ConceptNet 5: A Large Semantic Network for Relational Knowledge

ConceptNet is a knowledge representation project, providing a large semantic graph that describes general human knowledge and how it is expressed in natural language. Here we present the latest iteration, ConceptNet 5, with a focus on its fundamental design decisions and ways to interoperate with it.

[1]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[2]  Antal van den Bosch,et al.  A Kids' Open Mind Common Sense , 2010, AAAI Fall Symposium: Commonsense Knowledge.

[3]  Sven J. Körner,et al.  RESI - A Natural Language Specification Improver , 2009, 2009 IEEE International Conference on Semantic Computing.

[4]  Henry Holtzman,et al.  The Glass Infrastructure: Using Common Sense to Create a Dynamic, Place-Based Social Information System , 2012, AI Mag..

[5]  Henry Lieberman,et al.  Can Common Sense uncover cultural differences in computer applications? , 2006, IFIP AI.

[6]  Erik Cambria,et al.  SenticSpace: Visualizing Opinions and Sentiments in a Multi-dimensional Vector Space , 2010, KES.

[7]  Iryna Gurevych,et al.  Extracting Lexical Semantic Knowledge from Wikipedia and Wiktionary , 2008, LREC.

[8]  Chun Zhang,et al.  Storing and querying ordered XML using a relational database system , 2002, SIGMOD '02.

[9]  Lakhmi C. Jain,et al.  Knowledge-Based Intelligent Information and Engineering Systems , 2004, Lecture Notes in Computer Science.

[10]  Erik T. Mueller,et al.  Open Mind Common Sense: Knowledge Acquisition from the General Public , 2002, OTM.

[11]  Mirella Lapata,et al.  Proceedings of EMNLP 2004 , 2004 .

[12]  Henry Lieberman,et al.  Finding your way in a multi-dimensional semantic space with luminoso , 2010, IUI '10.

[13]  Jane Yung-jen Hsu,et al.  Community-based game design: experiments on social games for commonsense data collection , 2009, HCOMP '09.

[14]  Adam Pease,et al.  Towards a standard upper ontology , 2001, FOIS.

[15]  Praveen Paritosh,et al.  Freebase: a collaboratively created graph database for structuring human knowledge , 2008, SIGMOD Conference.

[16]  Dan I. Moldovan,et al.  Commonsense Knowledge Extraction Using Concepts Properties , 2011, FLAIRS Conference.

[17]  Jens Lehmann,et al.  DBpedia: A Nucleus for a Web of Open Data , 2007, ISWC/ASWC.

[18]  Manuel Blum,et al.  Verbosity: a game for collecting common-sense facts , 2006, CHI.

[19]  Martin Porter,et al.  Snowball: A language for stemming algorithms , 2001 .

[20]  Rakesh Gupta,et al.  Common Sense Data Acquisition for Indoor Mobile Robots , 2004, AAAI.

[21]  Silvia Coradeschi,et al.  On-line ADL Recognition with Prior Knowledge , 2010, STAIRS.

[22]  Simone Paolo Ponzetto,et al.  BabelNet: Building a Very Large Multilingual Semantic Network , 2010, ACL.

[23]  Yuji Matsumoto,et al.  Applying Conditional Random Fields to Japanese Morphological Analysis , 2004, EMNLP.

[24]  Oren Etzioni,et al.  Open Information Extraction from the Web , 2007, CACM.

[25]  Ewan Klein,et al.  Natural Language Processing with Python , 2009 .

[26]  Michael Strube,et al.  WikiNet: A Very Large Scale Multi-Lingual Concept Network , 2010, LREC.

[27]  Catherine Havasi,et al.  ConceptNet 3 : a Flexible , Multilingual Semantic Network for Common Sense Knowledge , 2007 .

[28]  Henry Lieberman,et al.  AnalogySpace: Reducing the Dimensionality of Common Sense Knowledge , 2008, AAAI.

[29]  Gerhard Weikum,et al.  MENTA: inducing multilingual taxonomies from wikipedia , 2010, CIKM '10.