Exploiting Data Semantics to Discover, Extract, and Model Web Sources

We describe DEIMOS, a system that automatically discovers and models new sources of information. The system exploits four core technologies developed by our group that makes an end-to-end solution to this problem possible. First, given an example source, DEIMOS finds other similar sources online. Second, it invokes and extracts data from these sources. Third, given the syntactic structure of a source, DEIMOS maps its inputs and outputs to semantic types. Finally, it infers the source’s semantic definition, i.e., the function that maps the inputs to the outputs. DEIMOS is able to successfully automate these steps by exploiting a combination of background knowledge and data semantics. We describe the challenges in integrating separate components into a unified approach to discovering, extracting and modeling new online sources. We provide an end-toend validation of the system in two information domains to show that it can successfully discover and model new data sources in those do...

• Type: Conference
• Year: 2008
• Where: ICDM
• Authors: José Luis Ambite, Craig A. Knoblock, Kristina Lerman, Anon Plangprasopchok, Thomas A. Russ, Cenk Gazen, Steven Minton, Mark James Carman
• Keywords: Data Mining, End-to-end Solution, ICDM 2008, Similar Sources Online, Source’s Semantic Definition