Publikationen

2017

  • K. Eichler, F. Xu, H. Uszkoreit, and S. Krause, „Generating Pattern-Based Entailment Graphs for Relation Extraction,“ in Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017), Vancouver, Canada, 2017, pp. 220-229.
    [BibTeX] [Abstract] [Download PDF]

    Relation extraction is the task of recognizing and extracting relations between entities or concepts in texts. A common approach is to exploit existing knowledge to learn linguistic patterns expressing the target relation and use these patterns for extracting new relation mentions. Deriving relation patterns automatically usually results in large numbers of candidates, which need to be filtered to derive a subset of patterns that reliably extract correct relation mentions. We address the pattern selection task by exploiting the knowledge represented by entailment graphs, which capture semantic relationships holding among the learned pattern candidates. This is motivated by the fact that a pattern may not express the target relation explicitly, but still be useful for extracting instances for which the relation holds, because its meaning entails the meaning of the target relation. We evaluate the usage of both automatically generated and gold-standard entailment graphs in a relation extraction scenario and present favorable experimental results, exhibiting the benefits of structuring and selecting patterns based on entailment graphs.

    @InProceedings{eichler-EtAl:2017:starSEM,
    author = {Eichler, Kathrin and Xu, Feiyu and Uszkoreit, Hans and Krause, Sebastian},
    title = {Generating Pattern-Based Entailment Graphs for Relation Extraction},
    booktitle = {Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)},
    month = {August},
    year = {2017},
    address = {Vancouver, Canada},
    publisher = {Association for Computational Linguistics},
    pages = {220--229},
    abstract = {Relation extraction is the task of recognizing and extracting relations between
    entities or concepts in texts. A common approach is to exploit existing
    knowledge to learn linguistic patterns expressing the target relation and use
    these patterns for extracting new relation mentions. Deriving relation patterns
    automatically usually results in large numbers of candidates, which need to be
    filtered to derive a subset of patterns that reliably extract correct relation
    mentions. We address the pattern selection task by exploiting the knowledge
    represented by entailment graphs, which capture semantic relationships holding
    among the learned pattern candidates. This is motivated by the fact that a
    pattern may not express the target relation explicitly, but still be useful for
    extracting instances for which the relation holds, because its meaning entails
    the meaning of the target relation. We evaluate the usage of both automatically
    generated and gold-standard entailment graphs in a relation extraction scenario
    and present favorable experimental results, exhibiting the benefits of
    structuring and selecting patterns based on entailment graphs.},
    url = {http://www.aclweb.org/anthology/S17-1026}
    }

  • S. Karn and H. Schütze, „End-to-End Trainable Attentive Decoder for Hierarchical Entity Typing,“ in Proceedings of the 2017 Conference of the European Chapter of the Association for Computational Linguistics (EACL, Short Paper), Valencia, Spain, 2017.
    [BibTeX]
    @InProceedings{karn_typing_2017,
    author = {Karn, Sanjeev and Schütze, Hinrich},
    title = {End-to-End Trainable Attentive Decoder for Hierarchical Entity Typing},
    year = {2017},
    booktitle = {Proceedings of the 2017 Conference of the European Chapter of the Association for Computational Linguistics (EACL, Short Paper)},
    address = {Valencia, Spain}
    }

  • T. Rohrmann, S. Schelter, T. Rabl, and V. Markl, „Gilbert: Declarative Sparse Linear Algebra on Massively Parallel Dataflow Systems,“ in Proceedings of BTW 2017 (Datenbanksysteme für Business, Technologie und Web), Stuttgart, Germany, 2017.
    [BibTeX]
    @InProceedings{rohrmann:2017,
    author = {Rohrmann, Till and Schelter, Sebastian and Rabl, Tilmann and Markl, Volker},
    title = {Gilbert: Declarative Sparse Linear Algebra on Massively Parallel Dataflow Systems},
    booktitle = {Proceedings of BTW 2017 (Datenbanksysteme für Business, Technologie und Web)},
    year = {2017},
    address = {Stuttgart, Germany}
    }

