RSS-Feed http://example.com en-gb TYPO3 News Mon, 23 Jul 2018 00:28:08 +0000 Mon, 23 Jul 2018 00:28:08 +0000 TYPO3 EXT:news 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 Research - Data Analytics Publications
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
news-2108 Mon, 07 May 2018 06:56:32 +0000 Roche Hypo University Challenge won by DWS-AI https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/roche-hypo-university-challenge-won-by-dws-ai/ We are happy to announce that Jakob Huber and Timo Sztyler reached the 1st place in the Hypo University Challenge that was hosted by Roche Diabetes Care GmbH and powered by IBM. The goal of the challenge was to develop an algorithm that predicts the probability for a nocturnal hypoglycemic event (severe, mild, hypo) in the upcoming 10, 20, 30, 40, and 60 minutes.

 

Today, more than 425 million people have Diabetes Mellitus, a metabolic disorder characterized by an increased blood sugar level. Keeping this untreated can lead to a hyperglycemia which results in confusion, abdominal pain, and coma. The treatment of diabetes lasts as long as life, i.e., there is no cure.

 

After the challenge, they were invited to present their solution approach as part of the Roche internal "Diagnostics R&D Fair" in Basel where they also received a trophy for winning the challenge.

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Research
news-2098 Tue, 17 Apr 2018 09:27:36 +0000 Paper accepted at IJCAI 2018 https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/paper-accepted-at-ijcai-2018/ Together with our colleagues Paola, Irene and Stefano at Sapienza University in Rome we have a paper accepted at the 27th International Joint Conference on Artificial Intelligence (IJCAI), the premier conference in the field of AI:

  • Stefano Faralli, Irene Finocchi, Simone Paolo Ponzetto and Paola Velardi: Efficient Pruning of Large Knowledge Graphs.
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Publications Simone Research
news-2097 Tue, 17 Apr 2018 09:24:14 +0000 Paper accepted at JCDL 2018 https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/paper-accepted-at-jcdl-2018/ We have a paper accepted at the 2018 Joint Conference on Digital Libraries (JCDL), the top conference in the field of digital libraries

  • Federico Nanni, Simone Paolo Ponzetto and Laura Dietz: Entity-Aspect Linking:  Providing Fine-Grained Semantics of Entities in Context.

The work presented in the paper is a collaboration between the DWS group and Prof. Laura Dietz at the University of New Hampshire in the context of an Elite Post-Doc grant of the Baden-Württemberg Stiftung recently awarded from Laura.

 

 

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Research Publications Simone
news-2096 Tue, 17 Apr 2018 09:08:19 +0000 Paper accepted at SIGIR 2018 https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/paper-accepted-at-sigir-2018/ Together with our colleague Ivan Vulic at the University of Cambridge we have a paper accepted at the 41st International ACM Conference on Research and Development in Information Retrieval (SIGIR), the premier conference in the field of Information Retrieval:

  • Robert Litschko, Goran Glavas, Ivan Vulic and Simone Paolo Ponzetto: Unsupervised Cross-Lingual Information Retrieval using Monolingual Data Only.
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Research Publications Simone
news-2084 Mon, 12 Mar 2018 11:57:47 +0000 Third Cohort of Students starts Part-time Master in Data Science https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/third-cohort-of-students-starts-part-time-master-in-data-science/ The third cohort consisting of 32 students has started their studies in the part-time master program in Data Science that professors of the DWS group offer together with the Hochschule Albstadt-Sigmaringen.

This weekend the students of the third cohort of the master program as well as students participating in the certificate program Data Science were in Mannheim for a data mining project weekend.

The students worked in teams on two case studies, one in the area of online marketing, the other in the area of text mining. The teams were coached by Prof. Christian Bizer, Dr. Robert Meusel, and Alexander Diete and we were very happy to see an exciting competition between the teams for the best F1 scores as well as the highest raises in sales.

Additional Information:

 

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Projects Chris
news-2075 Fri, 23 Feb 2018 14:41:28 +0000 Dmitry Ustalov has defended his PhD thesis https://dws.informatik.uni-mannheim.deen/news/singleview/detail/News/dmitry-ustalov-has-defended-his-phd-thesis/ Dmitry Ustalov has successfully defended his Kandidat Nauk (PhD) thesis on “Models, Methods and Algorithms for Constructing a Word Sense Network for Natural Language Processing” («Модели, методы и алгоритмы построения семантической сети слов для задач обработки естественного языка» in Russian). The defense was held at the South Ural State University (Chelyabinsk, Russia) on February 21, 2018. This thesis, among many other contributions, proposes the Watset and Watlink methods for extracting, inducing, clustering, and linking the word senses from the unstructured data.

Abstract

The goal of the thesis is to develop models, methods, and algorithms for constructing a semantic network that establishes semantic relationships between individual word senses using the weakly structured dictionaries; as well as to implement them as the software system for word sense network construction. Therefore, Part I reviews the state-of-the-art in the field of natural language processing and urges the development of new efficient ontology induction algorithms for under-resourced languages.

Part II proposes two new algorithms, Watset and Watlink, that extract and structure the knowledge available in unstructured form. Watset is a meta-algorithm for fuzzy graph clustering. This algorithm creates an intermediate representation of the input graph that naturally reflects the “ambiguity” of its nodes. Then, it uses hard clustering to discover clusters in this intermediate graph. This makes it possible to discover synsets in a synonymy graph. Watlink is an algorithm for discovering the disambiguated hierarchical links between individual word senses. This algorithm uses the synsets obtained using Watset to contextualize the input asymmetric word relationships. To increase the recall of the linking, it optionally uses a regularized projection learning approach to predict additional relevant relationships.

Part III describes the implementation of the proposed models, methods, and algorithms as a software system. The system is implemented in Python, AWK, and Bash programming languages using the scikit-learn, TensorFlow, NetworkX, and Raptor libraries. Also, it defines the representation of the produced word sense network as Linked Data.

Part IV reports the results of the experiments conducted on the Russian language, an under-resourced natural language. Both Watset and Watlink show state-of-the-art performance on the synset induction and hypernymy detection tasks on the RuWordNet and Yet Another RussNet gold standards.

The dissertation in Russian is available on ZENODO via doi:10.5281/zenodo.1161515.

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Research Group