Erhard Rahm

ATOM: Automatic target-driven ontology merging

by Erhard Rahm and Salvatore Raunich

2011 IEEE 27th International Conference on Data Engineering, 2011

Reinforcement learning architecture for Web recommendations

by Erhard Rahm and Nick Golovin

International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004., 2004

Page 1. Reinforcement Learning Architecture for Web Recommendations Nick Golovin, Erhard Rahm Uni... more

A Multidimensional Data Warehouse for Gene Expression Analysis

German Conference on Bioinformatics, 2003

We introduce the GeWare data warehouse approach for microarray-based gene expression analysis. Ge... more

A Data Warehouse for Multidimensional Gene Expression Analysis

Abstract We introduce the GeWare data warehouse system for microarray-based gene expression analy... more

Instance-based matching of hierarchical ontologies

Datenbanksysteme in Büro, Technik und Wissenschaft(German Database Conference), 2007

We study an instance-based approach for matching hierarchical ontolo- gies, such as product catal... more We study an instance-based approach for matching hierarchical ontolo- gies, such as product catalogs. The motivation for utilizing instances is that meta- data-based match approaches often suffer from semantic heterogeneity, e.g. am- biguous concept names, different concept granularities or incomparable categori- zations. Our instance-based match approach matches categories based on the in- stances (e.g. products) assigned to them. This way

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Comparative Evaluation of Microarray-based Gene Expression Databases

Datenbanksysteme in Büro, Technik und Wissenschaft(German Database Conference), 2003

Microarrays make it possible to monitor the expression of thousands of genes in parallel thus gen... more Microarrays make it possible to monitor the expression of thousands of genes in parallel thus generating huge amounts of data. So far, several databases have been developed for managing and analyzing this kind of data but the current state of the art in this field is still early stage. In this paper, we comprehensively analyze the requirements for microarray data

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Analyzing the Evolution of Life Science Ontologies and Mappings

Lecture Notes in Computer Science, 2008

Ontologies are heavily developed and used in life sciences and undergo continuous changes. Howeve... more Ontologies are heavily developed and used in life sciences and undergo continuous changes. However, the evolution of life science ontologies and references to them (e.g., annotations) is not well understood and has received little attention so far. We therefore propose a generic framework for analyzing both the evolution of ontologies and the evolution of ontology-related mappings, in particular annotations referring to ontologies and similarity (match) mappings between ontologies. We use our framework for an extensive comparative evaluation of evolution measures for 16 life science ontologies. Moreover, we analyze the evolution of annotation mappings and ontology mappings for the Gene Ontology.

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Efficient Management of Biomedical Ontology Versions

Lecture Notes in Computer Science, 2009

Ontologies have become very popular in life sciences and other domains. They mostly undergo conti... more Ontologies have become very popular in life sciences and other domains. They mostly undergo continuous changes and new ontology versions are frequently released. However, current analysis studies do not consider the ontology changes reflected in different versions but typically limit themselves to a specific ontology version which may quickly become obsolete. To allow applications easy access to different ontology versions we propose a central and uniform management of the versions of different biomedical ontologies. The proposed database approach takes concept and structural changes of succeeding ontology versions into account thereby supporting different kinds of change analysis. Furthermore, it is very space-efficient by avoiding redundant storage of ontology components which remain unchanged in different versions. We evaluate the storage requirements and query performance of the proposed approach for the Gene Ontology.

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Estimating the Quality of Ontology-Based Annotations by Considering Evolutionary Changes

Lecture Notes in Computer Science, 2009

Ontology-based annotations associate objects, such as genes and proteins, with well-defined ontol... more Ontology-based annotations associate objects, such as genes and proteins, with well-defined ontology concepts to semantically and uniformly describe object properties. Such annotation mappings are utilized in different applications and analysis studies whose results strongly depend on the quality of the used annotations. To study the quality of annotations we propose a generic evaluation approach considering the annotation generation methods (provenance) as well as the evolution of ontologies, object sources, and annotations. Thus, it facilitates the identification of reliable annotations, e.g., for use in analysis applications. We evaluate our approach for functional protein annotations in Ensembl and Swiss-Prot using the Gene Ontology.

