Focus Group: Data Analytics

(Prof. Gemulla)

As of July 2023, there is an opening for a full-time PhD position in our lab.

Our group's research focuses on systems and methods for analyzing and and learning from large datasets as well as their application in practice, including:

  • Machine learning with semi-structured/structured datadata
  • Combining unstructured and structured knowledge
  • Representation learning for multi-relational graphs
  • Efficient and scalable methods and systems for data-intensive processing

News

People

Former PhD students

Kaustubh Beedkar, Luciano del Corro, Stefan Kain, Faraz Makari Manshadi, Christina Teflioudi, Yanjie Wang

Data and Software

  • AdaPM: A fully adaptive parameter manager
  • LibKGE: A knowledge graph embedding library
  • Lapse: A parameter server with dynamic parameter allocation
  • OPIEC: An open information extraction corpus
  • MinIE: Open information extractor (spiritual successor to ClausIE)
  • DSGDpp: Various parallel algorithms for matrix factorization (including DSGD++)
  • DESQ: Frequent sequence mining with subsequence constraints
  • Rounding rank: algorithms for computing rounding-rank decompositions
  • CORE: Context-aware open relation extraction with factorization machines
  • FINET: Context-aware fine-grained named entity typing
  • Werdy: Recognition and Disambiguation of Verbs and Verb Phrases with Syntactic and Semantic Pruning
  • ClausIE: Clause-Based Open Information Extraction
  • LEMP: Fast Retrieval of Large Entries in a Matrix Product
  • LASH: Large-Scale Sequence Mining with Hierarchies
  • MG-FSM: Large-Scale Frequent Sequence Mining

Teaching

If you are interested in writing a seminar, Bachelor or Master thesis with us, please read the following guidelines.

Current semester (HWS 2023)

Previous semester (FSS 2023)

      Publications

      See also Google Scholar and DBLP.

      2023   A. Kochsiek, A. Saxena, I. Nair, R. Gemulla
      Friendly Neighbors: Contextualized Sequence-to-Sequence Link Prediction [pdf, resources]
      In Repl4NLP workshop, 2023
       A. Renz-Wieland, A. Kieslinger, R. Gericke, R. Gemulla, Z. Kaoudi, V. Markl
      Good Intentions: Adaptive Parameter Management via Intent Signaling [pdf, resources]
      In CIKM, 2023
      2022   A. Kochsiek, F. Niesel, R. Gemulla
      Start Small, Think Big: On Hyperparameter Optimization for Large-Scale Knowledge Graph Embeddings [pdf, resources]
      In ECML-PKDD, 2022
       A. Saxena, A. Kochsiek, R. Gemulla
      Sequence-to-Sequence Knowledge Graph Completion and Question Answering [pdf, , videoresources]
      In ACL, pp. 2814-2828, 2022
       A. Renz-Wieland, R. Gemulla, Z. Kaoudi, V. Markl
      NuPS: A Parameter Server for Machine Learning with Non-Uniform Parameter Access [pdf, source code]
      In SIGMOD, pp. 481–495, 2022
      2021   A. Kochsiek, R. Gemulla
      Parallel Training of Knowledge Graph Embedding Models: A Comparison of Techniques [pdf, resources]
      In PVLDB, 15(3), 2021
       A. Renz-Wieland, T. Drobisch, R. Gemulla, Z. Kaoudi, V. Markl
      Just Move It! Dynamic Parameter Allocation in Action [pdf, demo]
      In PVLDB (demo), 14(12), 2021.
      2020   A. Renz-Wieland, R. Gemulla, S. Zeuch, V. Markl
      Dynamic Parameter Allocation in Parameter Servers [pdf, source code]
      In PVLDB, 13(12), pp. 1877-1890, 2020
       S. Broscheit, K. Gashteovski, Y. Wang, Rainer Gemulla
      Can We Predict New Facts with Open Knowledge Graph Embeddings? A Benchmark for Open Link Prediction [pdf, resources]
      In ACL, 2020
       D. Ruffinelli, S. Broscheit, R. Gemulla
      You CAN Teach an Old Dog New Tricks! On Training Knowledge Graph Embeddings [pdf, video, resources, OpenReview]
      In ICLR, 2020
       S. Broscheit, D. Ruffinelli, A. Kochsiek, P. Betz, R. Gemulla
      LibKGE – A knowledge graph embedding library for reproducible research [pdf, source]
      In EMNLP (demo), 2020
       K. Gashteovski, R. Gemulla, B. Kotnis, S. Hertling, C. Meilicke
      On Aligning OpenIE Extractions with Knowledge Bases: A Case Study [pdf, slides, resources]
      In Eval4NLP, 2020
      2019   Y. Wang, D. Ruffinelli, R. Gemulla, S. Broscheit, C. Meilicke
      On Evaluating Embedding Models for Knowledge Base Completion [pdf]
      In RepL4NLP workshop, 2019
       K. Beedkar, R. Gemulla, W. Martens
      A Unified Framework for Frequent Sequence Mining with Subsequence Constraints [pdf (journal version), pdf (author version), resources]
      In TODS, 2019
       K. Gashteovski, S. Wanner, S. Hertling, S. Broscheit, R. Gemulla
      OPIEC: An Open Information Extraction Corpus [pdf, poster, resources, OpenReview]
      In AKBC, 2019
       A. Renz-Wieland, M. Bertsch, R. Gemulla
      Scalable Frequent Sequence Mining With Flexible Subsequence Constraints [pdf, poster]
      In ICDE, 2019
      Preprints
      (2019)
         
