Towards an Emergent Semantic Web

Portmann, Edy (2012). Towards an Emergent Semantic Web. Tiny Transactions on Computer Science, 1

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In his in uential article about the evolution of the Web, Berners-Lee [1] envisions a Semantic Web in which humans and computers alike are capable of understanding and processing information. This vision is yet to materialize. The main obstacle for the Semantic Web vision is that in today's Web meaning is rooted most often not in formal semantics, but in natural language and, in the sense of semiology, emerges not before interpretation and processing. Yet, an automated form of interpretation and processing can be tackled by precisiating raw natural language. To do that, Web agents extract fuzzy grassroots ontologies through induction from existing Web content. Inductive fuzzy grassroots ontologies thus constitute organically evolved knowledge bases that resemble automated gradual thesauri, which allow precisiating natural language [2]. The Web agents' underlying dynamic, self-organizing, and best-effort induction, enable a sub-syntactical bottom up learning of semiotic associations. Thus, knowledge is induced from the users' natural use of language in mutual Web interactions, and stored in a gradual, thesauri-like lexical-world knowledge database as a top-level ontology, eventually allowing a form of computing with words [3]. Since when computing with words the objects of computation are words, phrases and propositions drawn from natural languages, it proves to be a practical notion to yield emergent semantics for the Semantic Web. In the end, an improved understanding by computers on the one hand should upgrade human- computer interaction on the Web, and, on the other hand allow an initial version of human- intelligence amplification through the Web.

Item Type:

Journal Article (Original Article)

Division/Institute:

03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems > Information Management
03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems

UniBE Contributor:

Portmann, Edy

Subjects:

600 Technology > 650 Management & public relations

Projects:

[459] Big Data Analytics and Management

Language:

English

Submitter:

Sara D'Onofrio

Date Deposited:

10 Apr 2014 10:48

Last Modified:

02 Nov 2015 09:34

Uncontrolled Keywords:

Artificial Intelligence, Human-Computer Interaction

BORIS DOI:

10.7892/boris.45579

URI:

https://boris.unibe.ch/id/eprint/45579

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