SIOC Post profile for "AI3:::Adaptive Information"
type: Document
description: A SIOC profile describes the structure and contents of a weblog in a machine readable form. For more information please refer to http://sioc-project.org/.
primary topic: Shaping Wikipedia into a Computable Knowledge Base
generator agent: http://rdfs.org/sioc/wp-sioc.php

Shaping Wikipedia into a Computable Knowledge Base
type: Post
has container: weblog
has creator: Mike Bergman
maker: Mike Bergman
created: 2015-03-31T21:03:04Z
content: Part of a Vision for Information Interoperability on the Web Download PDF Wikipedia is arguably the most important information source yet invented for natural language processing (NLP) and artificial intelligence, in addition to its role as humanity's largest encyclopedia. Wikipedia is the principal information source for such prominent services as IBM's Watson [1], Freebase [2], the Google Knowledge Graph [3], Apple's Siri [4], YAGO [5], and DBpedia [6], the core reference structure for linked open data [7]. Wikipedia information has assumed a prominent role in NLP applications in word sense disambiguation, named entity recognition, co-reference resolution, and multi-lingual alignments; in information retrieval in query expansion, multi-lingual retrieval, question answering, entity ranking, text categorization, and topic indexing; and in semantic applications in topic extraction, relation extraction, entity extraction, entity typing, semantic relatedness, and ontology building [8]. The massive size of Wikipedia -- with more than 26 million articles across 250 different language versions [9,10] -- makes it a rich resource for reference entities and concepts. Structural features of Wikipedia that help to inform the understanding of relationships and connections include articles (and their embedded entities and concepts), article abstracts, article titles, infoboxes, redirects, internal and external links, editing histories, categories (in part), discussion pages, disambiguation pages, images and associated metadata, templates, tables, and pages of lists, not to mention Wikipedia as a whole being used as a corpus or graph [11]. It is no wonder that Wikipedia is referenced in about 665,000 academic articles and books [12]. And all of this occurs in a phenomenon that is not yet 15 years old! Wikipedia is unparalleled as a resource for mining these resources of structure, concepts and entities. But, and here is the challenge, Wikipedia is never itself used as a computabl…
encoded: Part of a Vision for Information Interoperability on the Web Download PDF Wikipedia is arguably the most important information source yet invented for natural language processing (NLP) and artificial intelligence, in addition to its role as humanity’s largest encyclopedia. Wikipedia is the principal information source for such prominent services as IBM’s Watson [1], Freebase [2], the Google Knowledge Graph [3], Apple’s Siri [4], YAGO [5], and DBpedia [6], the core reference structure for linked open data [7]. Wikipedia information has assumed a prominent role in NLP applications in word sense disambiguation, named entity recognition, co-reference resolution, and multi-lingual alignments; in information retrieval in query expansion, multi-lingual retrieval, question answering, entity ranking, text categorization, and topic indexing; and in semantic applications in topic extraction, relation extraction, entity extraction, entity typing, semantic relatedness, and ontology building [8]. The massive size of Wikipedia — with more than 26 million articles across 250 different language versions [9,10] — makes it a rich resource for reference entities and concepts. Structural features of Wikipedia that help to inform the understanding of relationships and connections include articles (and their embedded entities and concepts), article abstracts, article titles, infoboxes, redirects, internal and external links, editing histories, categories (in part), discussion pages, disambiguation pages, images and associated metadata, templates, tables, and pages of lists, not to mention Wikipedia as a whole being used as a corpus or graph [11]. It is no wonder that Wikipedia is referenced in about 665,000 academic articles and books [12]. And all of this occurs in a phenomenon that is not yet 15 years old! Wikipedia is unparalleled as a resource for mining these resources of structure, concepts and entities. But, and here is the challenge, Wikipedia is never itself used as a computable …
topic: Adaptive Innovation
topic: Artificial Intelligence
topic: Big Structure
topic: Peircean Principles
topic: Semantic Web
topic: UMBEL
has reply: comment-506668
has reply: comment-506669
links to: Download PDF
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links to: Freebase: a collaboratively created graph database for structuring human knowledge
links to: Introducing the Knowledge Graph: Things, not Strings
links to: Yago: a core of semantic knowledge.
links to: ISWC2007 IU Auer.pdf
links to: Linked data: Evolving the web into a global data space
links to: Mining Meaning from Wikipedia
links to: The sum of all human knowledge: A systematic review of scholarly research on the content of Wikipedia
links to: Wikipedia:Multilingual statistics
links to: In Search of ‘Gold Standards’ for the Semantic Web
links to: http://scholar.google.com/scholar?as_vis=1&q=wikipedia&hl=en&as_sdt=1,16

Mike Bergman
type: User

Mike Bergman
type: Person

[23]
label: [23

[39]
label: [39

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spoke-and-hub design

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