      Y. Wang, S. Broscheit, R. Gemulla
      A Relational Tucker Decomposition for Multi-Relational Link Prediction [arXiv]
      2019
      2018   C. Meilicke, M. Fink, Y. Wang, D. Ruffinelli, R. Gemulla, and H. Stuckenschmidt
      Fine-grained Evaluation of Rule- and Embedding-based Systems for Knowledge Graph Completion [pdf, resources]
      In ISWC, 2018
       J. Pfeiffer, S. Broscheit, R. Gemulla, M. Göschl
      A Neural Autoencoder Approach for Document Ranking and Query Refinement in Pharmacogenomic Information Retrieval [pdf]
      In BioNLP workshop, 2018
       S. Broscheit, R. Gemulla, M. Keuper
      Learning Distributional Token Representations from Visual Features [pdf]
      In RepL4NLP workshop, 2018
       Y. Wang, R. Gemulla, H. Li
      On Multi-Relational Link Prediction with Bilinear Models [pdf, resources]
      In AAAI, 2018
      2017   K. Gashteovski, R. Gemulla, L. del Corro
      MinIE: Minimizing Facts in Open Information Extraction [pdf, poster, resources]
      In EMNLP, pp. 2620-2630, 2017
       C. Teflioudi, R. Gemulla
      Exact and Approximate Maximum Inner Product Search with LEMP [pdf (journal version), pdf (author version), resources]
      In TODS, 42(1) Art. 5, 2017
      2016   S. Neumann, R. Gemulla, P. Miettinen
      What You Will Gain By Rounding: Theory and Algorithms for Rounding Rank [pdf, tech report, resources]
      In ICDM, pp. 380–389, 2016
       K. Beedkar, R. Gemulla
      DESQ: Frequent Sequence Mining with Subsequence Constraints [pdf, tech report, resources]
      In ICDM (short paper), pp. 793–798, 2016
      2015   L. Del Corro, A. Abujabal, R. Gemulla, G. Weikum
      FINET: Context-Aware Fine-Grained Named Entity Typing [pdf, slides, resources]
      In EMNLP, pp. 868–878, 2015
       F. Petroni, L. Del Corro, R. Gemulla
      CORE: Context-Aware Open Relation Extraction with Factorization Machines [pdf, slides, resources]
      In EMNLP, pp. 1763-1773, 2015
       K. Beedkar, K. Berberich, R. Gemulla, I. Miliaraki
      Closing the Gap: Sequence Mining at Scale [pdf (journal version), pdf (author version), resources]
      In TODS, 40(2) Art. 8, 2015
       C. Teflioudi, R. Gemulla, O. Mykytiuk
      LEMP: Fast Retrieval of Large Entries in a Matrix Product [pdf, slides, resources]
      In SIGMOD, pp. 107–122, 2015
       K. Beedkar, R. Gemulla
      LASH: Large-Scale Sequence Mining with Hierarchies [pdf, slides, source code]
      In SIGMOD, pp. 491–503, 2015
       R. Gemulla
      A Self-Portrayal of GI Junior Fellow Rainer Gemulla: Data Analysis at Scale [pdf (journal version), pdf (author version)]
      it – Information Technology 57(2), pp. 130–132 , 2015
      2014   L. Del Corro, R. Gemulla, G. Weikum
      Werdy: Recognition and Disambiguation of Verbs and Verb Phrases with Syntactic and Semantic Pruning [pdf, resources]
      In EMNLP, pp. 374–385, 2014
       P. Roy, J. Teubner, R. Gemulla
      Low-Latency Handshake Join [pdf]
      In PVLDB, 7(9), pp. 709–720, 2014
       L. Qu, Y. Zhang, R. Wang, L. Jiang, R. Gemulla, G. Weikum
