Smart Searching System for Virtual Science Brain
To decide research topics or analyze technical trends, researchers should collect and analyze information from hundreds of thousands of articles, patents, and technical reports. To facilitate the process, information extraction techniques from literature are very helpful. In addition, effective searching methods of the extracted information are necessary as well. While information extraction research has been a popular issue, research about searching and browsing methods for the extracted information has not been an attractive issue relatively. This paper presents a smart searching system that provides various analysis tools, and we expect that researchers can discover and develop new research outcomes through the proposed searching system.
KeywordsInformation Extraction Entity Recognition Natural Language Processing Technique Dynamic Table Event Ontology
Unable to display preview. Download preview PDF.
- 2.Chun, H.-W., Tsuruoka, Y., Kim, J.-D., Shiba, R., Nagata, N., Hishiki, T., Tsujii, J.: Automatic recognition of topic-classified relations between prostate cancer and genes using MEDLINE abstracts. BMC Bioinformatics 7(suppl. 3), S4 (2006)Google Scholar
- 4.Yoshida, K., Tsujii, J.: Reranking for Biomedical Named-Entity Recognition. In: BioNLP (2007)Google Scholar
- 6.Kim, J.-D., Ohta, T., Teteisi, Y., Tsujii, J.: GENIA Ontology. Technical Report(TR-NLP-UT-2006-2). Tsujii Laboratory, University of Tokyo (2006)Google Scholar