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ORCIDAnsgar Scherp
Person information
- affiliation: University of Ulm, Germany
- affiliation: University of Essex, Colchester, UK
- affiliation: University of Stirling, Scotland
- affiliation: Kiel University, Institute of Computer Science, Germany
- affiliation: Leibniz Information Center for Economics (ZBW), Kiel, Germany
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2020 – today
- 2024
[j39]Ansgar Scherp, Gerd Gröner, Petr Skoda, Katja Hose, Maria-Esther Vidal:
Semantic Web: Past, Present, and Future. TGDK 2(1): 3:1-3:37 (2024)- [i37]Hye Jin Kim, Nicolas Lell
, Ansgar Scherp:
Text Role Classification in Scientific Charts Using Multimodal Transformers. CoRR abs/2402.14579 (2024) - [i36]Marcel Hoffmann, Lukas Galke, Ansgar Scherp:
POWN: Prototypical Open-World Node Classification. CoRR abs/2406.09926 (2024) - [i35]Nicolas Lell, Ansgar Scherp:
HyperAggregation: Aggregating over Graph Edges with Hypernetworks. CoRR abs/2407.11596 (2024) - [i34]Jonatan Frank, Andor Diera, David Richerby, Ansgar Scherp:
Multi-View Structural Graph Summaries. CoRR abs/2407.18036 (2024) - [i33]Jonatan Frank, Marcel Hoffmann, Nicolas Lell, David Richerby, Ansgar Scherp:
Lifelong Graph Summarization with Neural Networks: 2012, 2022, and a Time Warp. CoRR abs/2407.18042 (2024) - 2023
- [j38]Yousef Younes, Ansgar Scherp:
Question Answering Versus Named Entity Recognition for Extracting Unknown Datasets. IEEE Access 11: 92775-92787 (2023) - [j37]Lukas Galke, Iacopo Vagliano, Benedikt Franke, Tobias Zielke, Marcel Hoffmann, Ansgar Scherp:
Lifelong learning on evolving graphs under the constraints of imbalanced classes and new classes. Neural Networks 164: 156-176 (2023) - [j36]Axel Polleres, Romana Pernisch, Angela Bonifati, Daniele Dell'Aglio, Daniil Dobriy, Stefania Dumbrava, Lorena Etcheverry, Nicolas Ferranti, Katja Hose, Ernesto Jiménez-Ruiz, Matteo Lissandrini, Ansgar Scherp, Riccardo Tommasini, Johannes Wachs:
How Does Knowledge Evolve in Open Knowledge Graphs? TGDK 1(1): 11:1-11:59 (2023) - [j35]Ansgar Scherp, David Richerby, Till Blume, Michael Cochez, Jannik Rau:
Structural Summarization of Semantic Graphs Using Quotients. TGDK 1(1): 12:1-12:25 (2023) - [c133]Ralf Schenkel, Ansgar Scherp:
Workshop on Data Engineering for Data Science (DE4DS). BTW 2023: 705-706 - [c132]Fabian Karl, Ansgar Scherp:
Transformers are Short-Text Classifiers. CD-MAKE 2023: 103-122 - [c131]Nicolas Lell, Ansgar Scherp:
The Split Matters: Flat Minima Methods for Improving the Performance of GNNs. CD-MAKE 2023: 200-226 - [c130]Andor Diera, Nicolas Lell, Aygul Garifullina, Ansgar Scherp:
Memorization of Named Entities in Fine-Tuned BERT Models. CD-MAKE 2023: 258-279 - [c129]Johannes Scherer, Deepayan Bhowmik, Ansgar Scherp:
Event and Entity Extraction from Generated Video Captions. CD-MAKE 2023: 280-300 - [c128]Justin Mücke, Daria Waldow, Luise Metzger, Philipp Schauz, Marcel Hoffmann, Nicolas Lell, Ansgar Scherp:
Fine-Tuning Language Models for Scientific Writing Support. CD-MAKE 2023: 301-318 - [c127]Jannik Rau, David Richerby, Ansgar Scherp:
Computing k-Bisimulations for Large Graphs: A Comparison and Efficiency Analysis. ICGT 2023: 223-242 - [c126]Marcel Hoffmann, Lukas Galke, Ansgar Scherp:
Open-World Lifelong Graph Learning. IJCNN 2023: 1-9 - [c125]Tobias Kalmbach, Marcel Hoffmann, Nicolas Lell, Ansgar Scherp:
On the Rule-Based Extraction of Statistics Reported in Scientific Papers. NLDB 2023: 326-338 - [i32]Nicolas Lell, Ansgar Scherp:
The Split Matters: Flat Minima Methods for Improving the Performance of GNNs. CoRR abs/2306.09121 (2023) - [i31]Justin Mücke, Daria Waldow, Luise Metzger, Philipp Schauz, Marcel Hoffmann, Nicolas Lell, Ansgar Scherp:
Fine-Tuning Language Models for Scientific Writing Support. CoRR abs/2306.10974 (2023) - [i30]Marcel Hoffmann, Lukas Galke, Ansgar Scherp:
Open-World Lifelong Graph Learning. CoRR abs/2310.12565 (2023) - [i29]Andor Diera, Abdelhalim Dahou, Lukas Galke, Fabian Karl, Florian Sihler, Ansgar Scherp:
GenCodeSearchNet: A Benchmark Test Suite for Evaluating Generalization in Programming Language Understanding. CoRR abs/2311.09707 (2023) - 2022
- [j34]Iacopo Vagliano, Lukas Galke, Ansgar Scherp:
Recommendations for item set completion: on the semantics of item co-occurrence with data sparsity, input size, and input modalities. Inf. Retr. J. 25(3): 269-305 (2022) - [j33]Steffen Epp, Marcel Hoffmann, Nicolas Lell, Michael Mohr, Ansgar Scherp:
Extracting Experiment Statistics, Conditions, and Topics from Scientific Papers with STEREO. J. Data Intell. 3(2): 252-277 (2022) - [c124]Lukas Galke, Ansgar Scherp:
Bag-of-Words vs. Graph vs. Sequence in Text Classification: Questioning the Necessity of Text-Graphs and the Surprising Strength of a Wide MLP. ACL (1) 2022: 4038-4051 - [c123]Maximilian Blasi, Manuel Freudenreich, Johannes Horvath, David Richerby, Ansgar Scherp:
Graph Summarization as Vertex Classification Task using Graph Neural Networks vs. Bloom Filter. DSAA 2022: 1-10 - [c122]Lukas Galke, Isabelle Cuber, Christoph Meyer, Henrik Ferdinand Nölscher, Angelina Sonderecker, Ansgar Scherp:
General Cross-Architecture Distillation of Pretrained Language Models into Matrix Embeddings. IJCNN 2022: 1-10 - [i28]Maximilian Blasi, Manuel Freudenreich, Johannes Horvath, David Richerby, Ansgar Scherp:
Graph Summarization with Graph Neural Networks. CoRR abs/2203.05919 (2022) - [i27]Andor Diera, Bao Xin Lin, Bhakti Khera, Tim Meuser, Tushar Singhal, Lukas Galke, Ansgar Scherp:
Bag-of-Words vs. Sequence vs. Graph vs. Hierarchy for Single- and Multi-Label Text Classification. CoRR abs/2204.03954 (2022) - [i26]Jannik Rau, David Richerby, Ansgar Scherp:
Single-Purpose Algorithms vs. a Generic Graph Summarizer for Computing k-Bisimulations on Large Graphs. CoRR abs/2204.05821 (2022) - [i25]Johannes Scherer, Ansgar Scherp, Deepayan Bhowmik:
Semantic Metadata Extraction from Dense Video Captioning. CoRR abs/2211.02982 (2022) - [i24]Tobias Kalmbach, Marcel Hoffmann, Nicolas Lell, Ansgar Scherp:
Reducing a Set of Regular Expressions and Analyzing Differences of Domain-specific Statistic Reporting. CoRR abs/2211.13632 (2022) - [i23]Fabian Karl, Ansgar Scherp:
Transformers are Short Text Classifiers: A Study of Inductive Short Text Classifiers on Benchmarks and Real-world Datasets. CoRR abs/2211.16878 (2022) - [i22]Andor Diera, Nicolas Lell, Aygul Garifullina, Ansgar Scherp:
A Study on Extracting Named Entities from Fine-tuned vs. Differentially Private Fine-tuned BERT Models. CoRR abs/2212.03749 (2022) - 2021
- [j32]Falko Schönteich, Ansgar Scherp, Andreas Kasten:
Distributed Identity Management for Semantic Entities Based on Graph Signatures and owl: sameAs. Int. J. Semantic Comput. 15(1): 57-92 (2021) - [j31]Ansgar Scherp, Till Blume:
Schema-level Index Models for Web Data Search. J. Data Intell. 2(1): 47-63 (2021) - [j30]Till Blume, David Richerby, Ansgar Scherp:
