Search Results for author: Çağatay Demiralp

Found 15 papers, 9 papers with code

Making Table Understanding Work in Practice

no code implementations11 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.

TagRuler: Interactive Tool for Span-Level Data Programming by Demonstration

1 code implementation24 Jun 2021 Dongjin Choi, Sara Evensen, Çağatay Demiralp, Estevam Hruschka

In this work, we extend the DPBD framework to span-level annotation tasks, arguably one of the most time-consuming NLP labeling tasks.

Active Learning Document Classification

GitTables: A Large-Scale Corpus of Relational Tables

1 code implementation14 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

Annotating Columns with Pre-trained Language Models

1 code implementation5 Apr 2021 Yoshihiko Suhara, Jinfeng Li, Yuliang Li, Dan Zhang, Çağatay Demiralp, Chen Chen, Wang-Chiew Tan

Inferring meta information about tables, such as column headers or relationships between columns, is an active research topic in data management as we find many tables are missing some of this information.

Multi-Task Learning Table annotation +1

Leam: An Interactive System for In-situ Visual Text Analysis

no code implementations8 Sep 2020 Sajjadur Rahman, Peter Griggs, Çağatay Demiralp

Text data analysis is an iterative, non-linear process with diverse workflows spanning multiple stages, from data cleaning to visualization.

Data Programming by Demonstration: A Framework for Interactively Learning Labeling Functions

1 code implementation3 Sep 2020 Sara Evensen, Chang Ge, Dongjin Choi, Çağatay Demiralp

We operationalize our framework with Ruler, an interactive system that synthesizes labeling rules for document classification by using span-level annotations of users on document examples.

Document Classification

Teddy: A System for Interactive Review Analysis

1 code implementation15 Jan 2020 Xiong Zhang, Jonathan Engel, Sara Evensen, Yuliang Li, Çağatay Demiralp, Wang-Chiew Tan

They contain a wealth of information about the opinions and experiences of users, which can help better understand consumer decisions and improve user experience with products and services.

Sato: Contextual Semantic Type Detection in Tables

1 code implementation14 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.

Information Retrieval Structured Prediction

Sherlock: A Deep Learning Approach to Semantic Data Type Detection

2 code implementations25 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.

Word Embeddings

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

1 code implementation12 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.

Track Xplorer: A System for Visual Analysis of Sensor-based Motor Activity Predictions

no code implementations25 Jun 2018 Marco Cavallo, Çağatay Demiralp

We demonstrate how Track Xplorer helps identify early on possible systemic data errors, effectively track and compare the results of different classifiers, and reason about and pinpoint the causes of misclassifications.

Clustrophile 2: Guided Visual Clustering Analysis

no code implementations9 Apr 2018 Marco Cavallo, Çağatay Demiralp

Data scientists need adequate interactive tools to effectively explore and navigate the large clustering space so as to improve the effectiveness of exploratory clustering analysis.

Data2Vis: Automatic Generation of Data Visualizations Using Sequence to Sequence Recurrent Neural Networks

2 code implementations9 Apr 2018 Victor Dibia, Çağatay Demiralp

Rapidly creating effective visualizations using expressive grammars is challenging for users who have limited time and limited skills in statistics and data visualization.

Data Visualization Translation

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