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Statistical semantics Meaning
Statistical semantics Meaning
Published: 2015/05/02
Channel: ADictionary
What does statistical semantics mean?
What does statistical semantics mean?
Published: 2015/01/07
Channel: What Does That Mean?
Deep Natural Language Semantics - Raymond Mooney
Deep Natural Language Semantics - Raymond Mooney
Published: 2014/11/26
Channel: Allen Institute for Artificial Intelligence (AI2)
Knowledge Representation | semantic networks | Frames | artificial intelligence | Hindi | #19
Knowledge Representation | semantic networks | Frames | artificial intelligence | Hindi | #19
Published: 2017/04/15
Channel: Well Academy
Semantic Interaction for Sense-making: Alex Endert at TEDxVirginiaTech
Semantic Interaction for Sense-making: Alex Endert at TEDxVirginiaTech
Published: 2012/12/05
Channel: TEDx Talks
Noam Chomsky 2014  Statistical Natural Language Processing
Noam Chomsky 2014 Statistical Natural Language Processing
Published: 2015/07/13
Channel: Ricardo Ruiz
Uncovering Semantic Similarities between Query Terms
Uncovering Semantic Similarities between Query Terms
Published: 2016/09/06
Channel: Microsoft Research
NIPS 2012 Tutorial (Getoor) Representation, Inference and Learning in Structured Statistical Models
NIPS 2012 Tutorial (Getoor) Representation, Inference and Learning in Structured Statistical Models
Published: 2013/02/20
Channel: NIPS
Semantics
Semantics
Published: 2012/03/29
Channel: Hard Left Productions
NSF Interdisciplinary Workshop on Statistical NLP and Software Engineering - Session 6
NSF Interdisciplinary Workshop on Statistical NLP and Software Engineering - Session 6
Published: 2016/06/22
Channel: Microsoft Research
Markov Logic for Statistical Relational Learning
Markov Logic for Statistical Relational Learning
Published: 2016/08/12
Channel: Microsoft Research
Tutorial - Natural Language Processing for Music Information Retrieval. Lexical Semantics
Tutorial - Natural Language Processing for Music Information Retrieval. Lexical Semantics
Published: 2017/03/02
Channel: Universitat Pompeu Fabra - Barcelona
NIPS 2011 Learning Semantics Workshop: Learning Dependency-Based Compositional Semantics
NIPS 2011 Learning Semantics Workshop: Learning Dependency-Based Compositional Semantics
Published: 2012/02/03
Channel: GoogleTechTalks
the meaning of semantics
the meaning of semantics
Published: 2010/05/02
Channel: David H. Mason
Pedro Domingos - Unifying Logical and Statistical AI
Pedro Domingos - Unifying Logical and Statistical AI
Published: 2009/09/17
Channel: The University of Edinburgh
NIPS 2011 Learning Semantics Workshop: Towards More Human-like Machine Learning of Word Meanings
NIPS 2011 Learning Semantics Workshop: Towards More Human-like Machine Learning of Word Meanings
Published: 2012/02/04
Channel: GoogleTechTalks
2 - 1 - Semantics & Factorization - Probabilistic Graphical Models - Professor Daphne Koller
2 - 1 - Semantics & Factorization - Probabilistic Graphical Models - Professor Daphne Koller
Published: 2012/03/27
Channel: OpenCourseOnline
Video Classification using Semantic Concept Co-occurrences
Video Classification using Semantic Concept Co-occurrences
Published: 2014/08/18
Channel: UCF CRCV
Video Demo - semSMT: Source Code Migration with Semantic Statistical Machine Translation
Video Demo - semSMT: Source Code Migration with Semantic Statistical Machine Translation
Published: 2013/11/22
Channel: Tuan Anh Nguyen
Feedforward Semantic Segmentation with Zoom-out Features
Feedforward Semantic Segmentation with Zoom-out Features
Published: 2016/06/27
Channel: Microsoft Research
文献紹介:Improve Statistical Machine Translation with Context-Sensitive Bilingual Semantic Embedding...
文献紹介:Improve Statistical Machine Translation with Context-Sensitive Bilingual Semantic Embedding...
Published: 2015/06/03
Channel: 長岡技術科学大学 自然言語処理研究室
Understand Short Texts by Harvesting and Analyzing Semantic Knowledge
Understand Short Texts by Harvesting and Analyzing Semantic Knowledge
Published: 2017/06/19
Channel: jpinfotechprojects
Coding Statistical Functions in C++ (part 1 Mean)
Coding Statistical Functions in C++ (part 1 Mean)
Published: 2015/03/28
Channel: Guadalupe Bernal
Semantic Text Processing: Example Application
Semantic Text Processing: Example Application
Published: 2015/01/16
Channel: cognitumeu
Perceptual Image/Video Segmentation and Semantic Classification
Perceptual Image/Video Segmentation and Semantic Classification
Published: 2012/08/22
Channel: GoogleTalksArchive
Probe Informatics - Semantic Machine Learning & Predictive Analytics
Probe Informatics - Semantic Machine Learning & Predictive Analytics
