Medical documents processing for summary generation and keywords highlighting based on natural language processing and ontology graph descriptor approach

Alexander Dudko, Tatiana Endrjukaite, Yasushi Kiyoki

研究成果: Conference contribution

抄録

In this paper a new method of data retrieval from free text documents in medical domain is proposed. Presented approach gives the document summary and highlights important keywords in the text to support further analysis of multiple medical documents. The document is processed with natural language processing techniques to find medical keywords and assign them to concepts in the medical ontology. These concepts contribute to higher levels in the hierarchy and build the document descriptor as a graph with concepts in the nodes and corresponding relevance points. The descriptor is used to generate the summary in a form of tree. Finally, we highlight the most important keywords in the original text. Presented experiments demonstrate the proposed approach, which successfully summarizes and highlights meaningful medical information.

本文言語English
ホスト出版物のタイトル19th International Conference on Information Integration and Web-Based Applications and Services, iiWAS2017 - Proceedings
出版社Association for Computing Machinery
ページ58-65
ページ数8
Part F134476
ISBN(電子版)9781450352994
DOI
出版ステータスPublished - 2017 12 4
イベント19th International Conference on Information Integration and Web-Based Applications and Services, iiWAS2017 - Salzburg, Austria
継続期間: 2017 12 42017 12 6

Other

Other19th International Conference on Information Integration and Web-Based Applications and Services, iiWAS2017
国/地域Austria
CitySalzburg
Period17/12/417/12/6

ASJC Scopus subject areas

  • 人間とコンピュータの相互作用
  • コンピュータ ネットワークおよび通信
  • コンピュータ ビジョンおよびパターン認識
  • ソフトウェア

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