Knowledge encapsulation framework for collaborative social modeling

Andrew J. Cowell, Michelle L. Gregory, Eric J. Marshall, Liam McGrath

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

This paper describes the Knowledge Encapsulation Framework (KEF), a suite of tools to enable knowledge inputs (relevant, domain-specific facts) to modeling and simulation projects, as well as other domains that require effective collaborative workspaces for knowledge-based task. This framework can be used to capture evidence (e.g., trusted material such as journal articles and government reports), discover new evidence (covering both trusted and social media), enable discussions surrounding domain-specific topics and provide automatically generated semantic annotations for improved corpus investigation. The current KEF implementation is presented within a wiki environment, providing a simple but powerful collaborative space for team members to review, annotate, discuss and align evidence with their modeling frameworks. The novelty in this approach lies in the combination of automatically tagged and user-vetted resources, which increases user trust in the environment, leading to ease of adoption for the collaborative environment.

Original languageEnglish
Title of host publicationTechnosocial Predictive Analytics - Papers from the AAAI Spring Symposium
Pages12-19
Number of pages8
StatePublished - 2009
Externally publishedYes
Event2009 AAAI Spring Symposium - Stanford, CA, United States
Duration: Mar 23 2009Mar 25 2009

Publication series

NameAAAI Spring Symposium - Technical Report
VolumeSS-09-09

Conference

Conference2009 AAAI Spring Symposium
Country/TerritoryUnited States
CityStanford, CA
Period03/23/0903/25/09

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