  • R. Schwarzenberg, L. Hennig, and H. Hemsen, „In-Memory Distributed Training of Linear-Chain Conditional Random Fields, with an Application to Fine-Grained Named Entity Recognition,“ in Proceedings of the International Conference of the German Society for Computational Linguistics and Language Technology, Berlin, Germany, 2017.
    [BibTeX] [Download PDF]
    @InProceedings{schwarzenberg2017,
    author = {Schwarzenberg, Robert and Hennig, Leonhard and Hemsen, Holmer},
    title = {In-Memory Distributed Training of Linear-Chain Conditional Random Fields, with an Application to Fine-Grained Named Entity Recognition},
    booktitle = {Proceedings of the International Conference of the German Society for Computational Linguistics and Language Technology},
    month = {September},
    year = {2017},
    address = {Berlin, Germany},
    _publisher = {German Society for Computational Linguistics and Language Technology},
    _pages = {},
    url = {http://www.dfki.de/lt/publication_show.php?id=9105}
    }

  • P. Thomas and L. Hennig, „Twitter Geolocation Prediction using Neural Networks,“ in Proceedings of the International Conference of the German Society for Computational Linguistics and Language Technology, Berlin, Germany, 2017.
    [BibTeX] [Download PDF]
    @InProceedings{thomas2017b,
    author = {Thomas, Philippe and Hennig, Leonhard},
    title = {Twitter Geolocation Prediction using Neural Networks},
    booktitle = {Proceedings of the International Conference of the German Society for Computational Linguistics and Language Technology},
    month = {September},
    year = {2017},
    address = {Berlin, Germany},
    _publisher = {German Society for Computational Linguistics and Language Technology},
    _pages = {},
    url = {http://www.dfki.de/lt/publication_show.php?id=9106}
    }

  • P. Thomas, J. Kirschnick, L. Hennig, R. Ai, S. Schmeier, H. Hemsen, F. Xu, and H. Uszkoreit, „Streaming Text Analytics for Real-time Event Recognition,“ in Proceedings of the International Conference Recent Advances in Natural Language Processing, Varna, Bulgaria, 2017.
    [BibTeX] [Download PDF]
    @InProceedings{thomas2017a,
    author = {Thomas, Philippe and Kirschnick, Johannes and Hennig, Leonhard and Ai, Renlong and Schmeier,Sven and Hemsen, Holmer and Xu, Feiyu and Uszkoreit, Hans},
    title = {Streaming Text Analytics for Real-time Event Recognition},
    booktitle = {Proceedings of the International Conference Recent Advances in Natural Language Processing},
    month = {September},
    year = {2017},
    address = {Varna, Bulgaria},
    _publisher = {},
    _pages = {},
    url = {http://www.dfki.de/lt/publication_show.php?id=9107}
    }

2016

  • S. Arnold, F. A. Gers, T. Kilias, and A. Löser, „Robust Named Entity Recognition in Idiosyncratic Domains,“ CoRR, vol. abs/1608.06757, 2016.
    [BibTeX] [Download PDF]
    @article{DBLP:journals/corr/ArnoldGKL16,
    author = {Sebastian Arnold and
    Felix A. Gers and
    Torsten Kilias and
    Alexander L{\"{o}}ser},
    title = {Robust Named Entity Recognition in Idiosyncratic Domains},
    journal = {CoRR},
    volume = {abs/1608.06757},
    year = {2016},
    url = {http://arxiv.org/abs/1608.06757},
    timestamp = {Fri, 02 Sep 2016 17:46:24 +0200},
    biburl = {http://dblp.uni-trier.de/rec/bib/journals/corr/ArnoldGKL16},
    bibsource = {dblp computer science bibliography, http://dblp.org}
    }

  • S. Arnold, R. Dziuba, and A. Löser, „TASTY: Interactive Entity Linking As-You-Type,“ in Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations, Osaka, Japan, 2016, pp. 111-115.
    [BibTeX] [Download PDF]
    @InProceedings{arnold-dziuba-loser:2016:COLINGDEMO,
    author = {Arnold, Sebastian and Dziuba, Robert and L\"{o}ser, Alexander},
    title = {TASTY: Interactive Entity Linking As-You-Type},
    booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations},
    month = {December},
    year = {2016},
    address = {Osaka, Japan},
    publisher = {The COLING 2016 Organizing Committee},
    pages = {111--115},
    url = {http://aclweb.org/anthology/C16-2024}
    }

