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'''FEIII CHALLENGE PAPER'''
'''FEIII Participant Reports'''
 
'''Financial Entity Identification and Information Integration (FEIII) 2017 Challenge: The Report of the Organizing Committee'''
    Doug Burdick, Mark Flood, John Grant, Joe Langsam, Louiqa Raschid, Ian Soboroff and Elena Zotkina


  '''Predicting Role Relevance with Deep Learning in a Financial Domain'''
  '''Predicting Role Relevance with Deep Learning in a Financial Domain'''
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  '''Ranking Sentences Describing Relationships Between Financial Entities by Relevance'''
  '''Ranking Sentences Describing Relationships Between Financial Entities by Relevance'''
     Tim Repke and Michael Loster and Ralf Krestel
     Tim Repke and Michael Loster and Ralf Krestel
'''Thomson Reuters' Solution for Triple Ranking in the FEIII 2017 Challenge'''
    Elizabeth Roman and Brian Ulicny
'''Towards Re-defining Relation Understanding in Financial Domain'''
    Chenguang Wang and Doug Burdick and Laura Chiticariu and Rajasekar Krishnamurthy
    and Yunyao Li and Huaiyu Zhu


  '''Entity Relationship Ranking Using Differential Keyword-Role Affinity'''
  '''Entity Relationship Ranking Using Differential Keyword-Role Affinity'''

Latest revision as of 06:25, 6 May 2017

FEIII Participant Reports

Predicting Role Relevance with Deep Learning in a Financial Domain
   Mayank Kejriwal
Understanding Relations using Concepts and Semantics 
   Jouyon Park and Hyunsouk Cho and Seungwon Hwang
Hybrid Feature Factored System for Scoring Extracted Passage Relevance in Regulatory Filings
   Denys Proux and Claude Roux and Agnes Sandor and Julien Perez
Ranking Sentences Describing Relationships Between Financial Entities by Relevance
   Tim Repke and Michael Loster and Ralf Krestel
Entity Relationship Ranking Using Differential Keyword-Role Affinity
   Rohit Naini and Pawan Yadav
FactSet - The Advantage of Scored Data
   Raymond Hicks