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'''FEIII CHALLENGE PAPER'''
'''FEIII CHALLENGE PAPER'''


  '''Financial Entity Identification and Information Integration (FEIII) Challenge: The Report of the Organizing Committee'''
  '''Financial Entity Identification and Information Integration (FEIII) 2017 Challenge: The Report of the Organizing Committee'''
     Mark Flood), J. Grant, H. Luo, L. Raschid, I. Soboroff, K. Yoo
     Doug Burdick, Mark Flood, John Grant, Joe Langsam, Louiqa Raschid, Ian Soboroff and Elena Zotkina


  '''Combination of Rule-based and Textual Similarity Approaches to Match Financial Entities'''
  '''Predicting Role Relevance with Deep Learning in a Financial Domain'''
     Ahmad Samiei, Ioannis Koumarelas, Michael Loster, Felix Naumann
     Mayank Kejriwal


  '''An Ensemble Approach to Financial Entity Matching for the FEIII 2016 Challenge'''
  '''Understanding Relations using Concepts and Semantics '''
     Enrico Palumbo, Giuseppe Rizzo, Raphael Troncy
     Jouyon Park and Hyunsouk Cho and Seungwon Hwang


  '''Thomson Reuters and the FEIII Challenge'''
  '''Hybrid Feature Factored System for Scoring Extracted Passage Relevance in Regulatory Filings'''
     B. Ulicny, A. Constandache, J. Cunningham, M. Traub, K. Yu, C. Azeglio, M. Saito-Varadi
     Denys Proux and Claude Roux and Agnes Sandor and Julien Perez


  '''Financial Entity Record Linkage with Random Forests'''
  '''Ranking Sentences Describing Relationships Between Financial Entities by Relevance'''
     Kunho Kim, C. Lee Giles
     Tim Repke and Michael Loster and Ralf Krestel


  '''Towards High-Precision and Reusable Entity Resolution Algorithms over Sparse Financial Datasets'''
  '''Thomson Reuters' Solution for Triple Ranking in the FEIII 2017 Challenge'''
    Douglas Burdick, Lucian Popa, Rajasekar Krishnamurthy
    Elizabeth Roman and Brian Ulicny


  '''FactSet Concordance: Entity Data Management'''
  '''Towards Re-defining Relation Understanding in Financial Domain'''
    Raymond Bentley Hicks
    Chenguang Wang and Doug Burdick and Laura Chiticariu and Rajasekar Krishnamurthy and Yunyao Li and Huaiyu Zhu


  '''Local, Domain-independent Heuristics for the FEIII Challenge: Lessons and Observations'''
  '''Entity Relationship Ranking Using Differential Keyword-Role Affinity'''
     Mayank Kejriwal, Daniel Miranker
    Rohit Naini and Pawan Yadav
 
'''FactSet - The Advantage of Scored Data'''
     Raymond Hicks

Revision as of 01:54, 30 March 2017

FEIII CHALLENGE PAPER 

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
   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

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
   Rohit Naini and Pawan Yadav

FactSet - The Advantage of Scored Data
   Raymond Hicks
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