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You searched for subject:(commonsense knowledge). Showing records 1 – 13 of 13 total matches.

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University of Illinois – Urbana-Champaign

1. Mancilla Caceres, Juan F. A Turing Game for commonsense knowledge extraction.

Degree: MS, 0112, 2010, University of Illinois – Urbana-Champaign

Commonsense is of primary interest to AI research since the inception of the field. Traditionally, commonsense knowledge is gathered by using humans to create and… (more)

Subjects/Keywords: Commonsense Knowledge; Crowd-sourcing; Knowledge Acquisition

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mancilla Caceres, J. F. (2010). A Turing Game for commonsense knowledge extraction. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/16159

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mancilla Caceres, Juan F. “A Turing Game for commonsense knowledge extraction.” 2010. Thesis, University of Illinois – Urbana-Champaign. Accessed October 18, 2019. http://hdl.handle.net/2142/16159.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mancilla Caceres, Juan F. “A Turing Game for commonsense knowledge extraction.” 2010. Web. 18 Oct 2019.

Vancouver:

Mancilla Caceres JF. A Turing Game for commonsense knowledge extraction. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2010. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/2142/16159.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mancilla Caceres JF. A Turing Game for commonsense knowledge extraction. [Thesis]. University of Illinois – Urbana-Champaign; 2010. Available from: http://hdl.handle.net/2142/16159

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Louisiana State University

2. Arab Khazaeli, Mahdi. Automated Semantic Content Extraction from Images.

Degree: PhD, Engineering Science and Materials, 2013, Louisiana State University

 In this study, an automatic semantic segmentation and object recognition methodology is implemented which bridges the semantic gap between low level features of image content… (more)

Subjects/Keywords: scene detection; contextual cueing; segmentation; Image processing; commonsense knowledge

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APA (6th Edition):

Arab Khazaeli, M. (2013). Automated Semantic Content Extraction from Images. (Doctoral Dissertation). Louisiana State University. Retrieved from etd-07052013-150623 ; https://digitalcommons.lsu.edu/gradschool_dissertations/2697

Chicago Manual of Style (16th Edition):

Arab Khazaeli, Mahdi. “Automated Semantic Content Extraction from Images.” 2013. Doctoral Dissertation, Louisiana State University. Accessed October 18, 2019. etd-07052013-150623 ; https://digitalcommons.lsu.edu/gradschool_dissertations/2697.

MLA Handbook (7th Edition):

Arab Khazaeli, Mahdi. “Automated Semantic Content Extraction from Images.” 2013. Web. 18 Oct 2019.

Vancouver:

Arab Khazaeli M. Automated Semantic Content Extraction from Images. [Internet] [Doctoral dissertation]. Louisiana State University; 2013. [cited 2019 Oct 18]. Available from: etd-07052013-150623 ; https://digitalcommons.lsu.edu/gradschool_dissertations/2697.

Council of Science Editors:

Arab Khazaeli M. Automated Semantic Content Extraction from Images. [Doctoral Dissertation]. Louisiana State University; 2013. Available from: etd-07052013-150623 ; https://digitalcommons.lsu.edu/gradschool_dissertations/2697


Universidade Nova

3. Pathak, Mahesh. Conservation GIS: Ontology and spatial reasoning for commonsense knowledge.

Degree: 2011, Universidade Nova

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Geographic information available from multiple sources are… (more)

Subjects/Keywords: Commonsense spatial knowledge; Conservation GIS; Geospatial ontology; Ontology engineering; Spatial cognition

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APA (6th Edition):

Pathak, M. (2011). Conservation GIS: Ontology and spatial reasoning for commonsense knowledge. (Thesis). Universidade Nova. Retrieved from http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/5616

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Pathak, Mahesh. “Conservation GIS: Ontology and spatial reasoning for commonsense knowledge.” 2011. Thesis, Universidade Nova. Accessed October 18, 2019. http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/5616.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Pathak, Mahesh. “Conservation GIS: Ontology and spatial reasoning for commonsense knowledge.” 2011. Web. 18 Oct 2019.