FLUID: A common model for semantic structural graph summaries based on equivalence relations. Theor. Comput. Sci. 854: 136-158 (2021) - [c121]Fabian Singhofer, Aygul Garifullina, Mathias Kern, Ansgar Scherp:
A novel approach on the joint de-identification of textual and relational data with a modified mondrian algorithm. DocEng 2021: 14:1-14:10 - [c120]Steffen Epp, Marcel Hoffmann, Nicolas Lell, Michael Mohr, Ansgar Scherp:
STEREO: A Pipeline for Extracting Experiment Statistics, Conditions, and Topics from Scientific Papers. iiWAS 2021: 340-349 - [c119]M. Lautaro Hickmann, Fabian Wurzberger, Megi Hoxhalli, Arne Lochner, Jessica Töllich, Ansgar Scherp:
Analysis of GraphSum's Attention Weights to Improve the Explainability of Multi-Document Summarization. iiWAS 2021: 359-366 - [c118]Lukas Galke, Benedikt Franke, Tobias Zielke, Ansgar Scherp:
Lifelong Learning of Graph Neural Networks for Open-World Node Classification. IJCNN 2021: 1-8 - [c117]Ishwar Venugopal, Jessica Töllich, Michael Fairbank, Ansgar Scherp:
A Comparison of Deep-Learning Methods for Analysing and Predicting Business Processes. IJCNN 2021: 1-8 - [c116]Falko Schönteich, Andreas Kasten, Ansgar Scherp:
Secure Product Lifecycle Management with CO-PLM. WOP (Book) 2021: 142-165 - [i21]Steffen Epp, Marcel Hoffmann, Nicolas Lell, Michael Mohr, Ansgar Scherp:
A Machine Learning Pipeline for Automatic Extraction of Statistic Reports and Experimental Conditions from Scientific Papers. CoRR abs/2103.14124 (2021) - [i20]Iacopo Vagliano, Lukas Galke, Ansgar Scherp:
Recommendations for Item Set Completion: On the Semantics of Item Co-Occurrence With Data Sparsity, Input Size, and Input Modalities. CoRR abs/2105.04376 (2021) - [i19]Fabian Singhofer, Aygul Garifullina, Mathias Kern, Ansgar Scherp:
rx-anon - A Novel Approach on the De-Identification of Heterogeneous Data based on a Modified Mondrian Algorithm. CoRR abs/2105.08842 (2021) - [i18]M. Lautaro Hickmann, Fabian Wurzberger, Megi Hoxhalli, Arne Lochner, Jessica Töllich, Ansgar Scherp:
Analysis of GraphSum's Attention Weights to Improve the Explainability of Multi-Document Summarization. CoRR abs/2105.11908 (2021) - [i17]Lukas Galke, Ansgar Scherp:
Forget me not: A Gentle Reminder to Mind the Simple Multi-Layer Perceptron Baseline for Text Classification. CoRR abs/2109.03777 (2021) - [i16]Lukas Galke, Isabelle Cuber, Christoph Meyer, Henrik Ferdinand Nölscher, Angelina Sonderecker, Ansgar Scherp:
New Students on Sesame Street: What Order-Aware Matrix Embeddings Can Learn from BERT. CoRR abs/2109.08449 (2021) - [i15]Till Blume, David Richerby, Ansgar Scherp:
Time and Memory Efficient Algorithm for Structural Graph Summaries over Evolving Graphs. CoRR abs/2111.12493 (2021) - [i14]Lukas Galke, Iacopo Vagliano, Benedikt Franke, Tobias Zielke, Ansgar Scherp:
Lifelong Learning in Evolving Graphs with Limited Labeled Data and Unseen Class Detection. CoRR abs/2112.10558 (2021) - 2020
- [j29]Tamara Heck, Isabella Peters, Athanasios Mazarakis, Ansgar Scherp, Ina Blümel:
Open science practices in higher education: Discussion of survey results from research and teaching staff in Germany. Educ. Inf. 36(3): 301-323 (2020) - [j28]Deniz Ersan, Chifumi Nishioka, Ansgar Scherp:
Comparison of machine learning methods for financial time series forecasting at the examples of over 10 years of daily and hourly data of DAX 30 and S&P 500. J. Comput. Soc. Sci. 3(1): 103-133 (2020) - [j27]Chifumi Nishioka, Jörn Hauke, Ansgar Scherp:
Influence of tweets and diversification on serendipitous research paper recommender systems. PeerJ Comput. Sci. 6: e273 (2020) - [c115]Till Blume, David Richerby, Ansgar Scherp:
Incremental and Parallel Computation of Structural Graph Summaries for Evolving Graphs. CIKM 2020: 75-84 - [c114]Till Blume, Ansgar Scherp:
Indexing Data on the Web: A Comparison of Schema-Level Indices for Data Search. DEXA (2) 2020: 277-286 - [c113]Falko Schönteich, Andreas Kasten, Ansgar Scherp:
Distributed Identity Management for Semantic Entities. SIMBig 2020: 497-512 - [p4]Ansgar Scherp, Gerd Gröner:
Semantic Web. Handbuch der Künstlichen Intelligenz 2020: 783-816 - [i13]Till Blume, Ansgar Scherp:
Indexing Data on the Web: A Comparison of Schema-level Indices for Data Search - Extended Technical Report. CoRR abs/2006.07064 (2020) - [i12]Lukas Galke, Iacopo Vagliano, Ansgar Scherp:
Incremental Training of Graph Neural Networks on Temporal Graphs under Distribution Shift. CoRR abs/2006.14422 (2020)
2010 – 2019
- 2019
- [c112]Morten Jessen, Falk Böschen, Ansgar Scherp:
Text Localization in Scientific Figures using Fully Convolutional Neural Networks on Limited Training Data. DocEng 2019: 13:1-13:10 - [c111]Chifumi Nishioka, Jörn Hauke, Ansgar Scherp:
Towards Serendipitous Research Paper Recommender Using Tweets and Diversification. TPDL 2019: 339-343 - [c110]Lukas Galke, Florian Mai, Ansgar Scherp:
What If We Encoded Words as Matrices and Used Matrix Multiplication as Composition Function? GI-Jahrestagung 2019: 287-288 - [c109]Chifumi Nishioka, Jörn Hauke, Ansgar Scherp:
Research Paper Recommender System with Serendipity Using Tweets vs. Diversification. ICADL 2019: 63-70 - [c108]Florian Mai, Lukas Galke, Ansgar Scherp:
CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space Model. ICLR (Poster) 2019 - [c107]Mohammad Abdel-Qader, Iacopo Vagliano, Ansgar Scherp:
Analyzing the Evolution of Linked Vocabularies. ICWE 2019: 409-424 - [c106]Iacopo Vagliano, Angela Fessl, Franziska Günther, Thomas Köhler, Vasileios Mezaris, Ahmed Saleh, Ansgar Scherp, Ilija Simic:
Training Researchers with the MOVING Platform. MMM (2) 2019: 560-565 - [d4]Mohammad Abdel-Qader, Iacopo Vagliano, Ansgar Scherp:
Statistics of the Network of Linked Vocabularies. Zenodo, 2019
- [d3]Falk Böschen, Ansgar Scherp:
EconBiz Images for Text Extraction from Scholarly Figures. Zenodo, 2019 - [d2]Sven Lüdeke, Till Blume, Ansgar Scherp:
IMPULSE: Integrate Public Metadata Underneath professional Library SErvices. Zenodo, 2019 - [d1]Sven Lüdeke, Till Blume, Ansgar Scherp:
IMPULSE: Integrate Public Metadata Underneath professional Library SErvices. Zenodo, 2019 - [i11]Florian Mai, Lukas Galke, Ansgar Scherp:
CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space Model. CoRR abs/1902.06423 (2019) - [i10]Lukas Galke, Iacopo Vagliano, Ansgar Scherp:
Can Graph Neural Networks Go "Online"? An Analysis of Pretraining and Inference. CoRR abs/1905.06018 (2019) - [i9]Lukas Galke, Florian Mai, Iacopo Vagliano, Ansgar Scherp:
Multi-Modal Adversarial Autoencoders for Recommendations of Citations and Subject Labels. CoRR abs/1907.12366 (2019) - [i8]Till Blume, Ansgar Scherp:
FLuID: A Meta Model to Flexibly Define Schema-level Indices for the Web of Data. CoRR abs/1908.01528 (2019) - 2018
- [j26]Iacopo Vagliano, Franziska Günther, Matthias Heinz, Aitor Apaolaza, Irina Bienia, Gert Breitfuss, Till Blume, Chrysa Collyda, Angela Fessl, Sebastian Gottfried, Peter Hasitschka, Jasmin Kellermann, Thomas Köhler, Annalouise Maas, Vasileios Mezaris, Ahmed Saleh, Andrzej M. J. Skulimowski, Stefan Thalmann, Markel Vigo, Alfred Wertner, Michael Wiese, Ansgar Scherp:
