Natural language processing knowledge network approach for interactive highlighting and summary

Alexander Dudko, Tatiana Endrjukaite, Yasushi Kiyoki

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This paper describes a new approach of data retrieval from free text documents in medical domain. Proposed approach creates the document summary and highlights most important keywords in the text by means of document ontology, as an internal representation of the document. This document ontology is a graph with concepts, relations between them, and concept points as a metric of relevance. By means of points the approach performs ambiguity resolution, selects most relevant concepts to display in the summary, and votes for keywords highlighting in the text. Moreover, interactive highlighting reveals additional information from document ontology as reader interacts with the keywords and summary in the document. The described approach helps to speed up analysis and decision-making processes by means of providing aggregated summary for a document and highlighting most meaningful parts of the text.

Original languageEnglish
Title of host publicationLecture Notes in Networks and Systems
PublisherSpringer
Pages191-200
Number of pages10
DOIs
Publication statusPublished - 2019 Jan 1

Publication series

NameLecture Notes in Networks and Systems
Volume68
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Keywords

  • Information retrieval
  • Interactive highlighting
  • Summary generation
  • Text mining

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Control and Systems Engineering

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  • Cite this

    Dudko, A., Endrjukaite, T., & Kiyoki, Y. (2019). Natural language processing knowledge network approach for interactive highlighting and summary. In Lecture Notes in Networks and Systems (pp. 191-200). (Lecture Notes in Networks and Systems; Vol. 68). Springer. https://doi.org/10.1007/978-3-030-12450-2_18