns, verbs and Adjectives. Element B is conveying the secondary level of messages that are most of time playing by Adverbs and other functional words. •2.2 The above mentioned natural fact in Chinese makes Chinese grammar must takes serious of study on functional words and word order. 4.0 •The "dominant" meaning显性语义 and the "recessive meaning"隐性语义. •4.1 •The "dominant" meaning is the meaning of vocabulary which is clear and easy to get from the word itself. Usually you can find a corresponding meaning from a foreign word. • 4.2 The "recessive meaning is a deeper semantic function. It usually does not come from the
Views: 1160 xiongyingzhanchi
Semantic Meaning
 
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Video shows what semantic means. Of or relating to semantics or the meanings of words.. Reflecting intended structure and meaning.. Petty or trivial; quibbling, niggling.. Semantic Meaning. How to pronounce, definition audio dictionary. How to say semantic. Powered by MaryTTS, Wiktionary
Views: 2285 SDictionary
Peter Groenewegen. Socio-Semantic Networks: Social Structure and Content in Networks (NetGloW'2014)
 
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Peter Groenewegen (VU University of Amsterdam, Netherlands) stated that social network analysis - based on interactions and relations - and sematic network analysis - that is focused on connections between words -have so far been developed as two separated spheres in social science research. Hence, both of them provide only a one-sided view of socio-semantic neworks. Thus, in his keynote speech he suggested to incorporate these two traditional theoretical views into a single framework, combining them with 3 distinct approaches: 1) comparing semantic structures of different network; 2) combining social structures of human agents and meaningful content; 3) studying the dynamics of socio-semantic networks and the role of popular concept vs popular actor. These new approaches enrich the current empirical research into networks by putting meaning on an equal footing to social interaction. International scientific conference ‘Networks in the Global World. Bridging Theory and Method: American, European, and Russian Studies’ took place in St. Petersburg State University on June 27-29, 2014. The primary goal of the ‘Networks in the Global World’ conference series is to bring together networks researchers from around the globe. It seeks to unite the efforts of various scientific disciplines in response to the key challenges faced by network studies today, and to exchange local research results – thus allowing an analysis of global processes. The idea of 2014-year event was to discuss the key current issues and problems of linking theoretical and methodological developments in network analysis. Find out more at http://www.ngw.spbu.ru/
Why Semantics, Not Syntax, creates NLU
 
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This is the first video in the series on NLU: why syntax alone is inadequate. We look at the underlying hypothesis and approach to syntactic structures and compare it to meaning-based systems. Contents 6:01 Fundamental Aim of Linguistic Analysis - 1957 8:17 Syntax recognises grammatical sentences AND ungrammatical sentences 9:32 Extending concept from grammatical to meaningful 14:19 Example 1: I want to go to the city 17:21 Example 2: John is eager/easy to please 22:08 Alternative way to retain correct language phrases 24:25 Why parsing is impossible, according to experts (1996) 25:23 Computational Linguistics and Google's work on parsers 28:16 What's up next time? A companion video provides some more detail on the use of meaning matching. https://youtu.be/jp9enFFy5JU
Views: 97 Pat Inc
Semantic Analysis for development
 
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https://innoradiant.com/ We help our customers to take to the right decisions in the product development life cycle by identifying user attitudes on social networks. Our help is not in terms of consultancy, but is based on the delivery of VoU, a platform which allows product teams to be completely autonomous in the discovery of “killer features” of the new product. VoU is based on a big data compliant architecture (we do not do much buzz about it, but yes we are dealing with big data!) where several world class Artificial Intelligence libraries have been injected, notably in the domain of Natural Language Processing.
Views: 191 INNORADIANT
A formal semantic analysis of iconic gesture -- A. Lascarides
 
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A. Lascarides (University of Edinburgh)
Mod-04 Lec-12 Semantic Analysis with Attribute Grammars Part 1
 
