Towards a Semantic Classification of Possible Human-to-Environment Interactions in IoT

Semantic Classification of Scientific Sentence Pair Using Recurrent Neural Network

2020 7th International Conference on Electrical Engineering, Computer Sciences and Informatics (EECSI) ◽

10.23919/eecsi50503.2020.9251897 ◽

2020 ◽

Author(s):

Agung Besti ◽

Ridwan Ilyas ◽

Fatan Kasyidi ◽

Esmeralda Contessa Djamal

Keyword(s):

Neural Network ◽

Recurrent Neural Network ◽

Sentence Pair ◽

Semantic Classification ◽

Scientific Sentence

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Lexical Changes in the Korean Residential Culture Corpus: Focused on Semantic Classification of Nouns.

Language and Information ◽

10.29403/li.24.3.2 ◽

2020 ◽

Vol 24 (3) ◽

pp. 27-45

Author(s):

Yoonjung Oh

Keyword(s):

Semantic Classification ◽

Residential Culture

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Semantic Classification of ‘dangha-da’ Passive Verbs in Korean

HAN-GEUL ◽

10.22557/hg.2007.12.278.31 ◽

2007 ◽

Vol 278 ◽

pp. 31

Author(s):

Jae Won Yu

Keyword(s):

Semantic Classification ◽

Passive Verbs

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Semantic classification of qualitative conditionals and calculating closures of nonmonotonic inference relations

International Journal of Approximate Reasoning ◽

10.1016/j.ijar.2020.12.020 ◽

2021 ◽

Vol 130 ◽

pp. 297-313

Author(s):

Steven Kutsch ◽

Christoph Beierle

Keyword(s):

Semantic Classification ◽

Nonmonotonic Inference

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Effective semantic classification of consumer events for automatic content management

Proceedings of the first SIGMM workshop on Social media - WSM '09 ◽

10.1145/1631144.1631153 ◽

2009 ◽

Cited By ~ 1

Author(s):

Wei Jiang ◽

Alexander C. Loui

Keyword(s):

Content Management ◽

Semantic Classification

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Semantic Classification of Heterogeneous Urban Scenes Using Intrascene Feature Similarity and Interscene Semantic Dependency

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing ◽

10.1109/jstars.2015.2414178 ◽

2015 ◽

Vol 8 (5) ◽

pp. 2005-2014 ◽

Cited By ~ 30

Author(s):

Xiuyuan Zhang ◽

Shihong Du ◽

Yi-Chen Wang

Keyword(s):

Semantic Classification ◽

Urban Scenes ◽

Feature Similarity ◽

Semantic Dependency

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Features, Color Spaces, and Boosting: New Insights on Semantic Classification of Remote Sensing Images

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2014.2321423 ◽

2015 ◽

Vol 53 (1) ◽

pp. 280-295 ◽

Cited By ~ 61

Author(s):

Piotr Tokarczyk ◽

Jan Dirk Wegner ◽

Stefan Walk ◽

Konrad Schindler

Keyword(s):

Remote Sensing ◽

Color Spaces ◽

Remote Sensing Images ◽

Semantic Classification

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Context-aware semantic classification of search queries for browsing community question–answering archives

Knowledge-Based Systems ◽

10.1016/j.knosys.2016.01.008 ◽

2016 ◽

Vol 96 ◽

pp. 1-13 ◽

Cited By ~ 19

Author(s):

Alejandro Figueroa ◽

Günter Neumann

Keyword(s):

Question Answering ◽

Context Aware ◽

Semantic Classification ◽

Search Queries ◽

Community Question Answering

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Structure and Semantics of Tactile Verbs in a Comparative Aspect (On the Material of the English, German and Russian Languages)

Uchenye zapiski St. Petersburg University of Management Technologies and Economics ◽

10.35854/2541-8106-2021-3-58-63 ◽

2021 ◽

pp. 58-63

Author(s):

Yu. A. Sakhno

Keyword(s):

Comparative Study ◽

Semantic Features ◽

Semantic Classification ◽

Comparative Aspect ◽

Similarities And Differences ◽

The Comparative Study ◽

Linguistic Units

This article deals with the study of the structural and semantic features of tactile verbs (hereinafter TVs) in English, German and Russian. Particular attention is paid to the comparative study of TVs, which allows us to identify structural and semantic similarities and differences of linguistic units studied. The structural and semantic classification of TVs in the compared languages is also provided.

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