AdaTyper: Adaptive Semantic Column Type Detection

1 code implementation • 23 Nov 2023 • Madelon Hulsebos, Paul Groth, Çağatay Demiralp

A key source for understanding a table is the semantics of its columns.

Observatory: Characterizing Embeddings of Relational Tables

1 code implementation • 5 Oct 2023 • Tianji Cong, Madelon Hulsebos, Zhenjie Sun, Paul Groth, H. V. Jagadish

Based on these properties, we define an extensible framework to evaluate language and table embedding models.

Results of SemTab 2022

no code implementations • SemTab@ISWC 2022 • Nora Abdelmageed, Jiaoyan Chen, Vincenzo Cutrona, Vasilis Efthymiou, Oktie Hassanzadeh, Madelon Hulsebos, Ernesto Jiménez-Ruiz, Juan Sequeda, Kavitha Srinivas

SemTab 2022 was the fourth edition of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, successfully collocated with the 21st International Semantic Web Conference (ISWC) and the 17th Ontology Matching (OM) Workshop.

Cell Entity Annotation Column Type Annotation +2

Augmenting Decision Making via Interactive What-If Analysis

no code implementations • 13 Sep 2021 • Sneha Gathani, Madelon Hulsebos, James Gale, Peter J. Haas, Çağatay Demiralp

The fundamental goal of business data analysis is to improve business decisions using data.

Decision Making Marketing

Making Table Understanding Work in Practice

no code implementations • 11 Sep 2021 • Madelon Hulsebos, Sneha Gathani, James Gale, Isil Dillig, Paul Groth, Çağatay Demiralp

However, we observe that there exists a gap between the performance of these models on these benchmarks and their applicability in practice.

Data Integration

GitTables: A Large-Scale Corpus of Relational Tables

2 code implementations • 14 Jun 2021 • Madelon Hulsebos, Çağatay Demiralp, Paul Groth

Existing table corpora primarily contain tables extracted from HTML pages, limiting the capability to represent offline database tables.

Information Retrieval Table annotation

Sato: Contextual Semantic Type Detection in Tables

1 code implementation • 14 Nov 2019 • Dan Zhang, Yoshihiko Suhara, Jinfeng Li, Madelon Hulsebos, Çağatay Demiralp, Wang-Chiew Tan

Detecting the semantic types of data columns in relational tables is important for various data preparation and information retrieval tasks such as data cleaning, schema matching, data discovery, and semantic search.

Column Type Annotation Hybrid Machine Learning +4

Sherlock: A Deep Learning Approach to Semantic Data Type Detection

2 code implementations • 25 May 2019 • Madelon Hulsebos, Kevin Hu, Michiel Bakker, Emanuel Zgraggen, Arvind Satyanarayan, Tim Kraska, Çağatay Demiralp, César Hidalgo

Correctly detecting the semantic type of data columns is crucial for data science tasks such as automated data cleaning, schema matching, and data discovery.

Column Type Annotation Deep Learning +2

VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository

1 code implementation • 12 May 2019 • Kevin Hu, Neil Gaikwad, Michiel Bakker, Madelon Hulsebos, Emanuel Zgraggen, César Hidalgo, Tim Kraska, Guoliang Li, Arvind Satyanarayan, Çağatay Demiralp

Researchers currently rely on ad hoc datasets to train automated visualization tools and evaluate the effectiveness of visualization designs.

Benchmarking

The Network Nullspace Property for Compressed Sensing of Big Data over Networks

no code implementations • 11 May 2017 • Alexander Jung, Madelon Hulsebos

The network nullspace property couples the cluster structure of the underlying network-structure with the geometry of the sampling set.