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Felix Naumann
Researcher at Hasso Plattner Institute
Publications - 271
Citations - 10336
Felix Naumann is an academic researcher from Hasso Plattner Institute. The author has contributed to research in topics: Query optimization & Data quality. The author has an hindex of 46, co-authored 248 publications receiving 9364 citations. Previous affiliations of Felix Naumann include Qatar Computing Research Institute & Humboldt State University.
Papers
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Journal ArticleDOI
Data fusion
Jens Bleiholder,Felix Naumann +1 more
TL;DR: This article places data fusion into the greater context of data integration, precisely defines the goals of data fusion, namely, complete, concise, and consistent data, and highlights the challenges of data Fusion.
Journal ArticleDOI
The Stratosphere platform for big data analytics
Alexander Alexandrov,Rico Bergmann,Stephan Ewen,Johann-Christoph Freytag,Fabian Hueske,Arvid Heise,Odej Kao,Marcus Leich,Ulf Leser,Volker Markl,Felix Naumann,Mathias Peters,Astrid Rheinländer,Matthias J. Sax,Sebastian Schelter,Mareike Hoger,Kostas Tzoumas,Daniel Warneke +17 more
TL;DR: The overall system architecture design decisions are presented, Stratosphere is introduced through example queries, and the internal workings of the system’s components that relate to extensibility, programming model, optimization, and query execution are dive into.
BookDOI
Assessment Methods for Information Quality Criteria
Felix Naumann,Claudia Rolker +1 more
TL;DR: This paper identifies three sources for IQ scores and thus, three IQ criterion classes, each with different general assessment possibilities, and gives detailed assessment methods for each, in a new, assessment-oriented way.
Book
An Introduction to Duplicate Detection
Felix Naumann,Melanie Herschel +1 more
TL;DR: This lecture examines closely the two main components to overcome the difficulties of automatically detecting duplicates: Similarity measures are used to automatically identify duplicates when comparing two records and algorithms developed to perform on very large volumes of data in search for duplicates.
Book
Quality-Driven Query Answering for Integrated Information Systems
TL;DR: This paper presents a meta-modelling framework that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of planning and executing quality-driven queries.