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米 に 関 す る 知 識 ・ 情 報 ポータ ル に お け る 集 合 知 生 態 系 の 管 理 に お け る 研 究 Collective Intelligence Ecosystem on Rice Knowledge Portal

By Frederic Andres, Asanee Kawtrakul, Richard Chbeir and Hiroshi IshikawaWhat For How, Frederic Andres, Asanee Kawtrakul, Richard Chbeir and Hiroshi Ishikawa

Abstract

This project introduces a collaborative multilingual semantic management of digital resources rltd related to Rice dmin domain. We pr provide id a fr framework rk that combines approaches based on Semantic Computing and Language Engineering with topic map data model (ISO 13250) to provide an effective semantic service. The platform combines a topic maps-based semantic support to the 5W1H model (Where, Who. When, What, Why and How). The MetaSemflow approach merges a local semantic indexing (metadata, feature vector) of multimedia documents and a vertical global semantic management according to end-users expertise and profile. 1. Background • Explosion of agriculture-related digital archives accessible over Internet • Needs to improve the semantic of multi-lingual multi-disciplinary agricultural rice studies • Large agriculture community • Management of the semantic interoperability based on scopes & profiles 2. MetaSemFlow Model LSA-enriched Topic Map data model (iso 12350

Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.190.6392
Provided by: CiteSeerX
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