  • C. Baron Neto, K. Müller, M. Brümmer, D. Kontokostas, and S. Hellmann, „LODVader: An Interface to LOD Visualization, Analyticsand DiscovERy in Real-time,“ in Proceedings of the 25th International Conference Companion on World Wide Web, Republic and Canton of Geneva, Switzerland, 2016, pp. 163-166. doi:10.1145/2872518.2890545
    [BibTeX] [Download PDF]
    @inproceedings{BaronNeto:2016:LIL:2872518.2890545,
    author = {Baron Neto, Ciro and M\"{u}ller, Kay and Br\"{u}mmer, Martin and Kontokostas, Dimitris and Hellmann, Sebastian},
    title = {LODVader: An Interface to LOD Visualization, Analyticsand DiscovERy in Real-time},
    booktitle = {Proceedings of the 25th International Conference Companion on World Wide Web},
    series = {WWW '16 Companion},
    year = {2016},
    isbn = {978-1-4503-4144-8},
    location = {Montr\&\#233;al, Qu\&\#233;bec, Canada},
    pages = {163--166},
    numpages = {4},
    url = {https://doi.org/10.1145/2872518.2890545},
    doi = {10.1145/2872518.2890545},
    acmid = {2890545},
    publisher = {International World Wide Web Conferences Steering Committee},
    address = {Republic and Canton of Geneva, Switzerland},
    keywords = {bloom filter, linked open data, linksets, rdf diagram},
    }

  • M. Brümmer, M. Dojchinovski, and S. Hellmann, „DBpedia Abstracts: A Large-Scale, Open, Multilingual NLP Training Corpus,“ in Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016), Paris, France, 2016.
    [BibTeX] [Download PDF]
    @inproceedings{BRMMER16.895,
    added-at = {2017-03-08T16:37:20.000+0100},
    address = {Paris, France},
    author = {Br{\"u}mmer, Martin and Dojchinovski, Milan and Hellmann, Sebastian},
    biburl = {https://www.bibsonomy.org/bibtex/2d73fd2e5802d5bcf946c73897d54783f/aksw},
    booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
    editor = {Chair), Nicoletta Calzolari (Conference and Choukri, Khalid and Declerck, Thierry and Grobelnik, Marko and Maegaard, Bente and Mariani, Joseph and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios},
    interhash = {8efa6a388422eb1170a1abc89f43f2b6},
    intrahash = {d73fd2e5802d5bcf946c73897d54783f},
    keywords = {bruemmer dojchinovski freme group_aksw hellmann kilt},
    month = may,
    publisher = {European Language Resources Association (ELRA)},
    timestamp = {2017-03-08T16:37:20.000+0100},
    title = {DBpedia Abstracts: A Large-Scale, Open, Multilingual NLP Training Corpus},
    url = {https://svn.aksw.org/papers/2016/LREC_DBpedia_Abstracts/public.pdf},
    year = 2016
    }

  • M. Dojchinovski, D. Kontokostas, R. Rößling, M. Knuth, and S. Hellmann, „DBpedia Links: The Hub of Links for the Web of Data,“ in Proceedings of the SEMANTiCS 2016 Conference (SEMANTiCS 2016), 12-15 2016.
    [BibTeX] [Download PDF]
    @inproceedings{DojchinovskiDBpediaLinks,
    added-at = {2017-03-08T16:37:25.000+0100},
    author = {Dojchinovski, Milan and Kontokostas, Dimitris and R{\"o}{\ss}ling, Robert and Knuth, Magnus and Hellmann, Sebastian},
    biburl = {http://www.bibsonomy.org/bibtex/21deda517b750eedad70dd5b10df98bf2/aksw},
    booktitle = {Proceedings of the SEMANTiCS 2016 Conference (SEMANTiCS 2016)},
    date = {12-15},
    interhash = {80c5ed7225e5860f9e301a1cbb00381b},
    intrahash = {1deda517b750eedad70dd5b10df98bf2},
    keywords = {2016 aligned-project dojchinovski freme group_aksw hellmann kilt kontokostas},
    language = {english},
    location = {Leipzig, Germany},
    month = {September},
    timestamp = {2017-03-08T16:37:25.000+0100},
    title = {DBpedia Links: The Hub of Links for the Web of Data},
    url = {https://svn.aksw.org/papers/2016/SEMANTiCS_DBpedia_Links/public.pdf},
    year = 2016
    }

