Cross-Document Coreference on a Large Scale Corpus

Abstract

In this paper, we will compare and evaluate the effectiveness of different statistical methods in the task of cross-document coreference resolution. We created entity models for different test sets and compare the following disambiguation and clustering techniques to cluster the entity models in order to create coreference chains: Incremental Vector Space, KL-Divergence, Agglomerative Vector Space. Coreference analysis refers to the process of determining whether or not two mentions of entities refer to the same person (Kibble and Deemter, 2000).

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2004
Accession Number
ADA458579

Entities

People

  • Chung H. Gooi
  • James Allan

Organizations

  • University of Massachusetts Amherst

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Clustering
  • Computational Linguistics
  • Computer Science
  • Detection
  • Information Retrieval
  • Information Science
  • Language
  • Linguistics
  • Named Entity Recognition
  • Precision
  • Probability
  • Probability Distributions
  • Test And Evaluation
  • Test Sets
  • Vector Spaces

Readers

  • Computer Vision.
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  • Theoretical Analysis.

Technology Areas

  • Space