Published: 2014/01/29
Channel: Probe Informatics
Semantic Awareness for Automatic Image Interpretation
Semantic Awareness for Automatic Image Interpretation
Published: 2016/07/28
Channel: Microsoft Research
Dr. Adam Lopez: A Formal Model of Semantics-Preserving Translation
Dr. Adam Lopez: A Formal Model of Semantics-Preserving Translation
Published: 2014/10/27
Channel: Ting-Hao Huang
Prof. Ram Frost - Statistical Learning and Second Language Acquisition
Prof. Ram Frost - Statistical Learning and Second Language Acquisition
Published: 2016/06/19
Channel: Department of Psychology HUJI
Fernando Pereira Low-Pass Semantics Technion Computer Engineering Conference Lecture
Fernando Pereira Low-Pass Semantics Technion Computer Engineering Conference Lecture
Published: 2013/06/02
Channel: Technion
Natural Language Processing (NLP) Tutorial - An introduction to NLP and Semantic Fingerprints
Natural Language Processing (NLP) Tutorial - An introduction to NLP and Semantic Fingerprints
Published: 2017/08/10
Channel: Fullstack Academy
Tutorial - Natural Language Processing.  Semantic Enrichment of Musical Texts
Tutorial - Natural Language Processing. Semantic Enrichment of Musical Texts
Published: 2017/03/02
Channel: Universitat Pompeu Fabra - Barcelona
Eradication, elimination and control: public health and policy implications – semantics or reality?
Eradication, elimination and control: public health and policy implications – semantics or reality?
Published: 2015/10/02
Channel: rstmh
TSD conference 2006 - Presentation of James Pustejovsky
TSD conference 2006 - Presentation of James Pustejovsky
Published: 2012/09/17
Channel: NLPassist
semantic text classification thatneedle.com
semantic text classification thatneedle.com
Published: 2016/01/11
Channel: thatneedle semantic search
NIPS 2011 Learning Semantics Workshop: Learning Semantics of Movement
NIPS 2011 Learning Semantics Workshop: Learning Semantics of Movement
Published: 2012/02/04
Channel: GoogleTechTalks
Chester Curme: Quantifying the semantics of search behavior before stock market moves
Chester Curme: Quantifying the semantics of search behavior before stock market moves
Published: 2015/07/03
Channel: Data Science Lab
Tutorial - Natural Language Processing for Music Information Retrieval. Construction of Music KBs
Tutorial - Natural Language Processing for Music Information Retrieval. Construction of Music KBs
Published: 2017/03/02
Channel: Universitat Pompeu Fabra - Barcelona
NIPS 2011 Learning Semantics Workshop: From Machine Learning to Machine Reasoning
NIPS 2011 Learning Semantics Workshop: From Machine Learning to Machine Reasoning
Published: 2012/02/04
Channel: GoogleTechTalks
Delroy proposal defense
Delroy proposal defense
Published: 2013/12/21
Channel: Knoesis Center
CppCon 2015: Matt P. Dziubinski “Rcpp: Seamless R and C++ Integration"
CppCon 2015: Matt P. Dziubinski “Rcpp: Seamless R and C++ Integration"
Published: 2015/10/14
Channel: CppCon
Semantic fingerprinting: Democratising natural language processing
Semantic fingerprinting: Democratising natural language processing
Published: 2015/08/27
Channel: TNG Technology Consulting GmbH
Textual entailment as a framework for applied semantics
Textual entailment as a framework for applied semantics
Published: 2016/09/07
Channel: Microsoft Research
Motion Graphs++: a Compact Generative Model for Semantic Motion Analysis and Synthesis
Motion Graphs++: a Compact Generative Model for Semantic Motion Analysis and Synthesis
Published: 2012/09/22
Channel: Jianyuan Min
Probabilistic (Logic) Programming: Concepts and Applications - Luc De Raedt
Probabilistic (Logic) Programming: Concepts and Applications - Luc De Raedt
Published: 2016/02/22
Channel: Electrical Engineering and Computer Science - OSU
Semantic Segmentation of Textured Meshes
Semantic Segmentation of Textured Meshes
Published: 2015/11/25
Channel: Mohammad Rouhani
k Nearest Neighbor Classification over Semantically Secure Encrypted Relational Data
k Nearest Neighbor Classification over Semantically Secure Encrypted Relational Data
Published: 2015/09/24
Channel: manju nath
Watch semantics
Watch semantics
Published: 2015/06/02
Channel: E SMART CLASS
Probability Theory and Probability Semantics Toronto Studies in Philosophy Pdf Book
Probability Theory and Probability Semantics Toronto Studies in Philosophy Pdf Book
Published: 2016/06/13
Channel: J. Alfarian
Mike Lewis (UW): Wide-Coverage Semantic Parsing
Mike Lewis (UW): Wide-Coverage Semantic Parsing
Published: 2016/04/26
Channel: UW AI Research
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WIKIPEDIA ARTICLE