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Principles of Compiler Design by Prof. Y.N. Srikanth,Department of Computer Science and Engineering,IISc Bangalore.For more details on NPTEL visit http://nptel.ac.in
Views: 11457 nptelhrd
Semantics #2 - Language System and Meaning of Words
 
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Music - YouTube AudioLibrary - Otis McDonald - "Stay"
Views: 1976 Ling Troduction
SEM120 - Sentence Semantics
 
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This introductory E-Lecture about sentence semantics introduces the main principles and the central mechanisms involved in propositional and predicate logic. Additionally, it shows how entailment relations can be defined and applied and how the principles of quantification can be combined with predicates.
Compiler Design lecture: Semantic Analysis, various Phases of compiler | 15
 
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Compiler Design lecture | Semantic Analysis | various Phases of compiler Lexical Analysis Syntax Analysis Semantic Analysis Intermediate Code Generation Code Optimization Target Machine Code Generation The semantic analyzer uses the syntax tree and the information in the symbol table to check the source program for semantic consistency with the language definition. It also gathers type information and saves it in either the syntax tree or the symbol table, for subsequent use during intermediate-code generation. An important part of semantic analysis is type checking, where the compiler checks that each operator has matching operands. For example, many program- ming language definitions require an array index to be an integer; the compiler must report an error if a floating-point number is used to index an array. The language specification may permit some type conversions called coer- cions. For example, a binary arithmetic operator may be applied to either a pair of integers or to a pair of floating-point numbers. If the operator is applied to a floating-point number and an integer, the compiler may convert or coerce the integer into a floating-point number.
Views: 21060 Gate Instructors
Knowledge Representation | semantic networks | Frames | artificial intelligence | Hindi | #19
 
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Follow us on : Facebook : https://www.facebook.com/wellacademy/ Instagram : https://instagram.com/well_academy Twitter : https://twitter.com/well_academy
Views: 164247 Well Academy
Semantic Analysis Phase : Introduction
 
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Semantic Analysis Phase : This is the 3rd phase of Compiler which gives you basically type checking facility in the form of Semantic Errors. Attribute Grammars: Also called as SDT (Semantic Directed Translation) which is a Representational formalism in which CFG production is attached with Semantic Actions. IN the upcoming session we will continue with few more problems.
Views: 15927 Go GATE IIT
Semantic Drift
 
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Learn how words developed slightly different meanings in English and its cousin language, Scots. Is Scots a dialect of English, or a language in its own right? I don't know! You figure it out!!
Views: 457 Jake Goldwasser
Semantics of Words and Sentences (ENG)
 
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Subject:English Paper: Introduction to Linguistics & Phonetics
Views: 4885 Vidya-mitra
Machine Learning for Semantic Segmentation - Basics of Modern Image Analysis
 
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This was a lecture in the "Basics of Modern Image Analysis" class by Prof. Fred Hamprecht. It took place at the HCI / Heidelberg University during the summer term of 2016. Machine Learning for Semantic Segmentation: * Features: linear and nonlinear * Overview of Classifiers 00:30:45 * Training Random Forests 00:50:50 * Cascaded Classifiers (Auto-Context) 01:02:50 * Hough Forests for Object Detection 01:10:15
Views: 1664 UniHeidelberg
Structural Ambiguity - Syntax Video #3
 
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Sometimes a single sentence has more than one meaning. A group of linguists explore prepositional phrase attachment ambiguity. Twitter @lingvids LingVids is created by Caroline Andrews, Leland Paul Kusmer, Gretchen McCulloch, and Joshua Levy. For a more detailed introduction to syntax, see the How to Draw Syntax Trees series starting at: http://allthingslinguistic.com/post/100357884082/how-to-draw-syntax-trees-part-1-so-you-asked Music is composed by Kevin MacLeod and used under a Creative Commons License. The track can be found here: https://www.youtube.com/watch?v=V8CAH0vsoPM LingVids is no longer being updated, but one of its creators is now cohosting a linguistics podcast called Lingthusiasm. You can listen to it on youtube, iTunes, soundcloud, or wherever else you get your podcasts.
Views: 29037 Ling Vids
FROM TWEET TO GRAPH: SOCIAL NETWORK ANALYSIS FOR SEMANTIC INFORMATION EXTRACTION
 