  • M. Freudenberg, M. Brümmer, J. Rücknagel, R. Ulrich, T. Eckart, D. Kontokostas, and S. Hellmann, „The Metadata Ecosystem of DataID,“ in Metadata and Semantics Research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings, E. Garoufallou, I. Subirats Coll, A. Stellato, and J. Greenberg, Eds., Cham: Springer International Publishing, 2016, pp. 317-332. doi:10.1007/978-3-319-49157-8_28
    [BibTeX] [Download PDF]
    @Inbook{Freudenberg2016,
    author="Freudenberg, Markus and Br{\"u}mmer, Martin and R{\"u}cknagel, Jessika and Ulrich, Robert and Eckart, Thomas and Kontokostas, Dimitris and Hellmann, Sebastian",
    editor="Garoufallou, Emmanouel and Subirats Coll, Imma and Stellato, Armando and Greenberg, Jane",
    title="The Metadata Ecosystem of DataID",
    bookTitle="Metadata and Semantics Research: 10th International Conference, MTSR 2016, G{\"o}ttingen, Germany, November 22-25, 2016, Proceedings",
    year="2016",
    publisher="Springer International Publishing",
    address="Cham",
    pages="317--332",
    isbn="978-3-319-49157-8",
    doi="10.1007/978-3-319-49157-8_28",
    url="http://dx.doi.org/10.1007/978-3-319-49157-8_28"
    }

  • P. Gupta, H. Schütze, and B. Andrassy, „Table Filling Multi-Task Recurrent Neural Network for Joint Entity and Relation Extraction,“ in Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, Osaka, Japan, 2016, pp. 2537-2547.
    [BibTeX] [Abstract] [Download PDF]

    This paper proposes a novel context-aware joint entity and word-level relation extraction approach through semantic composition of words, introducing a Table Filling Multi-Task Recurrent Neural Network (TF-MTRNN) model that reduces the entity recognition and relation classification tasks to a table-filling problem and models their interdependencies. The proposed neural network architecture is capable of modeling multiple relation instances without knowing the corresponding relation arguments in a sentence. The experimental results show that a simple approach of piggybacking candidate entities to model the label dependencies from relations to entities improves performance. We present state-of-the-art results with improvements of 2.0% and 2.7% for entity recognition and relation classification, respectively on CoNLL04 dataset.

    @InProceedings{gupta-schutze-andrassy:2016:COLING,
    author = {Gupta, Pankaj and Sch\"{u}tze, Hinrich and Andrassy, Bernt},
    title = {Table Filling Multi-Task Recurrent Neural Network for Joint Entity and Relation Extraction},
    booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
    month = {December},
    year = {2016},
    address = {Osaka, Japan},
    publisher = {The COLING 2016 Organizing Committee},
    pages = {2537--2547},
    abstract = {This paper proposes a novel context-aware joint entity and word-level relation
    extraction approach through semantic composition of words, introducing a Table
    Filling Multi-Task Recurrent Neural Network (TF-MTRNN) model that reduces the
    entity recognition and relation classification tasks to a table-filling problem
    and models their interdependencies. The proposed neural
    network architecture is capable of modeling multiple relation instances without
    knowing the corresponding relation arguments in a sentence. The experimental
    results show that a simple approach of piggybacking candidate entities to model
    the label dependencies from relations to entities improves performance.
    We present state-of-the-art results with improvements of 2.0% and 2.7% for
    entity recognition and relation classification, respectively on CoNLL04
    dataset.},
    url = {http://aclweb.org/anthology/C16-1239}
    }

