DWS Area: Web Data Mining, Research

The paper “Real-Time Smart Charging Based on Precomputed Schedules” by Oliver Frendo, Nadine Gärtner and Heiner Stuckenschmidt has been accepted by IEEE Transactions on Smart Grid (Impact Factor 7.364)

The article “Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction” by Dmitry Ustalov, Alexander Panchenko, Chris Biemann, and Simone Paolo Ponzetto has been accepted for publication at the Computational Linguistics (CL) journal by MIT Press. Abstract: We present a ...

The article „A Unified Framework for Frequent Sequence Mining with Subsequence Constraints“ by Kaustubh Beedkar, Rainer Gemulla und Wim Martens has been accepted for publication in ACM Transactions on Database Systems (TODS). Abstract: Frequent sequence mining methods often make use of constraints ...

The paper „Scalable Frequent Sequence Mining With Flexible Subsequence Constraints“ by Alexander Renz-Wieland, Matthias Bertsch, and Rainer Gemulla has been accepted at the 2019 IEEE International Conference on Data Engineering (ICDE). Abstract: We study scalable algorithms for frequent sequence ...

The DWS group is happy to announce the new release of the WebDataCommons Microdata, JSON-LD, RDFa and Microformat data corpus. The data has been extracted from the November 2018 version of the Common Crawl covering 2.5 billion HTML pages which originate from 32 million websites (pay-level domains).

The research focus in the field of entity resolution (aka link discovery or duplicate detection) is moving from traditional symbolic matching methods to embeddings and deep neural network based matching. A problem with evaluating deep learning based matchers is that they are rather training data ...

Our systems and applications paper Extending Cross-Domain Knowledge Bases with Long Tail Entities using Web Table Data (Yaser Oulabi, Christian Bizer) got accepted at the 22nd International Conference on Extending Database Technology (EDBT 2019), one of the top-tier conferences in the data ...

We are happy to announce the release of Version 1.3 of the Web Data Integration Framework (WInte.r). WInte.r is a Java framework for end-to-end data integration. The framework implements a wide variety of different methods for data pre-processing, schema matching, identity resolution, data fusion, ...

André Melo has defended his PhD thesis on “Automatic Refinement of Large-Scale Cross-Domain Knowledge Graphs”, supervised by Prof. Heiko Paulheim. In his thesis, André has developed different methods to improve large-scale, cross-domain knowledge graphs along various dimensions. His contributions ...

The Data and Web Science Group is hosting the Data Science Conference LWDA 2018 in Mannheim on August 22–24, 2018. LWDA, which expands to „Lernen, Wissen, Daten, Analysen“ („Learning, Knowledge, Data, Analytics“), covers recent research in areas such as knowledge discovery, machine learning & data ...