Question Answering Summarization of Multiple Biomedical Documents

نویسندگان

  • Zhongmin Shi
  • Gabor Melli
  • Yang Wang
  • Yudong Liu
  • Baohua Gu
  • Mehdi M. Kashani
  • Anoop Sarkar
  • Fred Popowich
چکیده

In this paper we introduce a system that automatically summarizes multiple biomedical documents relevant to a question. The system extracts biomedical and general concepts by utilizing concept-level knowledge from domain-specific and domain-independent sources. Semantic role labeling, semantic subgraph-based sentence selection and automatic post-editing are involved in the process of finding the information need. Due to the absence of expert-written summaries of biomedical documents, we propose an approximate evaluation by taking MEDLINE abstracts as expert-written summaries. Evaluation results indicate that our system does help in answering questions and the automatically generated summaries are comparable to abstracts of biomedical articles, as evaluated using the ROUGE measure.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Semantic Interpretation for the Biomedical Research Literature

Chapter Overview Natural language processing is increasingly used to support biomedical applications that manipulate information rather than documents. Examples include automatic summarization, question answering, and literature-based scientific discovery. Semantic processing is a method of automatic language analysis that identifies concepts and relationships to represent document content. The...

متن کامل

Multi-Document Summarization: Methodologies and Evaluations

This paper describes a system for the summarization of multiple documents. The system produces multi-document summaries using clustering techniques to identify common themes across the set of documents. For each theme, the system identifies representative passages that are included in the final summary. We also describe a methodology for evaluation of our system which is based upon a question a...

متن کامل

Answering Questions from Multiple Documents - the Role of Multi-Document Summarization

Ongoing research work on Question Answering using multi-document summarization has been described. It has two main sub modules, document retrieval and Multi-document Summarization. We first preprocess the documents and then index them using Nutch with NE field. Stop words are removed and NEs are tagged from each question and all remaining question words are stemmed and then retrieve the most re...

متن کامل

Assessing the performance of Olelo, a real-time biomedical question answering application

Question answering (QA) can support physicians and biomedical researchers to find answers to their questions in the scientific literature. Such systems process large collections of documents in real time and include many natural language processing (NLP) procedures. We recently developed Olelo, a QA system for biomedicine which includes various NLP components, such as question processing, docum...

متن کامل

Telugu - English Dictionary Based Cross Language Query Focused Multi-Document Summarization

Summarization systems and Question Answering systems can be treated to have complementary functionality to each other. For instance, a question answering system could have a summarization module, that can summarize the fragments of answers found by the question answering system. On the other hand a summarization system can be given a question as input, to generate a question focused summary as ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007