      Senti-LSSVM: Sentiment-Oriented Multi-Relation Extraction with Latent Structural SVM [pdf]
      In TACL, 2, pp. 155–168, 2014
       D. Erdös, R. Gemulla, E. Terzi
      Reconstructing Graphs from Neighborhood Data [pdf (author version), pdf (journal version)]
      In TKDD, 8(4), 2014
      2013   F. Makari, C. Teflioudi, R. Gemulla, P. J. Haas, Y. Sismanis
      Shared-Memory and Shared-Nothing Stochastic Gradient Descent Algorithms for Matrix Completion [pdf (author version), pdf (journal version), source code]
      In KAIS (special issue: best papers of ICDM 2012), pp. 1–31, 2013
       F. Makari, R. Gemulla
      A Distributed Approximation Algorithm for Mixed Packing-Covering Linear Programs [pdf]
      In NIPS 2013 Biglearn workshop (poster), 2013
       F. Makari, B. Awerbuch, R. Gemulla, R. Khandekar, J. Mestre, M. Sozio
      A Distributed Algorithm for Large-Scale Generalized Matching [pdf, slides]
      The analysis of the number of binary search steps (Lemma 2) contains a bug; see our Biglearn paper for a corrected version.
      In PVLDB, 6(9), pp. 613–624, 2013
       I. Miliaraki, K. Berberich, R. Gemulla, S. Zoupanos
      Mind the Gap: Large-Scale Frequent Sequence Mining [pdf, slides, resources]
      In SIGMOD, pp. 797–808, 2013
       L. Del Corro, R. Gemulla
      ClausIE: Clause-Based Open Information Extraction [pdf, slides, resources]
      In WWW, pp. 355–366, 2013
       R. Gemulla, P. J. Haas, W. Lehner
      Non-Uniformity Issues and Workarounds in Bounded-Size Sampling [pdf (author version), pdf (journal version), source code]
      In The VLDB Journal, 22(6), pp. 753–772, 2013
       K. Beedkar, L. Del Corro, R. Gemulla
      Fully Parallel Inference in Markov Logic Networks [pdf]
      In BTW, pp. 205–224, 2013
      2012   D. Erdös, R. Gemulla, E. Terzi
      Reconstructing Graphs from Neighborhood Data [pdf, slides]
      In ICDM, pp. 231–240, 2012
       C. Teflioudi, F. Makari, R. Gemulla
      Distributed Matrix Completion [pdf, slides, source code]
      In ICDM, pp. 655–664, 2012
       L. Qu, R. Gemulla, G. Weikum
      A Weakly Supervised Model for Sentence-Level Semantic Orientation Analysis with Multiple Experts [pdf]
      In EMNLP-CoNLL, pp. 149–159, 2012
      2011   R. Gemulla, P. J. Haas, Y. Sismanis, C. Teflioudi, F. Makari
      Large-Scale Matrix Factorization with Distributed Stochastic Gradient Descent [pdf, slides, source code]
      In NIPS 2011 Biglearn workshop, 2011 (best paper award)
       R. Gemulla, E. Nijkamp, P. J. Haas, Y. Sismanis
      Large-Scale Matrix Factorization with Distributed Stochastic Gradient Descent [pdf, slides, source code]
      In KDD, pp. 69–77, 2011
       K. Beyer, V. Ercegovac, R. Gemulla, A. Balmin, M. Eltabakh, C.C. Kanne, F. Ozcan, E. Shekita
      Jaql: A Scripting Language for Large Scale Semistructured Data Analysis [pdf]
      In PVLDB (industrial track), 4(11), pp. 1272-1283, 2011
       M. Y. Eltabakh, Y. Tian, F. Özcan, R. Gemulla, A. Krettek, J. McPherson
      CoHadoop: Flexible Data Placement and Its Exploitation in Hadoop [pdf]
