building linked data from a social media topic

Matching engine

Use case for Linked Data matching service for renewable

energy facts and people

1) News extracted from a social network( or any other online medium)

News taken from a social network: .i.e “Linkedin” ( can be anyone)

2) First data extraction pass: Automated data mining applied to identify initial key

entities:

• Companies: Fotowatio, Lowe's, Macy's, Manulife Financial Corporation, Renewable Ventures, Wells Fargo, Xcel Energy

• People: Matt Cheney , CEO of Municipal Mortgage and Equity• Technology terms: energy credits, energy sector, solar energy

projects• Event: Company Affiliation: Renewable Ventures- company_parent:

Fotowatio- affiliate

3) Querying other online sources to build and aggregate “mashup of facts” –”seeding”

4) Second data extraction pass: Additional data mining applied from online sources to enrich the

initial facts:• Companies: Fotowatio, Lowe's, Macy's, Manulife Financial Corporation, Renewable

Ventures, Wells Fargo, Xcel Energy, GE Energy Financial Services, Qualitas Venture Capital, Landon Group

• People: Matt Cheney CEO of Municipal Mortgage and Equity, Barry Neal director of Environmental Finance Wells Fargo, Jerry Hanrahan, Managing Director Municipal Mortgage and Equity,Carrol Dollard , energy engineer -Colorado State, Miguel Florez , director of Marketing - Xcel Energy,

• Technology terms: energy credits, energy sector, solar energy projects, power producer,solar energy mandates , long –term electricity contract, volatile energy markets

• Event: Company Affiliation: Renewable Ventures- company_parent: Fotowatio- affiliate , Xcel Energy solicits bids for solar installation , AMEC plc construct solar array panels

Build “derived data”

5) Analyze links and “derived data” to build matching profile/recommendation

Query derived links from news story to augment facts and aggregate more data, which in turn can be applied towards custom recommendations.

The software will be able to identify automatically without human intervention relations between companies and people and query in depth consequences of event ( Affiliates – “Renewable Ventures - investment -Xcel Energy-bid Univ of Colorado-bid solar installation-AMEX plc –implementation-key people-competitors-technologies involved –OPPORTUNITY :match/recommendation against existing facts in the database!

Single use case examined here – there are hundreds like these parsed each day.

Potential for reference data and opportunity indexing.