An Introduction to the Syntax and Content of Cyc
Cynthia Matuszek,John Cabral,Michael Witbrock,John DeOliveira +3 more
- pp 44-49
TLDR
Spring Symposium on Formalizing and Compiling Background Knowledge and Its Applications to Knowledge Representation and Question Answering, Stanford, CA, March 2006.Abstract:
Spring Symposium on Formalizing and Compiling Background Knowledge and Its Applications to Knowledge Representation and Question Answering, Stanford, CA, March 2006.read more
Citations
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Proceedings ArticleDOI
Yago: a core of semantic knowledge
TL;DR: YAGO as discussed by the authors is a light-weight and extensible ontology with high coverage and quality, which includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as HASONEPRIZE).
Journal ArticleDOI
A Survey on Knowledge Graphs: Representation, Acquisition and Applications
TL;DR: A comprehensive review of the knowledge graph covering overall research topics about: 1) knowledge graph representation learning; 2) knowledge acquisition and completion; 3) temporal knowledge graph; and 4) knowledge-aware applications and summarize recent breakthroughs and perspective directions to facilitate future research.
Journal ArticleDOI
A survey on opinion mining and sentiment analysis
Kumar Satish Ravi,Vadlamani Ravi +1 more
TL;DR: A rigorous survey on sentiment analysis is presented, which portrays views presented by over one hundred articles published in the last decade regarding necessary tasks, approaches, and applications of sentiment analysis.
Journal ArticleDOI
YAGO: A Large Ontology from Wikipedia and WordNet
TL;DR: YAGO is a large ontology with high coverage and precision, based on a clean logical model with a decidable consistency that allows representing n-ary relations in a natural way while maintaining compatibility with RDFS.
Journal ArticleDOI
Knowledge Graphs
Aidan Hogan,Eva Blomqvist,Michael Cochez,Claudia d'Amato,Gerard de Melo,Claudio Gutierrez,José Emilio Labra Gayo,Sabrina Kirrane,Sebastian Neumaier,Axel Polleres,Roberto Navigli,Axel-Cyrille Ngonga Ngomo,Sabbir M. Rashid,Anisa Rula,Lukas Schmelzeisen,Juan F. Sequeda,Steffen Staab,Antoine Zimmermann +17 more
TL;DR: The historical events that lead to the interweaving of data and knowledge are tracked to help improve knowledge and understanding of the world around us.
References
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Journal ArticleDOI
CYC: a large-scale investment in knowledge infrastructure
TL;DR: The fundamental assumptions of doing such a large-scale project are examined, the technical lessons learned by the developers are reviewed, and the range of applications that are or soon will be enabled by the technology is surveyed.
Proceedings Article
The role of common ontology in achieving sharable, reusable knowledge bases
TL;DR: A solar cell has a heat collector bar with a heat absorbing material in contact there with a transparent web member having a plurality of capsule uniformly distributed therein with each capsules having a suspension of highly reflective, flake-like, field responsive particles therein.
Proceedings Article
Searching for common sense: populating Cyc™ from the web
Cynthia Matuszek,Michael Witbrock,Robert C. Kahlert,John Cabral,Dave Schneider,Purvesh Shah,Douglas B. Lenat +6 more
TL;DR: Initial work is presented on a method of using a combination of Cyc and the World Wide Web, accessed via Google, to assist in entering knowledge into Cyc.
First-Orderized ResearchCyc : Expressivity and Efficiency in a Common-Sense Ontology
TL;DR: A translati on of a large part of the Cyc ontology into FirstOrder Logic is presented, indicating that, while the use of higher-order logic is not essential to the representabilit y of common-sense knowledge, it greatly improves the efficiency of reasoning.
Proceedings ArticleDOI
Using knowledge to facilitate factoid answer pinpointing
TL;DR: In this paper, the Webclopedia QA system employs a range of knowledge resources, including a QA Typology with answer patterns, WordNet, information about typical numerical answer ranges, and semantic relations identified by a robust parser, to filter out likely-looking but wrong candidate answers.