Title :
Data Enrichment Using Web APIs
Author :
Gomadam, Karthik ; Yeh, Peter Z. ; Verma, Kunal ; Miller, John A.
Author_Institution :
Accenture Technol. Labs., Univ. of Georgia, San Jose, CA, USA
Abstract :
As businesses seek to monetize their data, they are leveraging Web-based delivery mechanisms to provide publically available data sources. Also, as analytics becomes a central part of many business functions such as customer segmentation, competitive intelligence and fraud detection, many businesses are seeking to enrich their internal data records with data from these data sources. As the number of sources with varying degrees of accuracy and quality proliferate, it is a non-trivial task to effectively select which sources to use for a particular enrichment task. The old model of statically buying data from one or two providers becomes inefficient because of the rapid growth of new forms of useful data such as social media and the lack of dynamism to plug sources in and out. In this paper, we present the data enrichment framework, a tool that uses data mining and other semantic techniques to automatically guide the selection of sources. The enrichment framework also monitors the quality of the data sources and automatically penalizes sources that continue to return low quality results.
Keywords :
Internet; application program interfaces; business data processing; data mining; Web API; Web-based delivery mechanism; business functions; competitive intelligence; customer segmentation; data enrichment framework; data mining; data sources; fraud detection; semantic techniques; social media; Cities and towns; Companies; Databases; Equations; Media; Monitoring;
Conference_Titel :
Services Economics (SE), 2012 IEEE First International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4673-3048-0