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Seedea, scalable creativity

Xye, consultancy for serious creators

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(:pmgraphviz -- digraph { subgraph cluster_public_code{ public_code [shape=record,label="APIs|libraries|mashups|publications|meta_repositories"]; } subgraph cluster_seedea{ seedea [shape=record,label="<discovery>discovery\n(intelligence)|<integration>integration\n(hooks)|suggestion\n(stats/ML)|evaluation\n(stats/ML)|prediction\n(CAEE)"]; } subgraph cluster_client{ client [shape=record,label="<working_platform>content|user_preferences\n(explicit feedback)|user_history\n(implicit feedback)"]; } seedea:discovery -> public_code [label="categorisation"]; seedea:integration -> client:working_platform [label="adaptation"]; } :)

mechanismdiscoveryintegrationsuggestionevaluationprediction
descriptionfinding new micro-services on the internetmaking those micro-services available on the platformpresenting micro-services only to user that should find them usefulgive user the ability to provide explicit and implicit feedback on micro-services and the mechanismsstudies the epistemological trends
toolSeedea.ServicesArchitectureWikiLayerSeedea.AImatrixinterfaceResearch.Research
API?????

Suggestion mechanism

 MS1MS2...MSnMSn+1
U1     
U2     
...     
Um     
Um+1     

See also Recked: A Night of Recommendation Technologies, January 2009

External data-mining

initially the principle was to use only data from the local Seedea instance (aka here but after reflection:

make a lot of sense. Adapters (see Yahoo! Execute or RunMyProcess for potential help) would have to be used so eventually a balance of effort/information would decide if it's sufficiently valuable but the opportunity must be studied, especially to bootstrap the system.

To do


Page last modified on July 07, 2009, at 02:56 PM