  • L. Hennig, P. Thomas, R. Ai, J. Kirschnick, H. Wang, J. Pannier, N. Zimmermann, S. Schmeier, F. Xu, J. Ostwald, and H. Uszkoreit, „Real-Time Discovery and Geospatial Visualization of Mobility and Industry Events from Large-Scale, Heterogeneous Data Streams,“ in Proceedings of ACL-2016 System Demonstrations, Berlin, Germany, 2016, pp. 37-42.
    [BibTeX] [Download PDF]
    @InProceedings{hennig-EtAl:2016:P16-4,
    author = {Hennig, Leonhard and Thomas, Philippe and Ai, Renlong and Kirschnick, Johannes and Wang, He and Pannier, Jakob and Zimmermann, Nora and Schmeier, Sven and Xu, Feiyu and Ostwald, Jan and Uszkoreit, Hans},
    title = {Real-Time Discovery and Geospatial Visualization of Mobility and Industry Events from Large-Scale, Heterogeneous Data Streams},
    booktitle = {Proceedings of ACL-2016 System Demonstrations},
    month = {August},
    year = {2016},
    address = {Berlin, Germany},
    publisher = {Association for Computational Linguistics},
    pages = {37--42},
    url = {http://www.aclweb.org/anthology/P/P16/P16-4007.pdf}
    }

  • J. Kirschnick, H. Hemsen, and V. Markl, „JEDI: Joint Entity and Relation Detection using Type Inference,“ in Proceedings of ACL-2016 System Demonstrations, Berlin, Germany, 2016, pp. 61-66.
    [BibTeX] [Download PDF]
    @InProceedings{kirschnick-hemsen-markl:2016:P16-4,
    author = {Kirschnick, Johannes and Hemsen, Holmer and Markl, Volker},
    title = {JEDI: Joint Entity and Relation Detection using Type Inference},
    booktitle = {Proceedings of ACL-2016 System Demonstrations},
    month = {August},
    year = {2016},
    address = {Berlin, Germany},
    publisher = {Association for Computational Linguistics},
    pages = {61--66},
    url = {http://www.aclweb.org/anthology/P/P16/P16-4011.pdf}
    }

  • K. Müller, C. Stadler, and R. K. Singh, „Towards Sustainable view-based Extract-Transform-Load (ETL) Fusion of Open Data,“ in Proceedings of the 3rd Workshop on Linked Data Quality co-located with ESWC 2016, 2016.
    [BibTeX]
    @InProceedings{mueller_towards_2016,
    author = {M\"{u}ller, Kay and Stadler, Claus and Singh, Ritesh Kumar},
    title = {Towards Sustainable view-based Extract-Transform-Load (ETL) Fusion of Open Data},
    booktitle = {Proceedings of the 3rd Workshop on Linked Data Quality co-located with ESWC 2016},
    year = {2016}
    }

  • C. B. Neto, D. Kontokostas, S. Hellmann, K. Müller, and M. Brümmer, „Assessing Quantity and Quality of Links Between Linked Data Datasets,“ in Proceedings of the Workshop on Linked Data on the Web co-located with the 25th International World Wide Web Conference (WWW 2016), 2016.
    [BibTeX]
    @inproceedings{baron-2016-ldow-assessing-links,
    added-at = {2017-03-08T16:37:51.000+0100},
    author = {Neto, Ciro Baron and Kontokostas, Dimitris and Hellmann, Sebastian and M{\"u}ller, Kay and Br{\"u}mmer, Martin},
    biburl = {https://www.bibsonomy.org/bibtex/206325f941b000843d843367e0277f943/aksw},
    booktitle = {Proceedings of the Workshop on Linked Data on the Web co-located with the 25th International World Wide Web Conference (WWW 2016)},
    interhash = {f49919d9c98f3a3bf7cdb463a99b52a9},
    intrahash = {06325f941b000843d843367e0277f943},
    keywords = {baron bruemmer group_aksw hellmann kilt kmueller kontokostas},
    month = apr,
    owner = {baron},
    timestamp = {2017-03-08T16:37:51.000+0100},
    title = {Assessing Quantity and Quality of Links Between Linked Data Datasets},
    year = 2016
    }