Open Innovation in the Big Data Era With the MOVING Platform. IEEE Multim. 25(3): 8-21 (2018) - [j25]Falk Böschen, Tilman Beck, Ansgar Scherp:
Survey and empirical comparison of different approaches for text extraction from scholarly figures. Multim. Tools Appl. 77(22): 29475-29505 (2018) - [c105]Lukas Galke, Gunnar Gerstenkorn, Ansgar Scherp:
A Case Study of Closed-Domain Response Suggestion with Limited Training Data. DEXA Workshops 2018: 218-229 - [c104]Tilman Beck, Falk Böschen, Ansgar Scherp:
What to Read Next? Challenges and Preliminary Results in Selecting Representative Documents. DEXA Workshops 2018: 230-242 - [c103]Mohammad Abdel-Qader, Ansgar Scherp, Iacopo Vagliano:
Analyzing the Evolution of Vocabulary Terms and Their Impact on the LOD Cloud. ESWC 2018: 1-16 - [c102]Till Blume, Ansgar Scherp:
Towards Flexible Indices for Distributed Graph Data: The Formal Schema-level Index Model FLuID. Grundlagen von Datenbanken 2018: 23-28 - [c101]Ahmed Saleh, Tilman Beck, Lukas Galke, Ansgar Scherp:
Performance Comparison of Ad-Hoc Retrieval Models over Full-Text vs. Titles of Documents. ICADL 2018: 290-303 - [c100]Ahmed Saleh, Ansgar Scherp:
Attend2trend: Attention Model for Real-Time Detecting and Forecasting of Trending Topics. ICDM Workshops 2018: 1509-1510 - [c99]Anne Lauscher, Kai Eckert, Lukas Galke, Ansgar Scherp, Syed Tahseen Raza Rizvi, Sheraz Ahmed, Andreas Dengel, Philipp Zumstein, Annette Klein:
Linked Open Citation Database: Enabling Libraries to Contribute to an Open and Interconnected Citation Graph. JCDL 2018: 109-118 - [c98]Florian Mai, Lukas Galke, Ansgar Scherp:
Using Deep Learning for Title-Based Semantic Subject Indexing to Reach Competitive Performance to Full-Text. JCDL 2018: 169-178 - [c97]Till Blume, Ansgar Scherp:
Towards an Incremental Schema-level Index for Distributed Linked Open Data Graphs. LWDA 2018: 61-72 - [c96]Iacopo Vagliano, Lukas Galke, Florian Mai, Ansgar Scherp:
Using Adversarial Autoencoders for Multi-Modal Automatic Playlist Continuation. RecSys Challenge 2018: 5:1-5:6 - [c95]Chifumi Nishioka, Ansgar Scherp:
Analysing the Evolution of Knowledge Graphs for the Purpose of Change Verification. ICSC 2018: 25-32 - [c94]Falko Schönteich, Andreas Kasten, Ansgar Scherp:
A Pattern-Based Core Ontology for Product Lifecycle Management based on DUL. WOP@ISWC 2018: 92-106 - [c93]Lukas Galke, Florian Mai, Iacopo Vagliano, Ansgar Scherp:
Multi-Modal Adversarial Autoencoders for Recommendations of Citations and Subject Labels. UMAP 2018: 197-205 - [i7]Florian Mai, Lukas Galke, Ansgar Scherp:
Using Deep Learning For Title-Based Semantic Subject Indexing To Reach Competitive Performance to Full-Text. CoRR abs/1801.06717 (2018) - 2017
- [j24]Abdallah Salama, Carsten Binnig, Tim Kraska, Ansgar Scherp, Tobias Ziegler:
Rethinking Distributed Query Execution on High-Speed Networks. IEEE Data Eng. Bull. 40(1): 27-37 (2017) - [j23]Stefan Morana, Silvia Schacht, Ansgar Scherp, Alexander Maedche:
A review of the nature and effects of guidance design features. Decis. Support Syst. 97: 31-42 (2017) - [c92]Falk Böschen, Benjamin Strobel, Steffen Goos, Christoph Liebers, Bastian Rathje, Ansgar Scherp:
Evaluation of the Comprehensiveness of Bar Charts with and without Stacking Functionality using Eye-Tracking. CHIIR 2017: 337-340 - [c91]Lukas Galke, Ahmed Saleh, Ansgar Scherp:
