%DVHG RQ DQ H[SHUW ¶V GLJLWDO WUDFH LQ D FRPSDQ\ semantic technologies in combination with enterprise social media applications enable the identification of experts in a required field of knowledge. We analyze how this identification of experts can be used to target the right crowd for corporate problem solving and analyze how accurate this expert identification algorithm can be in the case of sparse digital trace data. The case study presents real-world data of the so-FDOOHG 8UJHQW 5HTXHVWV IURP 6LHPHQV ¶ 7echnoWeb, a Siemens-internal crowd sourcing method. The three metrics spam reduction factor, gain factor and conversion rate are defined in order to measure the quality of the semantic message targeting in relation to a simple broadcasting of the Urgent Request to every TechnoWeb user. We apply these metrics to the real-world data of the Urgent Requests and analyze the reasons why some messages are better targeted than others.
The basic challenge of information management is to provide useful information to the right people in a given situation, such as for problem solving. In a company, semantic technologies in combination with enterprise social media applications can be applied for the identification of experts in a required field of expertise. Our approach uses the Web 3L model, a 3-layer structure of networks which includes relations from social and semantic networks.It is shown how this model can be used to target the right crowd for corporate problem solving. The distribution of urgent requests in an internal knowledge networking tool is described as a real world example that is used in a productive environment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.