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In linguistics, statistical semantics applies the methods of statistics to the problem of determining the meaning of words or phrases, ideally through unsupervised learning, to a degree of precision at least sufficient for the purpose of information retrieval.

History[edit]

The term statistical semantics was first used by Warren Weaver in his well-known paper on machine translation.[1] He argued that word sense disambiguation for machine translation should be based on the co-occurrence frequency of the context words near a given target word. The underlying assumption that "a word is characterized by the company it keeps" was advocated by J.R. Firth.[2] This assumption is known in linguistics as the distributional hypothesis.[3] Emile Delavenay defined statistical semantics as the "statistical study of meanings of words and their frequency and order of recurrence".[4] "Furnas et al. 1983" is frequently cited as a foundational contribution to statistical semantics.[5] An early success in the field was latent semantic analysis.

Applications[edit]

Research in statistical semantics has resulted in a wide variety of algorithms that use the distributional hypothesis to discover many aspects of semantics, by applying statistical techniques to large corpora:

Related fields[edit]

Statistical semantics focuses on the meanings of common words and the relations between common words, unlike text mining, which tends to focus on whole documents, document collections, or named entities (names of people, places, and organizations). Statistical semantics is a subfield of computational semantics, which is in turn a subfield of computational linguistics and natural language processing.

Many of the applications of statistical semantics (listed above) can also be addressed by lexicon-based algorithms, instead of the corpus-based algorithms of statistical semantics. One advantage of corpus-based algorithms is that they are typically not as labour-intensive as lexicon-based algorithms. Another advantage is that they are usually easier to adapt to new languages than lexicon-based algorithms. However, the best performance on an application is often achieved by combining the two approaches.[21]

See also[edit]

References[edit]

Sources[edit]

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