Impact Mining for Supporting Literature-based Discovery
Date Issued
2012
Date
2012
Author(s)
Guo, Tai-Ying
Abstract
Scientific literature has growth rapidly in the past century, and a great deal of knowledge can support medical researchers to keep up with up-to-date information. This large volume of data is difficult to discover hidden relationships. To overcome this problem, Swanson proposed a method called literature-based discovery in 1986 to support researchers an effective way to uncovering new, potentially meaningful relationships. After Swanson proposed this method, other researchers also try to improve the result from literature-base discovery or develop new method to improve.
Researchers could employ literature-based discovery to support them reduce the time of discovering hidden relationships. But literature-based discovery method could not provide more information such as fish oil and blood viscosity is a suppressing relationship because fish oil can decrease blood viscosity. The kind of relationship we defined as impact relationship. Therefore, this study proposed a LBD (Impact) technique which is based on the concept of literature-based discovery and this technique can extract impact relationship to support researchers easier to analyze large volume of data. First, we apply literature-based discovery to retrieve related medical concepts. Subsequently, we use our proposed technique to extract impact relationship then order medical concepts in an appropriate way.
We construct two scenarios to evaluate our proposed LBD (Impact) technique, disease-chemicals and drugs scenario and drug-chemicals and drugs scenario. In disease-chemicals and drugs scenario, researchers usually focus on which drug can cure disease. And our proposed technique can rank drugs that can cure disease at higher rank. In the other scenario, drug-chemicals and drugs scenario, although the experiment result is not better than disease-chemicals and drugs scenario, we still can provide a better result to researchers. For researchers, they usually pay more attention on top 100 or 300. In this study, our proposed technique can provide a better result for researchers.
Subjects
Literature-based discovery
Impact mining
Medical literature mining
Type
thesis
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