<abstract xmlns="http://www.w3.org/1999/xhtml"><p> Document summarization deals with providing condensed version of the original document. We present an extractive informative single medical document summarization approach. We compare the tokens in the sentence with cue words. A sentence ranking method is used to extract the important sentences. The existing summarizers are used for performance analysis.</p></abstract>

Document summarization deals with providing condensed version of the original document. We present an extractive informative single medical document summarization approach. We compare the tokens in the sentence with cue words. A sentence ranking method is used to extract the important sentences. The existing summarizers are used for performance analysis.

Towards an Efficient Approach for Automatic Medical Document Summarization

School of Computing Science and Engineering, VIT University, Tamil Nadu, India

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Towards an Efficient Approach for Automatic Medical Document Summarization"}

Document summarization deals with providing condensed version of the original document. We present an extractive informative single medical document...

Towards an Efficient Approach for Automatic Medical Document Summarization

Data publikacji: 26 lis 2015

Zakres stron: 78 - 91

DOI: https://doi.org/10.1515/cait-2015-0056

Słowa kluczowe
Document summarization, medical document, Domain-specific vocabulary, cue words, sentence ranking

© by P. Gayathri

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Towards an Efficient Approach for Automatic Medical Document Summarization

Data publikacji: 26 lis 2015

Zakres stron: 78 - 91

DOI: https://doi.org/10.1515/cait-2015-0056

Słowa kluczoweDocument summarization, medical document, Domain-specific vocabulary, cue words, sentence ranking

© by P. Gayathri

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Słowa kluczowe
Document summarization, medical document, Domain-specific vocabulary, cue words, sentence ranking