DWS Group - News http://example.com This RSS feed provides news about the research activities of the Data and Web Science Group at the University of Mannheim. en-gb TYPO3 News Tue, 16 Oct 2018 09:16:03 +0000 Tue, 16 Oct 2018 09:16:03 +0000 TYPO3 EXT:news news-2165 Mon, 08 Oct 2018 13:12:38 +0000 New Champion of the "Bohnenspiel WM" https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/new-champion-of-the-bohnenspiel-wm/ In the 2018 edition of the annual Bohnenspiel WM a new champion emerged! As integral part of the AI bachelor lecture, every year the students have the chance to participate in small groups in a tournament called the Bohnen-WM. For this tournament the students have to design and implement an AI that is capable of playing the game Bohnenspiel on a high level . This year 8 groups participated with AIs implementing different techniques and tactics. Finally, the AI of the group Selia Bati, Yves Mike Ekspenszid, and Sophia Isabel Maguin have won the cup. The winning AI was named "DieWilde9".

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Topics - Künstliche Intelligenz I Other Christian
news-2164 Thu, 04 Oct 2018 20:27:13 +0000 New DFG Project on joining graph- and vector-based sense representations for semantic end-user information access https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/new-dfg-project-on-joining-graph-and-vector-based-sense-representations-for-semantic-end-user-infor/ We are happy to announce that the Deutsche Forschungsgemeinschaft accepted our proposal for extending a joint research project on hybrid semantic representations together with our friends and colleagues of the Language Technology Group of the University of Hamburg.


The project, titled "Joining graph- and vector-based sense representations for semantic end-user information access" (JOIN-T 2) builds upon and aims at bringing our JOIN-T project (also funded funded by DFG) one step forward. Our vision for the next three years is to explore ways to produce semantic representations that combine the interpretability of manually crafted resources and sparse representations with the accuracy and high coverage of dense neural embeddings.

Stay tuned for forthcoming research papers and resources!

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Research Topics - Artificial Intelligence (NLP) Simone
news-2166 Thu, 04 Oct 2018 08:52:00 +0000 WInte.r Web Data Integration Framework Version 1.3 released https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/winter-web-data-integration-framework-version-13-released/ 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, and result evaluation. The methods are designed to be easily customizable by exchanging pre-defined building blocks, such as blockers, matching rules, similarity functions, and conflict resolution functions.

The following features have been added to the framework for the new release:

  • Value Normalization: New ValueNormaliser class for normalizing quantifiers and units of measurement. New DataSetNormaliser class for detecting data types and transform complete datasets into a normalised base format.
  • External Rule Learning: In addition to learning matching rules directly inside of WInte.r, the new release also supports learning matching rules using external tools such as Rapidminer and importing the learned rules back into WInte.r.
  • Debug Reporting: The new release features detailed reports about the application of matching rules, blockers, and data fusion methods which lay the foundation for fine-tuning the methods.
  • Step-by-Step Tutorial: In order to get users started with the framework, we have written a step-by-step tutorial on how to use WInte.r for identity resolution and data fusion and how to debug and fine-tune the different steps of the integration process.

The WInte.r famework forms a foundation for our research on large-scale web data integration. The framework is used by the T2K Match algorithm for matching millions of Web tables against a central knowledge base, as well as within our work on Web table stitching for improving matching quality. The framework is also used in the context of the DS4DM research project for matching tabular data for data search.

Beside of being used for research, we also use the WInte.r famework for teaching. The students of our Web Data Integration course use the framework to solve case studies and implement their term projects.  

Detailed information about the WInte.r framework is found at

https://github.com/olehmberg/winter

The WInte.r framework can be downloaded from the same web site. The framework can be used under the terms of the Apache 2.0 License.

Lots of thanks to Alexander Brinkmann and Oliver Lehmberg for their work on the new release as well as on the tutorial and extended documentation in the WInte.r wiki.

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Research - Web-based Systems Chris Projects
news-2151 Tue, 28 Aug 2018 12:34:04 +0000 Paper accepted at EMNLP 2018 https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/paper-accepted-at-emnlp-2018/ Our long paper submission

"Investigating the Role of Argumentation in the Rhetorical Analysis of Scientific Publications with Neural Multi-Task Learning Models " (Anne Lauscher, Goran Glavaš, Kai Eckert, and Simone Paolo Ponzetto)

got accepted at the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018), one of the top-tier conferences in natural language processing!

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Simone Publications Kai Topics - Artificial Intelligence (NLP) Research - Data Analytics
news-2150 Fri, 24 Aug 2018 14:27:52 +0000 André Melo has defended his PhD thesis https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/andre-melo-has-defended-his-phd-thesis/ 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 include, among others, a benchmarking suite for knowledge graph completion and correction, an effective method for type prediction using hierarchical classification, and a machine-learning based method for detection wrong relation assertions. Moreover, he has proposed methods for error correction in knowledge graph, and for distilling high-level tests from individual errors identified.

As of September, André will start a new job as a knowledge engineer for Babylon Health in London. We wish him all the best!