Vancouver:

Pathak M. Conservation GIS: Ontology and spatial reasoning for commonsense knowledge. [Internet] [Thesis]. Universidade Nova; 2011. [cited 2019 Oct 18]. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/5616.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pathak M. Conservation GIS: Ontology and spatial reasoning for commonsense knowledge. [Thesis]. Universidade Nova; 2011. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/5616

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Ottawa

4. Hassani, Kaveh. Commonsense Knowledge for 3D Modeling: A Machine Learning Approach .

Degree: 2017, University of Ottawa

 Common‒sense knowledge is a collection of non‒expert and agreed‒upon facts and information about the world shared among most people past early childhood based on their… (more)

Subjects/Keywords: Machine Learning; Natural Language Processing; Commonsense Knowledge; Deep Learning; 3D Modelling

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APA (6th Edition):

Hassani, K. (2017). Commonsense Knowledge for 3D Modeling: A Machine Learning Approach . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/36165

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hassani, Kaveh. “Commonsense Knowledge for 3D Modeling: A Machine Learning Approach .” 2017. Thesis, University of Ottawa. Accessed October 18, 2019. http://hdl.handle.net/10393/36165.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hassani, Kaveh. “Commonsense Knowledge for 3D Modeling: A Machine Learning Approach .” 2017. Web. 18 Oct 2019.

Vancouver:

Hassani K. Commonsense Knowledge for 3D Modeling: A Machine Learning Approach . [Internet] [Thesis]. University of Ottawa; 2017. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/10393/36165.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hassani K. Commonsense Knowledge for 3D Modeling: A Machine Learning Approach . [Thesis]. University of Ottawa; 2017. Available from: http://hdl.handle.net/10393/36165

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Adelaide

5. Nowak, Krzysztof Zbigniew. Conceptual reasoning : belief, multiple agents and preference / by Krzysztof Zbigniew Nowak.

Degree: 1998, University of Adelaide

 One of the central issues in Artificial Intelligence (AI) is common sense reasoning. This includes logics of knowledge and belief, non-monotonic reasoning, truth-maintenance and belief… (more)

Subjects/Keywords: Commonsense reasoning.; Knowledge representation (Information theory)

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APA (6th Edition):

Nowak, K. Z. (1998). Conceptual reasoning : belief, multiple agents and preference / by Krzysztof Zbigniew Nowak. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/19565

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Nowak, Krzysztof Zbigniew. “Conceptual reasoning : belief, multiple agents and preference / by Krzysztof Zbigniew Nowak.” 1998. Thesis, University of Adelaide. Accessed October 18, 2019. http://hdl.handle.net/2440/19565.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Nowak, Krzysztof Zbigniew. “Conceptual reasoning : belief, multiple agents and preference / by Krzysztof Zbigniew Nowak.” 1998. Web. 18 Oct 2019.

Vancouver:

Nowak KZ. Conceptual reasoning : belief, multiple agents and preference / by Krzysztof Zbigniew Nowak. [Internet] [Thesis]. University of Adelaide; 1998. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/2440/19565.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nowak KZ. Conceptual reasoning : belief, multiple agents and preference / by Krzysztof Zbigniew Nowak. [Thesis]. University of Adelaide; 1998. Available from: http://hdl.handle.net/2440/19565

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


EPFL

6. Boia, Marina. Acquiring Broad Commonsense Knowledge for Sentiment Analysis Using Human Computation.

Degree: 2016, EPFL

 While artificial intelligence is successful in many applications that cover specific domains, for many commonsense problems there is still a large gap with human performance.… (more)

Subjects/Keywords: commonsense knowledge acquisition; human computation; crowdsourcing; gamification; games with a purpose; sentiment analysis; sentiment classification; fine-grained opinion extraction

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APA (6th Edition):

Boia, M. (2016). Acquiring Broad Commonsense Knowledge for Sentiment Analysis Using Human Computation. (Thesis). EPFL. Retrieved from http://infoscience.epfl.ch/record/221433

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Boia, Marina. “Acquiring Broad Commonsense Knowledge for Sentiment Analysis Using Human Computation.” 2016. Thesis, EPFL. Accessed October 18, 2019. http://infoscience.epfl.ch/record/221433.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Boia, Marina. “Acquiring Broad Commonsense Knowledge for Sentiment Analysis Using Human Computation.” 2016. Web. 18 Oct 2019.

