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Concept Frequency Distribution in Biomedical Text Summarization

This study presents a method to identify important sentences in biomedical texts, aiding physicians in finding clinical trial information. The paper evaluates the use of frequency distribution to generate text summaries and discusses different summarization approaches.

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Concept Frequency Distribution in Biomedical Text Summarization

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  1. Concept Frequency Distribution in Biomedical Text Summarization Advisor : Dr. Hsu Presenter : Yu-San Hsieh Author : Lawrence H. Reeve, Hyoil Han, Saya V. Nagori, Jonathan C. Yang, Tamara A. Schwimmer, Ari D. Brooks 2006. CIKM.604-611

  2. Outline • Motivation • Objective • Introduction • Method • Experiments • Conclusions

  3. Motivation • The medical text summarization is particularly useful in the biomedical domain, where physicians must continuously find clinical trial study information in mass treatment information database ,then to incorporate into their patient treatment efforts.

  4. Objective • This paper has proposed a better method to identify important sentences within a full-text and generate text summaries.

  5. Full-text Sentences Noun phrase Concept Introduction Term • The approaches of generating summaries • Extractive and Abstractive • UMLS Metathesaurus • UMLS MetaMap Transfer • Biomedical text concept distribution full-text abstracts

  6. Summary-output Candidate model source-model Method Source-text Source-model Candidate-model Sentence-pool srcUIs : [12, 13, 14, 7, 10] sryUIs : [5, 9, 6, 7, 8] ui: unit item Sentence-pool Candidate-model n > best-score y Best-sentence

  7. Experiments • Corpus • A citation database of oncology clinical trial papers(1200) • Evaluation tool • ROUGE-2 and ROUGE-SU4 • Model Summaries • The first model is the abstract of the paper • Three models from three different domain experts were generated • Summarizers used for evaluation • BaseLine, FreqDist, MEAD, AutoSummarize, SumBasic, SWESUM

  8. Experiments

  9. Conclusions • We developed a new algorithm based on frequency distribution modeling and evaluate it using terms as well as concepts.

  10. My opinion • Advantage • …… • Drawback • …… • Application • Information Retrieval

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