CoIN: A network analysis for document triage

Yi Yu Hsu, Hung Yu Kao

研究成果: Article同行評審

4 引文 斯高帕斯(Scopus)

摘要

In recent years, there was a rapid increase in the number of medical articles. The number of articles in PubMed has increased exponentially. Thus, the workload for biocurators has also increased exponentially. Under these circumstances, a system that can automatically determine in advance which article has a higher priority for curation can effectively reduce the workload of biocurators. Determining how to effectively find the articles required by biocurators has become an important task. In the triage task of BioCreative 2012, we proposed the Co-occurrence Interaction Nexus (CoIN) for learning and exploring relations in articles. We constructed a co-occurrence analysis system, which is applicable to PubMed articles and suitable for gene, chemical and disease queries. CoIN uses co-occurrence features and their network centralities to assess the influence of curatable articles from the Comparative Toxicogenomics Database. The experimental results show that our network-based approach combined with co-occurrence features can effectively classify curatable and non-curatable articles. CoIN also allows biocurators to survey the ranking lists for specific queries without reviewing meaningless information. At BioCreative 2012, CoIN achieved a 0.778 mean average precision in the triage task, thus finishing in second place out of all participants.

原文English
文章編號bat076
期刊Database
2013
DOIs
出版狀態Published - 2013

All Science Journal Classification (ASJC) codes

  • 資訊系統
  • 一般生物化學,遺傳學和分子生物學
  • 一般農業與生物科學

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