ARCTIC: metadata extraction from scientific papers in pdf using two-layer CRF

No abstract is available for this paper.

• Publication year

  2014

• Venue

  ACM Symposium on Document Engineering

• Publication date

  2014-09-16

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1145/2644866.2644872
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Extracting and matching authors and affiliations in scholarly documents

  2013cited by this paper
• Evaluation of header metadata extraction approaches and tools for scientific PDF documents

  2013cited by this paper
• Logical Structure Recovery in Scholarly Articles with Rich Document Features

  2010cited by this paper
• An Evaluation Framework for Plagiarism Detection

  2010cited by this paper
• Retrieving Metadata for Your Local Scholarly Papers

  2009cited by this paper
• ParsCit: an Open-source CRF Reference String Parsing Package

  2008cited by this paper
• Automated Template-Based Metadata Extraction Architecture

  2007cited by this paper
• Header Metadata Extraction from Semi-structured Documents Using Template Matching

  2006cited by this paper
• Conditional Random Fields: An Introduction

  2004cited by this paper
• Metadata Extraction from Bibliographies Using Bigram HMM

  2004cited by this paper
• Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data

  2001cited by this paper
• Learning Hidden Markov Model Structure for Information Extraction

  1999cited by this paper

• Metadata Extraction Leveraging Large Language Models

  2025cites this paper
• Annotated Open Corpus Construction and BERT-Based Approach for Automatic Metadata Extraction From Korean Academic Papers

  2023cites this paper
• A Benchmark of PDF Information Extraction Tools Using a Multi-task and Multi-domain Evaluation Framework for Academic Documents

  2023cites this paper
• Automatic Detection of the Boundary between Metadata and Body in Persian Theses using BA_SVM

  2021cites this paper
• Automatic Metadata Extraction From Iranian Theses And Dissertations

  2020cites this paper
• Information extraction from scientific articles: a survey

  2018cites this paper
• Scholarly Document Information Extraction using Extensible Features for Efficient Higher Order Semi-CRFs

  2015cites this paper
• Automatic Metadata Extraction The High Energy Physics Use Case

  2015cites this paper