Image Retrieval for Open Access PubMedCentral Archive

Traditional literature search engine in biomedicine domain focus mainly on summary content such as title, abstract, keywords, journal published, author etc. There is a need to develop full-text search engine to encompass not only summary information, but also experimental details described in results and discussion. Images in the paper convey important and rich information about the experimental design and findings and are key components for results and discussion. Yet so far there is no image retrieval system implemented for literature databases. In this study, we build a prototype for image retrieval of PubMedCentral, an open access biomedical literature database containing full-text articles, to provide researchers a useful tool in looking into details of supporting evidences for scientific findings.
image retrieval data mining text mining
Zhong Huang
College of information science and technology Drexel University Philadelphia, PA 19104 USA
国际会议
成都
英文
111-114
2011-01-14(万方平台首次上网日期,不代表论文的发表时间)