Vancouver:

Boia M. Acquiring Broad Commonsense Knowledge for Sentiment Analysis Using Human Computation. [Internet] [Thesis]. EPFL; 2016. [cited 2019 Oct 18]. Available from: http://infoscience.epfl.ch/record/221433.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Boia M. Acquiring Broad Commonsense Knowledge for Sentiment Analysis Using Human Computation. [Thesis]. EPFL; 2016. Available from: http://infoscience.epfl.ch/record/221433

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Louisiana State University

7. Javadpour, Seyedeh Leili. Resolving pronominal anaphora using commonsense knowledge.

Degree: PhD, Engineering Science and Materials, 2013, Louisiana State University

 Coreference resolution is the task of resolving all expressions in a text that refer to the same entity. Such expressions are often used in writing… (more)

Subjects/Keywords: text processing; semantic analysis; coreference resolution; anaphora resolution; pronoun resolution; commonsense knowledge; machine learning; information extraction

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APA (6th Edition):

Javadpour, S. L. (2013). Resolving pronominal anaphora using commonsense knowledge. (Doctoral Dissertation). Louisiana State University. Retrieved from etd-07032013-180842 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1599

Chicago Manual of Style (16th Edition):

Javadpour, Seyedeh Leili. “Resolving pronominal anaphora using commonsense knowledge.” 2013. Doctoral Dissertation, Louisiana State University. Accessed October 18, 2019. etd-07032013-180842 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1599.

MLA Handbook (7th Edition):

Javadpour, Seyedeh Leili. “Resolving pronominal anaphora using commonsense knowledge.” 2013. Web. 18 Oct 2019.

Vancouver:

Javadpour SL. Resolving pronominal anaphora using commonsense knowledge. [Internet] [Doctoral dissertation]. Louisiana State University; 2013. [cited 2019 Oct 18]. Available from: etd-07032013-180842 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1599.

Council of Science Editors:

Javadpour SL. Resolving pronominal anaphora using commonsense knowledge. [Doctoral Dissertation]. Louisiana State University; 2013. Available from: etd-07032013-180842 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1599


Brno University of Technology

8. Daniš, Tomáš. Strojové porozumění s použitím znalostní báze .

Degree: 2019, Brno University of Technology

 V tejto práci je skumaná schopnosť používať zdravý rozum v moderných systémoch založených na neurónových sieťach. Zdravým rozumom je myslená schopnosť extrahovať z textu fakty,… (more)

Subjects/Keywords: neurónová sieť; uvažovanie zdravým rozumom; znalostná báza zdravého rozumu; strojové učenie; spracovanie prirodzeného jazyka; odpovedanie na otázky; znalostná báza.; neural network; commonsense reasoning; commonsense knowledge; machine learning; natural language processing; question answering; knowledge base

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APA (6th Edition):

Daniš, T. (2019). Strojové porozumění s použitím znalostní báze . (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/180176

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Daniš, Tomáš. “Strojové porozumění s použitím znalostní báze .” 2019. Thesis, Brno University of Technology. Accessed October 18, 2019. http://hdl.handle.net/11012/180176.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Daniš, Tomáš. “Strojové porozumění s použitím znalostní báze .” 2019. Web. 18 Oct 2019.

Vancouver:

Daniš T. Strojové porozumění s použitím znalostní báze . [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/11012/180176.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Daniš T. Strojové porozumění s použitím znalostní báze . [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/180176

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

9. Mauceri, Cecilia R. Expanding commonsense knowledge bases by learning from image tags.

Degree: MS, Computer Science, 2015, University of Illinois – Urbana-Champaign

 I present a method for learning new commonsense facts to augment existing commonsense knowledge bases by using the metadata of large online image collections. Online… (more)

Subjects/Keywords: Commonsense knowledge; transfer learning; image collection; knowledge extraction

…Introduction Commonsense knowledge describes the everyday facts that humans learn through experience… …sweet. Shared commonsense knowledge is an important starting point for making sense of… …reference frame, but without commonsense knowledge, any reasoning about the scene would be like… …models of their environment in the form of commonsense knowledge bases to make sense of… …observations. Commonsense knowledge bases have well established uses in text parsing [34]… 