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Views: 79 content writter
Semantics and Sarcasm in Online Dialogue
 
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Speaker: Marilyn Walker Position title: Professor, Computer Science, UC-Santa Cruz Talk title: Semantics and Sarcasm in Online Dialogue Talk abstract: Online forums provide a fascinating source of data for research on the structure of dialogue. Unlike traditional media corpora, online conversation is highly social and subjective and its interpretation and analysis are strongly dependent on context. Phenomena such as sarcasm and rhetorical questions are highly frequent. In this talk I will first describe the IAC corpus (Internet Argument Corpus) that we have made publicly available. I will then discuss our research on several tasks related to dialogue structure and the meaning of utterances, such as recognizing sarcasm, identifying the linguistic properties of factual vs. emotional arguments, and mining the facets of arguments on different topics. About the Forum: The IBM Research Distinguished Speaker Series brings together IBM and external researchers and practitioners to share their expertise in all aspects of analytics. This global bi-weekly event features a wide range of scientific topics which appeal to a broad audience interested in the latest technology for analytics, and how analytics is being used to gain insights from data.
Views: 378 IBM Research
NLP at Scale for Maintenance and Supply Chain Management — Ryan Chandler, Caterpillar
 
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How do you read 100,000 documents? The connection between the words we use and things and ideas that they represent can be represented as a structure. Using Neo4j this linguistic and semantic structure is developed to facilitate the large-scale analysis of text for meaning representation and automatic reading at scale. Learn how natural language processing can be implemented within Neo4j at scale to reveal actionable insights.  Also, see how these structures are visualized in virtual reality. Speaker: Ryan Chandler Location: GraphConnect NYC 2017
Views: 1210 Neo4j
What is SEMIOTICS? What does SEMIOTICS mean? SEMIOTICS meaning, definition & explanation
 
