文章摘要
潘昊杰,周芳,张博文,张乐乐,方帆,殷绪成.生物医学文献检索方法与问答系统[J].情报工程,2016,2(5):050-057
生物医学文献检索方法与问答系统
Query Processing in Biomedical Literature RetrievalandQuestion Answering System
  
DOI:
中文关键词: 生物医学文献检索,序列依赖模型,词向量,伪相关反馈,排序学习
英文关键词: Biomedical literature retrieval, sequential dependence model, word embedding, pseudo relevance feedback,learning-to-rank
基金项目:本研究得到国家自然科学基金“结合前馈和反馈机制的自然场景文本识别技术”(编号:61473036)的资助,并在此基 础上展开后续理论及应用研究。
作者单位
潘昊杰 北京科技大学计算机科学与技术系 
周芳 北京科技大学计算机科学与技术系 
张博文 北京科技大学计算机科学与技术系 
张乐乐 北京科技大学计算机科学与技术系 
方帆 北京科技大学计算机科学与技术系 
殷绪成 北京科技大学计算机科学与技术系 
摘要点击次数: 306
全文下载次数: 363
中文摘要:
      如何有效的进行生物医学文献检索和信息挖掘,是计算机技术和生物信息技术研究领域中的一 个经典课题。本文对生物医学文献中自然语言问题文档,片段,概念和 RDF 三元组,构建了高效的检 索和问答系统。特别的,在文档检索中,我们搭建了基于顺序依赖模型,词向量,和伪相关反馈相结 合的通用检索模型;同时,前 k 个文档被分离为句子和片段,并以此建立检索索引,并基于文档检索 模型,完成片段检索;在概念挖掘中,提取生物医学的概念,列出相关的概念属于网络服务的五个数 据库链接,通过得分排名得到最终的概念。在 CLEF BioASQ 几年的评测数据上,我们构造的检索系统 都取得了不错的性能。
英文摘要:
      How to effectively carry out the biomedical literature search and information mining is a classic topic in the field of computer technology and biological information technology research.This study constructed an efficient retrieval and question answering system refer to the related problem of natural language problems in biological medical literature documents,including snippets, concepts and RDF triplets.In particular, this research built a general search model based on Sequential Dependence Model, WordEmbedding and Pseudo Relevance Feedbackin the documents retrieval. Moreover, the former K documents were separated into sentences and snippets to establish the indexand complete the snippets search based on the documents retrieval model. In concepts mining, this study extracted biomedical concepts from the concepts, listed the related concepts belong to the web service of five URLs, and obtained the final concepts through the score rank. The results indicated that the retrieval systemof this study has achieved good performance based on the test data from CLEF BioASQ.
查看全文   查看/发表评论  下载PDF阅读器
关闭

分享按钮