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APA (6th Edition):

Mauceri, C. R. (2015). Expanding commonsense knowledge bases by learning from image tags. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/88091

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mauceri, Cecilia R. “Expanding commonsense knowledge bases by learning from image tags.” 2015. Thesis, University of Illinois – Urbana-Champaign. Accessed October 18, 2019. http://hdl.handle.net/2142/88091.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mauceri, Cecilia R. “Expanding commonsense knowledge bases by learning from image tags.” 2015. Web. 18 Oct 2019.

Vancouver:

Mauceri CR. Expanding commonsense knowledge bases by learning from image tags. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2015. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/2142/88091.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mauceri CR. Expanding commonsense knowledge bases by learning from image tags. [Thesis]. University of Illinois – Urbana-Champaign; 2015. Available from: http://hdl.handle.net/2142/88091

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Arizona State University

10. Aditya, Somak. Knowledge and Reasoning for Image Understanding.

Degree: Computer Science, 2018, Arizona State University

Subjects/Keywords: Computer science; Artificial intelligence; Commonsense Reasoning; Knowledge Representation; Reasoning; Reasoning under Uncertainty; Vision

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APA (6th Edition):

Aditya, S. (2018). Knowledge and Reasoning for Image Understanding. (Doctoral Dissertation). Arizona State University. Retrieved from http://repository.asu.edu/items/50115

Chicago Manual of Style (16th Edition):

Aditya, Somak. “Knowledge and Reasoning for Image Understanding.” 2018. Doctoral Dissertation, Arizona State University. Accessed October 18, 2019. http://repository.asu.edu/items/50115.

MLA Handbook (7th Edition):

Aditya, Somak. “Knowledge and Reasoning for Image Understanding.” 2018. Web. 18 Oct 2019.

Vancouver:

Aditya S. Knowledge and Reasoning for Image Understanding. [Internet] [Doctoral dissertation]. Arizona State University; 2018. [cited 2019 Oct 18]. Available from: http://repository.asu.edu/items/50115.

Council of Science Editors:

Aditya S. Knowledge and Reasoning for Image Understanding. [Doctoral Dissertation]. Arizona State University; 2018. Available from: http://repository.asu.edu/items/50115


University of Central Florida

11. Schwartz, Hansen A. The Acquisition Of Lexical Knowledge From The Web For Aspects Of Semantic Interpretation.

Degree: 2011, University of Central Florida

 This work investigates the effective acquisition of lexical knowledge from the Web to perform semantic interpretation. The Web provides an unprecedented amount of natural language… (more)

Subjects/Keywords: Commonsense reasoning; Computational linguistics; Knowledge acquisition (Expert systems); Lexicology  – Data processing; Natural language processing (Computer science); Semantics; World wide web; Electrical and Computer Engineering; Electrical and Electronics; Engineering; Dissertations, Academic  – Engineering and Computer Science, Engineering and Computer Science  – Dissertations, Academic

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Schwartz, H. A. (2011). The Acquisition Of Lexical Knowledge From The Web For Aspects Of Semantic Interpretation. (Doctoral Dissertation). University of Central Florida. Retrieved from https://stars.library.ucf.edu/etd/1963

Chicago Manual of Style (16th Edition):

Schwartz, Hansen A. “The Acquisition Of Lexical Knowledge From The Web For Aspects Of Semantic Interpretation.” 2011. Doctoral Dissertation, University of Central Florida. Accessed October 18, 2019. https://stars.library.ucf.edu/etd/1963.

MLA Handbook (7th Edition):

Schwartz, Hansen A. “The Acquisition Of Lexical Knowledge From The Web For Aspects Of Semantic Interpretation.” 2011. Web. 18 Oct 2019.

Vancouver:

Schwartz HA. The Acquisition Of Lexical Knowledge From The Web For Aspects Of Semantic Interpretation. [Internet] [Doctoral dissertation]. University of Central Florida; 2011. [cited 2019 Oct 18]. Available from: https://stars.library.ucf.edu/etd/1963.

