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Local, Domain-independent Heuristics for the FEIII Challenge: Lessons and Observations

Published: 26 June 2016 Publication History

Abstract

The recently concluded Financial Entity Identification and Information Integration (FEIII) competition is an example of a domain-specific entity linking challenge. Given a variety of datasets describing financial institutions, the goal of the competition was to interlink entities referring to the same underlying entity in a minimally supervised manner. In this paper, we present our solution to the challenge. Using local, domain-independent heuristics, namely thresholded block purging and a simple Jaccard matcher, we devised a solution that has execution times of less than a minute on the alloted tasks. Although the method did not achieve competitive precision, it was recall-friendly, suggesting that it is useful both as an easily implemented baseline, as well as a generic preprocessing step for more expensive, precision-friendly algorithms that are fine-tuned for specific domains.

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cover image ACM Conferences
DSMM'16: Proceedings of the Second International Workshop on Data Science for Macro-Modeling
June 2016
71 pages
ISBN:9781450344074
DOI:10.1145/2951894
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 June 2016

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Author Tags

  1. Block purging
  2. Domain-specific
  3. Entity linking
  4. Heuristics
  5. Jaccard
  6. Local
  7. Unsupervised

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  • Short-paper
  • Research
  • Refereed limited

Conference

SIGMOD/PODS'16
Sponsor:
SIGMOD/PODS'16: International Conference on Management of Data
June 26 - July 1, 2016
CA, San Francisco, USA

Acceptance Rates

DSMM'16 Paper Acceptance Rate 6 of 17 submissions, 35%;
Overall Acceptance Rate 32 of 64 submissions, 50%

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