  • C. B. Neto, D. Kontokostas, G. Publio, K. Müller, S. Hellmann, and E. Moletta, „LD-LEx: Linked Dataset Link Extractor (Short Paper),“ in On the Move to Meaningful Internet Systems: OTM 2016 Conferences: Confederated International Conferences: CoopIS, C&TC, and ODBASE 2016, Rhodes, Greece, October 24-28, 2016, Proceedings, C. Debruyne, H. Panetto, R. Meersman, T. Dillon, E. Kühn, D. O’Sullivan, and C. A. Ardagna, Eds., Cham: Springer International Publishing, 2016, pp. 727-734. doi:10.1007/978-3-319-48472-3_45
    [BibTeX] [Download PDF]
    @Inbook{Neto2016,
    author="Neto, Ciro Baron and Kontokostas, Dimitris and Publio, Gustavo and M{\"u}ller, Kay and Hellmann, Sebastian and Moletta, Eduardo",
    editor="Debruyne, Christophe and Panetto, Herv{\'e} and Meersman, Robert and Dillon, Tharam and K{\"u}hn, Eva and O'Sullivan, Declan and Ardagna, Claudio Agostino",
    title="LD-LEx: Linked Dataset Link Extractor (Short Paper)",
    bookTitle="On the Move to Meaningful Internet Systems: OTM 2016 Conferences: Confederated International Conferences: CoopIS, C{\&}TC, and ODBASE 2016, Rhodes, Greece, October 24-28, 2016, Proceedings",
    year="2016",
    publisher="Springer International Publishing",
    address="Cham",
    pages="727--734",
    isbn="978-3-319-48472-3",
    doi="10.1007/978-3-319-48472-3_45",
    url="http://dx.doi.org/10.1007/978-3-319-48472-3_45"
    }

  • R. Schneider, C. Guder, T. Kilias, A. Löser, J. Graupmann, and O. Kozachuk, „Interactive Relation Extraction in Main Memory Database Systems,“ in Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations, Osaka, Japan, 2016, pp. 103-106.
    [BibTeX] [Abstract] [Download PDF]

    We present INDREX-MM, a main memory database system for interactively executing two interwoven tasks, declarative relation extraction from text and their exploitation with SQL. INDREX-MM simplifies these tasks for the user with powerful SQL extensions for gathering statistical semantics, for executing open information extraction and for integrating relation candidates with domain specific data. We demonstrate these functions on 800k documents from Reuters RCV1 with more than a billion linguistic annotations and report execution times in the order of seconds.

    @InProceedings{schneider-EtAl:2016:COLINGDEMO,
    author = {Schneider, Rudolf and Guder, Cordula and Kilias, Torsten and L\"{o}ser, Alexander and Graupmann, Jens and Kozachuk, Oleksandr},
    title = {Interactive Relation Extraction in Main Memory Database Systems},
    booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations},
    month = {December},
    year = {2016},
    address = {Osaka, Japan},
    publisher = {The COLING 2016 Organizing Committee},
    pages = {103--106},
    abstract = {We present INDREX-MM, a main memory database system for interactively executing
    two interwoven tasks, declarative relation extraction from text and their
    exploitation with SQL. INDREX-MM simplifies these tasks for the user with
    powerful SQL extensions for gathering statistical semantics, for executing open
    information extraction and for integrating relation candidates with domain
    specific data. We demonstrate these functions on 800k documents from Reuters
    RCV1 with more than a billion linguistic annotations and report execution times
    in the order of seconds.},
    url = {http://aclweb.org/anthology/C16-2022}
    }

  • N. T. Vu, H. Adel, P. Gupta, and H. Schütze, „Combining Recurrent and Convolutional Neural Networks for Relation Classification,“ in Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, San Diego, California, 2016, pp. 534-539.
    [BibTeX] [Download PDF]
    @InProceedings{vu-EtAl:2016:N16-1,
    author = {Vu, Ngoc Thang and Adel, Heike and Gupta, Pankaj and Sch\"{u}tze, Hinrich},
    title = {Combining Recurrent and Convolutional Neural Networks for Relation Classification},
    booktitle = {Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
    month = {June},
    year = {2016},
    address = {San Diego, California},
    publisher = {Association for Computational Linguistics},
    pages = {534--539},
    url = {http://www.aclweb.org/anthology/N16-1065}
    }