Council of Science Editors:

Schwartz HA. The Acquisition Of Lexical Knowledge From The Web For Aspects Of Semantic Interpretation. [Doctoral Dissertation]. University of Central Florida; 2011. Available from: https://stars.library.ucf.edu/etd/1963

12. Sharma, Arpit. Solving Winograd Schema Challenge : Using Semantic Parsing, Automatic Knowledge Acquisition and Logical Reasoning.

Degree: Computer Science, 2014, Arizona State University

Subjects/Keywords: Computer science; Artificial intelligence; Automatic Background Knowledge Extraction; Commonsense Reasoning; Natural Language Prcessing; Semantic Parsing; Winograd Schema Challenge

commonsense knowledge about the input via previous experiences. Third and last one is to reach a… …encode the commonsense knowledge from FrameNet, VerbNet, PropBank, etc. while still lacking the… …it is required to have some sort of background information or commonsense knowledge about… …other words, one of the reason that humans have commonsense knowledge about entities and… …events is day-to-day reading. Another source of commonsense knowledge for humans are… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sharma, A. (2014). Solving Winograd Schema Challenge : Using Semantic Parsing, Automatic Knowledge Acquisition and Logical Reasoning. (Masters Thesis). Arizona State University. Retrieved from http://repository.asu.edu/items/27387

Chicago Manual of Style (16th Edition):

Sharma, Arpit. “Solving Winograd Schema Challenge : Using Semantic Parsing, Automatic Knowledge Acquisition and Logical Reasoning.” 2014. Masters Thesis, Arizona State University. Accessed October 18, 2019. http://repository.asu.edu/items/27387.

MLA Handbook (7th Edition):

Sharma, Arpit. “Solving Winograd Schema Challenge : Using Semantic Parsing, Automatic Knowledge Acquisition and Logical Reasoning.” 2014. Web. 18 Oct 2019.

Vancouver:

Sharma A. Solving Winograd Schema Challenge : Using Semantic Parsing, Automatic Knowledge Acquisition and Logical Reasoning. [Internet] [Masters thesis]. Arizona State University; 2014. [cited 2019 Oct 18]. Available from: http://repository.asu.edu/items/27387.

Council of Science Editors:

Sharma A. Solving Winograd Schema Challenge : Using Semantic Parsing, Automatic Knowledge Acquisition and Logical Reasoning. [Masters Thesis]. Arizona State University; 2014. Available from: http://repository.asu.edu/items/27387

13. Mancilla Caceres, Juan. Social sensing games.

Degree: PhD, 0112, 2014, University of Illinois – Urbana-Champaign

 We introduce Social Sensing Games (SSGs), a new method for collecting data about social relationships, and present an algorithm that can be used to efficiently… (more)

Subjects/Keywords: Game-Based Methods; Social Network Analysis; Identification of Bullying and Cyberbullying; Evaluation of Commonsense Knowledge; Formalization of Social Sensing through Games; Global Inference from Pairwise Interactions; Visualizing Pairwise Interactions; Combining observational methods with lab-controlled experiments in a computational setting

Commonsense Knowledge . 3.6 Application: Identification of Aggressive Individuals 3.7 Conclusions… …commonsense knowledge and is relevant to the Commonsense and AI communities. The second one, focuses… …we present two case studies of SSGs: the evaluation of commonsense knowledge and the… …some information relevant to each of the case studies, including Commonsense Knowledge and… …evaluation of commonsense knowledge. 2.1 Related Fields 2.1.1 Human Computation Human Computation… 

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APA (6th Edition):

Mancilla Caceres, J. (2014). Social sensing games. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/49616

Chicago Manual of Style (16th Edition):

Mancilla Caceres, Juan. “Social sensing games.” 2014. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed October 18, 2019. http://hdl.handle.net/2142/49616.

MLA Handbook (7th Edition):

Mancilla Caceres, Juan. “Social sensing games.” 2014. Web. 18 Oct 2019.

Vancouver:

Mancilla Caceres J. Social sensing games. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2014. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/2142/49616.

Council of Science Editors:

Mancilla Caceres J. Social sensing games. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2014. Available from: http://hdl.handle.net/2142/49616

.