RevistaSinfac_CP_210x280.indd

First Page		Document Content
Date: 2015-02-05 12:29:39 Natural language processing Business intelligence Risk Actuarial science Unstructured data Text mining Operational risk Analytics Information extraction Science Statistics Management		RevistaSinfac_CP_210x280.indd Add to Reading List Source URL: www.serasaexperian.com.br Download Document from Source Website File Size: 2,79 MB Share Document on Facebook

	Toward Completeness in Concept Extraction and Classification Eduard Hovy and Zornitsa Kozareva USC Information Sciences Institute 4676 Admiralty Way Marina del Rey, CA 90292 , DocID: 1vo3X - View Document
	ISPRS Commission III on ‘Remote Sensing’ and WG III/5 on ‘Information Extraction from LiDAR Intensity Data’ is pleased to announce the availability of two data sets collected using different sensors and platforms DocID: 1veuV - View Document
	Distributional Semantics for Medical Information Extraction Lautaro Quiroz1, Lydia Mennes2, Mostafa Dehghani1, Evangelos Kanoulas1 1 2 University of Amsterdam, CTcue DocID: 1v2Ee - View Document
	Clinical Information Extraction at the CLEF eHealth Evaluation lab 2016 Aur´elie N´ev´eol1 , K. Bretonnel Cohen1,2 , Cyril Grouin1 , Thierry Hamon1,3 Thomas Lavergne1,4 , Liadh Kelly5 , Lorraine Goeuriot6 Gr´egoire R DocID: 1v2k0 - View Document
	Handling uncertainty in information extraction Maurice van Keulen1 and Mena B. Habib1 University of Twente, Faculty of EEMCS, Enschede, The Netherlands {m.vankeulen,m.badiehhabibmorgan}@utwente.nl Abstract. This positio DocID: 1uYrq - View Document