2015

  • S. Arnold, A. Löser, and T. Kilias, „Resolving Common Analytical Tasks in Text Databases,“ in Proceedings of the ACM Eighteenth International Workshop on Data Warehousing and OLAP, New York, NY, USA, 2015, pp. 75-84. doi:10.1145/2811222.2811224
    [BibTeX] [Download PDF]
    @inproceedings{arnold_dolap_2015,
    author = {Arnold, Sebastian and L\"{o}ser, Alexander and Kilias, Torsten},
    title = {Resolving Common Analytical Tasks in Text Databases},
    booktitle = {Proceedings of the ACM Eighteenth International Workshop on Data Warehousing and OLAP},
    series = {DOLAP '15},
    year = {2015},
    isbn = {978-1-4503-3785-4},
    location = {Melbourne, Australia},
    pages = {75--84},
    numpages = {10},
    url = {http://doi.acm.org/10.1145/2811222.2811224},
    doi = {10.1145/2811222.2811224},
    acmid = {2811224},
    publisher = {ACM},
    address = {New York, NY, USA},
    keywords = {informational search, keywords, query intent, user goals},
    }

  • L. Hennig, H. Li, S. Krause, F. Xu, and H. Uszkoreit, „A Web-based Collaborative Evaluation Tool for Automatically Learned Relation Extraction Patterns,“ in Proceedings of ACL-IJCNLP 2015 System Demonstrations, Beijing, China, 2015, pp. 43-48.
    [BibTeX] [Download PDF]
    @InProceedings{hennig_acl_2015,
    author = {Hennig, Leonhard and Li, Hong and Krause, Sebastian and Xu, Feiyu and Uszkoreit, Hans},
    title = {A Web-based Collaborative Evaluation Tool for Automatically Learned Relation Extraction Patterns},
    booktitle = {Proceedings of ACL-IJCNLP 2015 System Demonstrations},
    month = {July},
    year = {2015},
    address = {Beijing, China},
    publisher = {Association for Computational Linguistics and The Asian Federation of Natural Language Processing},
    pages = {43--48},
    url = {http://www.aclweb.org/anthology/P15-4008}
    }

  • T. Kilias, A. Löser, and P. Andritsos, „INDREX: In-database relation extraction,“ Information Systems, vol. 53, pp. 124-144, 2015. doi:http://dx.doi.org/10.1016/j.is.2014.11.006
    [BibTeX] [Download PDF]
    @article{kilias_is_2015,
    title = "INDREX: In-database relation extraction ",
    journal = "Information Systems ",
    volume = "53",
    number = "",
    pages = "124 - 144",
    year = "2015",
    issn = "0306-4379",
    doi = "http://dx.doi.org/10.1016/j.is.2014.11.006",
    url = "http://www.sciencedirect.com/science/article/pii/S0306437914001823",
    author = "Torsten Kilias and Alexander Löser and Periklis Andritsos",
    }

  • S. Krause, L. Hennig, A. Gabryszak, F. Xu, and H. Uszkoreit, „Sar-graphs: A Linked Linguistic Knowledge Resource Connecting Facts with Language,“ in Proceedings of the 4th Workshop on Linked Data in Linguistics: Resources and Applications (ACL 2015), Beijing, China, 2015, pp. 30-38.
    [BibTeX] [Download PDF]
    @InProceedings{krause_acl_2015,
    author = {Krause, Sebastian and Hennig, Leonhard and Gabryszak, Aleksandra and Xu, Feiyu and Uszkoreit, Hans},
    title = {Sar-graphs: A Linked Linguistic Knowledge Resource Connecting Facts with Language},
    booktitle = {Proceedings of the 4th Workshop on Linked Data in Linguistics: Resources and Applications (ACL 2015)},
    month = {July},
    year = {2015},
    address = {Beijing, China},
    publisher = {Association for Computational Linguistics},
    pages = {30--38},
    url = {http://www.aclweb.org/anthology/W15-4204}
    }