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Comparative evaluation of entity resolution approaches with FEVER

Proceedings of The Vldb Endowment, 2009

We present FEVER, a new evaluation platform for entity resolu- tion approaches. The modular struc... more We present FEVER, a new evaluation platform for entity resolu- tion approaches. The modular structure of the FEVER framework supports the incorporation or reconstruction of many previously proposed approaches for entity resolution. A distinctive feature of FEVER is that it not only evaluates traditional measures such as precision and recall but also the effort for configuring (e.g., pa- rameter tuning,

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Evaluation of entity resolution approaches on real-world match problems

Proceedings of the VLDB Endowment, 2010

Despite the huge amount of recent research efforts on entity resolution (matching) there has not ... more Despite the huge amount of recent research efforts on entity resolution (matching) there has not yet been a comparative evaluation on the relative effectiveness and efficiency of alternate approaches. We therefore present such an evaluation of existing implementations on challenging real-world match tasks. We consider approaches both with and without using machine learning to find suitable parameterization and combination of similarity functions. In addition to approaches from the research community we also consider a state-of-the-art commercial entity resolution implementation. Our results indicate significant quality and efficiency differences between different approaches. We also find that some challenging resolution tasks such as matching product entities from online shops are not sufficiently solved with conventional approaches based on the similarity of attribute values.

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CloudFuice: A Flexible Cloud-Based Data Integration System

Lecture Notes in Computer Science, 2011

The advent of cloud computing technologies shows great promise for web engineering and facilitate... more The advent of cloud computing technologies shows great promise for web engineering and facilitates the development of flexible, distributed, and scalable web applications. Data integration can notably benefit from cloud computing because integrating web data is usually an expensive task. This paper introduces CloudFuice, a data integration system that follows a mashup-like specification of advanced dataflows for data integration. CloudFuice's task-based execution approach allows for an efficient, asynchronous, and parallel execution of dataflows in the cloud and utilizes recent cloud-based web engineering instruments. We demonstrate and evaluate CloudFuice's applicability for mashup-based data integration in the cloud with the help of a first prototype implementation.

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Citation analysis of database publications

ACM SIGMOD Record, 2005

We analyze citation frequencies for two main database conferences (SIGMOD, VLDB) and three databa... more We analyze citation frequencies for two main database conferences (SIGMOD, VLDB) and three database journals (TODS, VLDB Journal, Sigmod Record) over 10 years. The citation data is obtai- ned by integrating and cleaning data from DBLP and Google Scho- lar. Our analysis considers different comparative metrics per publication venue, in particular the total and average number of ci- tations as

Database and XML Technologies, First International XML Database Symposium, XSym 2003, Berlin, Germany, September 8, 2003, Proceedings

International XML Database Symposium, 2003

... IBM (USA) Ingo Macherius, Infonyte (Germany) Susan Malaika, IBM (USA) Florent Masseglia, INRI... more

A Clustering-Based Approach for Large-Scale Ontology Matching

Lecture Notes in Computer Science, 2011

Schema and ontology matching have attracted a great deal of interest among researchers. Despite t... more Schema and ontology matching have attracted a great deal of interest among researchers. Despite the advances achieved, the large matching problem still presents a real challenge, such as it is a timeconsuming and memory-intensive process. We therefore propose a scalable, clustering-based matching approach that breaks up the large matching problem into smaller matching problems. In particular, we first introduce a structure-based clustering approach to partition each schema graph into a set of disjoint subgraphs (clusters). Then, we propose a new measure that efficiently determines similar clusters between every two sets of clusters to obtain a set of small matching tasks. Finally, we adopt the matching prototype COMA++ to solve individual matching tasks and combine their results. The experimental analysis reveals that the proposed method permits encouraging and significant improvements.

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FoodBroker - Generating Synthetic Datasets for Graph-Based Business Analytics

Lecture Notes in Computer Science, 2015

MOMA - A Mapping-based Object Matching System

Conference on Innovative Data Systems Research, 2007

Object matching or object consolidation is a crucial task for data in- tegration and data cleanin... more Object matching or object consolidation is a crucial task for data in- tegration and data cleaning. It addresses the problem of identifying object instances in data sources referring to the same real world entity. We propose a flexible framework called MOMA for map- ping-based object matching. It allows the construction of match workflows combining the results of several matcher algorithms

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Research report 2003

Analysis of parallel scan processing in Shared Disk database systems

Lecture Notes in Computer Science, 1995

Distributed optimistic concurrency control for high performance transaction processing

Proceedings. PARBASE-90: International Conference on Databases, Parallel Architectures, and Their Applications, 1990

... 2. System and transaction processing model Though our protocols are in principle applicable t... more

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