The power of declarative languages: from information extraction to machine learning
dc.contributor.author | Vaithyanathan, Shivakumar | |
dc.contributor.editor | Härder, Theo | |
dc.contributor.editor | Lehner, Wolfgang | |
dc.contributor.editor | Mitschang, Bernhard | |
dc.contributor.editor | Schöning, Harald | |
dc.contributor.editor | Schwarz, Holger | |
dc.date.accessioned | 2019-01-17T10:36:46Z | |
dc.date.available | 2019-01-17T10:36:46Z | |
dc.date.issued | 2011 | |
dc.description.abstract | As advanced analytics has become more mainstream in enterprises, usability and system-managed performance optimizations are critical for its wide adoption. As a result, there is an active interest in the design of declarative languages in several analytics areas. In this talk I will describe the efforts in IBM around three areas namely Information Extraction, Entity Resolution and Machine Learning. I will detail these efforts, at some length, and also explain the motivation behind some of the design choices made while implementing declarative solutions for the individual areas. I will end with results that demonstrate multiple advantages of the declarative approaches as compared with existing solutions. | en |
dc.identifier.isbn | 978-3-88579-274-1 | |
dc.identifier.pissn | 1617-5468 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/19597 | |
dc.language.iso | en | |
dc.publisher | Gesellschaft für Informatik e.V. | |
dc.relation.ispartof | Datenbanksysteme für Business, Technologie und Web (BTW) | |
dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-180 | |
dc.title | The power of declarative languages: from information extraction to machine learning | en |
dc.type | Text/Conference Paper | |
gi.citation.endPage | 23 | |
gi.citation.publisherPlace | Bonn | |
gi.citation.startPage | 23 | |
gi.conference.date | 02.-04.03.2011 | |
gi.conference.location | Kaiserslautern | |
gi.conference.sessiontitle | Regular Research Papers |
Dateien
Originalbündel
1 - 1 von 1