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Building the Dresden Web Table Corpus: A Classification Approach
TLDR
In recent years, researchers have recognized relational tables on the Web as an important source of information. Expand
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The State of Open Data Limits of Current Open Data Platforms
Following the Open Data trend, governments and public agencies have started making their data available to the public using web portals, web services or REST interfaces. Ideally, making this dataExpand
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Towards a Hybrid Imputation Approach Using Web Tables
TLDR
We propose a novel hybrid data imputation strategy that takes into account the characteristics of an incomplete dataset and based on that chooses the best imputation approach, i.e. either a statistical approach such as regression analysis or a Web-based lookup. Expand
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DeExcelerator: a framework for extracting relational data from partially structured documents
TLDR
We present the DeExcelerator, which is a framework for extracting relations from partially structured documents such as spreadsheets and HTML tables. Expand
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Partition-based workload scheduling in living data warehouse environments
TLDR
We present the concept of Workload Balancing by Election (WINE), which allows users to express their individual demands on the Quality of Service and Quality of Data respectively. Expand
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A Machine Learning Approach for Layout Inference in Spreadsheets
TLDR
In this paper, we propose a classification approach to discover the layout of tables in spreadsheets. Expand
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Table Recognition in Spreadsheets via a Graph Representation
TLDR
We propose Remove and Conquer (RAC), an algorithm for table recognition that implements a list of carefully curated rules for recognizing tables in spreadsheets. Expand
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From Web Tables to Concepts: A Semantic Normalization Approach
TLDR
We propose a normalization approach to decompose multi-concept Web tables into smaller single-concept tables and use the table schema to identify semantic concepts. Expand
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OPEN—Enabling Non-expert Users to Extract, Integrate, and Analyze Open Data
TLDR
In this article, we propose OPEN, a novel concept for the management and situational analysis of Open Data within a single system. Expand
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