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Do you travel a lot? Get yourself a mobile application to find THE CHEAPEST airline tickets deals available on the market: ANDROID - http://android.theaudiopedia.com - IPHONE - http://iphone.theaudiopedia.com or get BEST HOTEL DEALS worldwide: ANDROID - htttp://androidhotels.theaudiopedia.com - IPHONE - htttp://iphonehotels.theaudiopedia.com What is SEMIOTICS? What does SEMIOTICS mean? SEMIOTICS meaning - SEMIOTICS definition - SEMIOTICS explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. Semiotics (also called semiotic studies; not to be confused with the Saussurean tradition called semiology which is a part of semiotics) is the study of meaning-making, the study of sign processes and meaningful communication. This includes the study of signs and sign processes (semiosis), indication, designation, likeness, analogy, allegories, metonyms, metaphor, symbolism, signification, and communication. Semiotics is closely related to the field of linguistics, which, for its part, studies the structure and meaning of language more specifically. The semiotic tradition explores the study of signs and symbols as a significant part of communications. As different from linguistics, however, semiotics also studies non-linguistic sign systems. Semiotics is frequently seen as having important anthropological dimensions; for example, the late Italian semiotician and novelist Umberto Eco proposed that every cultural phenomenon may be studied as communication. Some semioticians focus on the logical dimensions of the science, however. They examine areas belonging also to the life sciences—such as how organisms make predictions about, and adapt to, their semiotic niche in the world (see semiosis). In general, semiotic theories take signs or sign systems as their object of study: the communication of information in living organisms is covered in biosemiotics (including zoosemiotics). Semioticians classify signs or sign systems in relation to the way they are transmitted (see modality). This process of carrying meaning depends on the use of codes that may be the individual sounds or letters that humans use to form words, the body movements they make to show attitude or emotion, or even something as general as the clothes they wear. To coin a word to refer to a thing (see lexical words), the community must agree on a simple meaning (a denotative meaning) within their language, but that word can transmit that meaning only within the language's grammatical structures and codes (see syntax and semantics). Codes also represent the values of the culture, and are able to add new shades of connotation to every aspect of life. To explain the relationship between semiotics and communication studies, communication is defined as the process of transferring data and-or meaning from a source to a receiver. Hence, communication theorists construct models based on codes, media, and contexts to explain the biology, psychology, and mechanics involved. Both disciplines recognize that the technical process cannot be separated from the fact that the receiver must decode the data, i.e., be able to distinguish the data as salient, and make meaning out of it. This implies that there is a necessary overlap between semiotics and communication. Indeed, many of the concepts are shared, although in each field the emphasis is different. In Messages and Meanings: An Introduction to Semiotics, Marcel Danesi (1994) suggested that semioticians' priorities were to study signification first, and communication second. A more extreme view is offered by Jean-Jacques Nattiez (1987; trans. 1990: 16), who, as a musicologist, considered the theoretical study of communication irrelevant to his application of semiotics. Semiotics differs from linguistics in that it generalizes the definition of a sign to encompass signs in any medium or sensory modality. Thus it broadens the range of sign systems and sign relations, and extends the definition of language in what amounts to its widest analogical or metaphorical sense. Peirce's definition of the term "semiotic" as the study of necessary features of signs also has the effect of distinguishing the discipline from linguistics as the study of contingent features that the world's languages happen to have acquired in the course of their evolutions. From a subjective standpoint, perhaps more difficult is the distinction between semiotics and the philosophy of language. In a sense, the difference lies between separate traditions rather than subjects. Different authors have called themselves "philosopher of language" or "semiotician". This difference does not match the separation between analytic and continental philosophy. On a closer look, there may be found some differences regarding subjects. Philosophy of language pays more attention to natural languages or to languages in general, while semiotics is deeply concerned with non-linguistic signification.
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HermeneutiX – Getting Started
 
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HermeneutiX is a tool for analysing the syntactic and semantic structure of texts as part of an exegesis (e.g. biblical exegesis). It is part of the SciToS (scientific tool set) project and freely available on GitHub: https://github.com/scientific-tool-set/scitos/releases ---------------- This video aims at providing a basic tutorial on how to use HermeneutiX and to present an overview of the main features. Contents: 00:00 Introduction 00:48 Download HermeneutiX (SciToS) from GitHub 01:03 Start HermeneutiX (SciToS) from extracted .zip 03:25 Creating a HermeneutiX project & pre-format text 04:48 Performing the syntactic structure analysis 07:22 Performing the semantic structure analysis 08:59 Adding comments and other minor features 12:04 Configuration options (Look & Feel) 13:24 Configuration options (Colors and Fonts in exported SVG files) 13:47 Configuration options (Semantic relations/roles) 14:08 Configuration options (Input Languages, i.e. syntactic functions) 16:27 Exporting to SVG 17:12 How to share configurations ---------------- Additional points: 1. For creating semantic relations over multiple elements (propositions/relations), just tick all of their check boxes and right-click on any one of them to create the relation. Actually it doesn’t matter whether the one you click on has been checked as well. 2. For changing the origin text’s font after starting the analysis, go to „Edit“ – „Edit Project Info“, which includes the origin text font as well as the other meta data (title, author, comment). ---------------- I want to apologize for a few things here: The quality of both video and sound due to my non-professional equipment and lack of experience in creating these screencasts. Since I'm only the (main) developer for HermeneutiX (since 2009) but not the head behind the idea, I've no background in theological studies and are therefore blissfully ignorant to the intricacies of the (biblical) exegesis. --------------- If you have any suggestions how to improve SciToS/HermeneutiX, you're welcome to contact me. Cheers, Carsten
Views: 131 SciToS