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Group Research
news-2105 Fri, 10 Aug 2018 09:58:00 +0000 Data Science Conference LWDA 2018 in Mannheim https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/data-science-conference-lwda-2018-in-mannheim-1/ 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 mining, knowledge management, database management & information systems, information retrieval. 

The LWDA conference is organized by and brings together the various special interest groups of the Gesellschaft für Informatik (German Computer Science Society) in this area. The program comprises of joint research sessions and keynotes as well as of workshops organized by each special interest group.

Further information can be found on the conference website: https://www.uni-mannheim.de/lwda-2018/.

Download the conference poster.

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Other Topics - Künstliche Intelligenz I Topics - Data Mining Topics - Decision Support Topics - Web Search and IR Chris Heiner Rainer Simone
news-2131 Wed, 11 Jul 2018 16:36:52 +0000 Paper accepted at ISWC 2018: Fine-grained Evaluation of Rule- and Embedding-based Systems for Knowledge Graph Completion https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/paper-accepted-at-iswc-2018-fine-grained-evaluation-of-rule-and-embedding-based-systems-for-knowle/ The paper "Fine-grained Evaluation of Rule- and Embedding-based Systems for Knowledge Graph Completion" by Christian Meilicke, Manuel Fink, Yanjie Wang, Daniel Ruffinelli, Rainer Gemulla, and Heiner Stuckenschmidt has been accepted at the 2018 International Semantic Web Conference (ISWC).

Abstract:
Over the recent years, embedding methods have attracted increasing focus as a means for knowledge graph completion. Similarly, rule-based systems have been studied for this task in the past. What is missing so far is a common evaluation that includes more than one type of method. We close this gap by comparing representatives of both types of systems in a frequently used evaluation protocol. Leveraging the explanatory qualities of rule-based systems, we present a fine-grained evaluation that gives insight into characteristics of the most popular datasets and points out the different strengths and shortcomings of the examined approaches. Our results show that models such as TransE, RESCAL or HolE have problems in solving certain types of completion tasks that can be solved by a rule-based approach with high precision. At the same time, there are other completion tasks that are difficult for rule-based systems. Motivated by these insights, we combine both families of approaches via ensemble learning. The results support our assumption that the two methods complement each other in a beneficial way.

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Publications Rainer
news-2124 Wed, 27 Jun 2018 06:03:30 +0000 Mannheim Students Score Second Place at Data Mining Cup https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/mannheim-students-score-second-place-at-data-mining-cup/ The Data Mining Cup is an annual data mining competition for students from all over the world. Since 2014, students from Mannheim take part in the competition as an integral part of the Data Mining 2 lecture, held by Prof. Paulheim. In the course of the competition, the students have to solve a data mining task based on real e-commerce data.

This year, the data was provided by an online sports apparel retailer, and the task was to predict the sellout date for individual articles. Students had six weeks time to develop their solution. In the course of the lecture, they worked in different teams and had regular discussions about solution approaches and results.

One of the student teams from Mannheim qualified for the final round of the 10 best teams in May and was invited to present their solution Berlin at the prudsys personalization & pricing summit. In the final ranking, they scored second out of 197 solutions in total. Overall, teams from 148 universities from 47 countries took part in the 2018 data mining cup.

The DWS group wants to congratulate the winning team:

  • Nele Ecker
  • Thilo Habrich
  • Andreea Iana
  • Adrian Kochsiek
  • Alexander Luetke
  • Laurien Theresa Lummer
  • Nils Richter
  • Fabian Oliver Schmitt

Picture: Members of the winnig team in Berlin. Left to right: Nele Ecker, Laurien Lummer, Adrian Kochsiek, Alexander Lütke
Picture credits: Data Mining Cup/prudsys AG

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Group Research
news-2123 Fri, 22 Jun 2018 09:35:32 +0000 JCDL 2018 - Vannevar Bush Best Paper Award https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/jcdl-2018-vannevar-bush-best-paper-award/ Our paper "Entity-Aspect Linking: Providing Fine-Grained Semantics of Entities in Context" has recently won the Vannevar Bush best paper award at the 2018 Joint Conference on Digital Libraries (JCDL), the top conference in the field of digital libraries!

The work, coauthored by Federico Nanni, Simone Paolo Ponzetto and Laura Dietz, is part of a collaboration between the DWS group and the University of New Hampshire in the context of an Elite Post-Doc grant of the Baden-Württemberg Stiftung recently awarded from Laura.

Congratulations also to Myriam Traub, Thaer Samar, Jacco van Ossenbruggen and Lynda Hardman, who, with their work, share with us the 2018 best paper award!

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Simone Publications Research
news-2119 Mon, 11 Jun 2018 13:23:27 +0000 Papers accepted at ACL 2018 https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/papers-accepted-at-acl-2018/ We have three papers to be presented at the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018), the premier international conference on Computational Linguistics and Natural Language Processing.

Two short papers prepared in collaboration with our colleagues from the University of Cambridge, the University of Hamburg and the University of Oslo have been accepted at the main conference track:

One paper has been accepted at the 3rd Workshop on Representation Learning for NLP (RepL4NLP) hosted by ACL 2018:

  • Samuel Broscheit: Learning Distributional Token Representations from Visual Features.
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Research Publications Simone