      In PVLDB, 4(9), pp. 575–585, 2011
       R. Gemulla, P. J. Haas, E. Nijkamp, Y. Sismanis
      Large-Scale Matrix Factorization with Distributed Stochastic Gradient Descent [pdf]
      IBM Research Report RJ10481, March 2011 Revised February, 2013
       B. Schlegel, R. Gemulla, W. Lehner
      Memory-Efficient Frequent-Itemset Mining [pdf]
      In EDBT, pp. 461–472, 2011
      2010   S. Das, Y. Sismanis, K. S. Beyer, R. Gemulla, P. J. Haas, J. McPherson.
      Ricardo: Integrating R and Hadoop [pdf]
      In SIGMOD (industrial track), pp. 987–998, 2010
       B. Schlegel, R. Gemulla, W. Lehner.
      Fast Integer Compression using SIMD Instructions [pdf]
      In DAMON, pp. 34–40, 2010
      2009   K. Beyer, R. Gemulla. P. J. Haas, B. Reinwald, Y. Sismanis.
      Distinct-Value Synopses for Multiset Operations [pdf, technical perspective by Surajit Chaudhuri]
      In Commun. ACM, 52(10), pp. 87–95, 2009
       B. Schlegel, R. Gemulla, W. Lehner.
      k-Ary Search on Modern Processors [pdf, slides]
      In DAMON, pp. 52–60, 2009
      2008   R. Gemulla.
      Sampling Algorithms for Evolving Datasets [pdf, summary, slides]
      Ph.D. thesis, Technische Universität Dresden, 2009
      URL for citations: nbn-resolving.de/urn:nbn:de:bsz:14-ds-1224861856184-11644
       R. Gemulla, P. Rösch and W. Lehner.
      Linked Bernoulli Synopses: Sampling Along Foreign Keys [pdf, slides]
      In SSDBM, pp. 6–23, 2008
       R. Gemulla and W. Lehner.
      Sampling Time-Based Sliding Windows in Bounded Space [pdf, slides]
      As observed by Hu et al., the lower bound of Ω(k log N) stated in Theorem 1 should read Ω(k log(N/k)).
      In SIGMOD, pp. 379–392, 2008
       P. Rösch, R. Gemulla and W. Lehner.
      Designing Random Sample Synopses with Outliers [pdf, poster]
      In ICDE (poster), pp. 1400-1402, 2008
      2007   R. Gemulla, W. Lehner and P.J. Haas.
      Maintaining Bounded-Size Sample Synopses of Evolving Datasets [pdf]
      The resizing algorithm proposed in this article contains a bug; see my Ph.D. thesis or our 2013 VLDB Journal paper for a corrected version.
      In The VLDB Journal, Special Issue: Best Papers of VLDB 2006, pp. 173–201, 2007
       K. Beyer, P. J. Haas, B. Reinwald, Y. Sismanis and R. Gemulla.
      On Synopses for Distinct-Value Estimation Under Multiset Operations [pdf, slides]
      In SIGMOD, pp. 199–210, 2007
       R. Gemulla, W. Lehner and P. J. Haas.
      Maintaining Bernoulli Samples over Evolving Multisets [pdf, slides]
      In PODS, pp. 93–102, 2007
      2006   R. Gemulla, W. Lehner and P. J. Haas.
      A Dip in the Reservoir: Maintaining Sample Synopses of Evolving Datasets [pdf, slides]
      In VLDB, pp. 595–606, 2006
       A. Klein, R. Gemulla, P. Rösch and W. Lehner.
      Derby/S: A DBMS for Sample-Based Query Answering [pdf, poster1, poster2]
      In SIGMOD (demo), pp. 757–759, 2006
       R. Gemulla and W. Lehner.
      Deferred Maintenance of Disk-Based Random Samples [pdf, slides]
      In EDBT, pp. 423–441, 2006