The purpose of research on biomedical literature-based discovery is to bring out new knowledge from the existing biomedical information. Beginning with Dr. Swanson's ABC model, many studies extended or applied the ABC model to find new associations between biomedical entities. While the methods applied to data have advanced, in most cases biomedical literature has been used for the text data. Assuming that web crawl data is helpful in studying literature-based discovery as well as biomedical literature which is the existing but rather limited data source, we discovered new disease-drug associations using web crawl data in addition to biomedical literature. We also analyzed how helpful the additional use of web crawl data is for biomedical literature mining. Literature-based discovery using web crawl data has its significance as a pioneering work utilizing new data.
|Title of host publication||2016 Symposium on Applied Computing, SAC 2016|
|Publisher||Association for Computing Machinery|
|Number of pages||6|
|Publication status||Published - 2016 Apr 4|
|Event||31st Annual ACM Symposium on Applied Computing, SAC 2016 - Pisa, Italy|
Duration: 2016 Apr 4 → 2016 Apr 8
|Name||Proceedings of the ACM Symposium on Applied Computing|
|Other||31st Annual ACM Symposium on Applied Computing, SAC 2016|
|Period||16/4/4 → 16/4/8|
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2015R1A2A1A05001845). We also appreciate Mr. Junsik Kim's proofreading efforts.
© 2016 ACM.
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