Word Embeddings for Practical Information Retrieval. GI-Jahrestagung 2017: 2155-2167 - [c90]Ahmed Saleh, Florian Mai, Chifumi Nishioka, Ansgar Scherp:
Reranking-based Recommender System with Deep Learning. GI-Jahrestagung 2017: 2169-2175 - [c89]Lukas Galke, Florian Mai, Alan Schelten, Dennis Brunsch, Ansgar Scherp:
Using Titles vs. Full-text as Source for Automated Semantic Document Annotation. K-CAP 2017: 20:1-20:4 - [c88]Iacopo Vagliano, Diego Monti, Ansgar Scherp, Maurizio Morisio:
Content Recommendation through Semantic Annotation of User Reviews and Linked Data. K-CAP 2017: 32:1-32:4 - [c87]Ansgar Scherp, Vasileios Mezaris, Thomas Köhler, Alexander G. Hauptmann:
MultiEdTech 2017: 1st International Workshop on Multimedia-based Educational and Knowledge Technologies for Personalized and Social Online Training. ACM Multimedia 2017: 1980-1982 - [c86]Falk Böschen, Ansgar Scherp:
A Comparison of Approaches for Automated Text Extraction from Scholarly Figures. MMM (1) 2017: 15-27 - [c85]Chifumi Nishioka, Ansgar Scherp:
Keeping linked open data caches up-to-date by predicting the life-time of RDF triples. WI 2017: 73-80 - [e7]Ansgar Scherp, Vasileios Mezaris, Thomas Köhler, Alexander G. Hauptmann:
Proceedings of the 2017 ACM Workshop on Multimedia-based Educational and Knowledge Technologies for Personalized and Social Online Training, MultiEdTech@MM 2017, Mountain View, CA, USA, October 27, 2017. ACM 2017, ISBN 978-1-4503-5508-7 [contents] - [i6]Lukas Galke, Florian Mai, Alan Schelten, Dennis Brunsch, Ansgar Scherp:
Comparing Titles vs. Full-text for Multi-Label Classification of Scientific Papers and News Articles. CoRR abs/1705.05311 (2017) - [i5]Iacopo Vagliano, Diego Monti, Ansgar Scherp, Maurizio Morisio:
Content Recommendation through Semantic Annotation of User Reviews and Linked Data - An Extended Technical Report. CoRR abs/1709.09973 (2017) - [i4]Mohammad Abdel-Qader, Ansgar Scherp:
Towards Understanding the Evolution of Vocabulary Terms in Knowledge Graphs. CoRR abs/1710.00232 (2017) - 2016
- [j22]Atif Latif, Ansgar Scherp, Klaus Tochtermann:
LOD for Library Science: Benefits of Applying Linked Open Data in the Digital Library Setting - Retrospects and Research Topics. Künstliche Intell. 30(2): 149-157 (2016) - [c84]Mohammad Abdel-Qader, Ansgar Scherp:
Qualitative Analysis of Vocabulary Evolution on the Linked Open Data Cloud. PROFILES@ESWC 2016 - [c83]Thomas Gottron, Malte Knauf, Ansgar Scherp, Johann Schaible:
ELLIS: Interactive Exploration of Linked Data on the Level of Induced Schema Patterns. SumPre@ESWC 2016 - [c82]Chifumi Nishioka, Ansgar Scherp:
Information-theoretic Analysis of Entity Dynamics on the Linked Open Data Cloud. PROFILES@ESWC 2016 - [c81]Johann Schaible, Thomas Gottron, Ansgar Scherp:
TermPicker: Enabling the Reuse of Vocabulary Terms by Exploiting Data from the Linked Open Data Cloud. ESWC 2016: 101-117 - [c80]Johann Schaible, Pedro A. Szekely, Ansgar Scherp:
Comparing Vocabulary Term Recommendations Using Association Rules and Learning to Rank: A User Study. ESWC 2016: 214-230 - [c79]Chifumi Nishioka, Ansgar Scherp:
Profiling vs. Time vs. Content: What does Matter for Top-k Publication Recommendation based on Twitter Profiles? JCDL 2016: 171-180 - [i3]Chifumi Nishioka, Ansgar Scherp:
Profiling vs. Time vs. Content: What does Matter for Top-k Publication Recommendation based on Twitter Profiles? - An Extended Technical Report. CoRR abs/1603.07016 (2016) - 2015
- [b2]