Supervised Contrastive Learning for Product Matching | 1 | 0.36 | 2022 |
Impact of the Characteristics of Multi-source Entity Matching Tasks on the Performance of Active Learning Methods | 0 | 0.34 | 2022 |
Cross-Language Learning for Product Matching | 0 | 0.34 | 2022 |
Graph-Boosted Active Learning for Multi-source Entity Resolution | 0 | 0.34 | 2021 |
Dual-Objective Fine-Tuning of BERT for Entity Matching. | 0 | 0.34 | 2021 |
Profiling Entity Matching Benchmark Tasks | 0 | 0.34 | 2020 |
Unsupervised Bootstrapping of Active Learning for Entity Resolution. | 0 | 0.34 | 2020 |
Intermediate Training of BERT for Product Matching. | 0 | 0.34 | 2020 |
MWPD2020 - Semantic Web Challenge on Mining the Web of HTML-embedded Product Data. | 0 | 0.34 | 2020 |
Using schema.org annotations for training and maintaining product matchers | 0 | 0.34 | 2020 |
Using Weak Supervision to Identify Long-Tail Entities for Knowledge Base Completion. | 0 | 0.34 | 2019 |
Synthesizing N-ary Relations from Web Tables | 0 | 0.34 | 2019 |
Robust Active Learning of Expressive Linkage Rules | 0 | 0.34 | 2019 |
Profiling the semantics of n-ary web table data | 0 | 0.34 | 2019 |
The WDC Training Dataset and Gold Standard for Large-Scale Product Matching | 0 | 0.34 | 2019 |
Density- and Correlation-based Table Extension. | 0 | 0.34 | 2018 |
Estimating Missing Temporal Meta-Information using Knowledge-Based-Trust. | 0 | 0.34 | 2017 |
Extracting attribute-value pairs from product specifications on the web | 1 | 0.37 | 2017 |
Matching Web Tables To DBpedia - A Feature Utility Study. | 5 | 0.40 | 2017 |
LDOW2017: 10th Workshop on Linked Data on the Web. | 0 | 0.34 | 2017 |
Stitching Web Tables for Improving Matching Quality. | 0 | 0.34 | 2017 |
Extending RapidMiner with Data Search and Integration Capabilities. | 1 | 0.34 | 2016 |
Web table column categorisation and profiling. | 1 | 0.35 | 2016 |
A Large Public Corpus of Web Tables containing Time and Context Metadata. | 20 | 0.79 | 2016 |
A Web Application to Search a Large Repository of Taxonomic Relations from the Web. | 0 | 0.34 | 2016 |
Profiling the Potential of Web Tables for Augmenting Cross-domain Knowledge Bases. | 19 | 0.71 | 2016 |
Fusing time-dependent web table data. | 0 | 0.34 | 2016 |
A Large DataBase of Hypernymy Relations Extracted from the Web. | 12 | 0.59 | 2016 |
Mining the Web of Linked Data with RapidMiner | 23 | 1.05 | 2015 |
The Graph Structure in the Web -- Analyzed on Different Aggregation Levels | 24 | 0.86 | 2015 |
Towards Automatic Topical Classification of LOD Datasets | 3 | 0.39 | 2015 |
A Web-scale Study of the Adoption and Evolution of the schema.org Vocabulary over Time | 14 | 0.84 | 2015 |
LDOW 2013: The 8th Workshop on Linked Data on the Web | 0 | 0.34 | 2015 |
DBpedia - A large-scale, multilingual knowledge base extracted from Wikipedia. | 180 | 6.43 | 2015 |
The Mannheim Search Join Engine | 23 | 0.90 | 2015 |
Matching HTML Tables to DBpedia | 35 | 1.38 | 2015 |
Graph structure in the web: aggregated by pay-level domain | 13 | 0.76 | 2014 |
Integrating product data from websites offering microdata markup | 9 | 0.90 | 2014 |
Detecting Errors in Numerical Linked Data Using Cross-Checked Outlier Detection | 13 | 0.81 | 2014 |
RESTful open workflows for data provenance and reuse | 3 | 0.51 | 2014 |
Learning Regular Expressions for the Extraction of Product Attributes from E-commerce Microdata. | 4 | 0.47 | 2014 |
Adoption of the Linked Data Best Practices in Different Topical Domains | 154 | 4.75 | 2014 |
Search Joins with the Web. | 3 | 0.41 | 2014 |
Learning conflict resolution strategies for cross-language Wikipedia data fusion | 13 | 0.66 | 2014 |
Graph structure in the web --- revisited: a trick of the heavy tail | 36 | 1.56 | 2014 |
The WebDataCommons Microdata, RDFa and Microformat Dataset Series | 40 | 1.92 | 2014 |
Type Inference on Noisy RDF Data | 60 | 2.05 | 2013 |
Interlinking Scientific Data on a Global Scale. | 5 | 0.48 | 2013 |
Deployment of RDFa, Microdata, and Microformats on the Web - A Quantitative Analysis. | 11 | 1.70 | 2013 |
Active learning of expressive linkage rules using genetic programming | 21 | 0.90 | 2013 |