Classification of research methodology?
Classifying research papers into patent classification systems
enables an exhaustive and effective invalidity search, prior art
search, and technical trend analysis. However, it is very costly to
classify research papers manually. Therefore, we have studied
automatic classification of research papers into a patent
classification system. To classify research papers into patent
classification systems, the differences in terms used in research
papers and patents should be taken into account. This is because
the terms used in patents are often more abstract or creative than
those used in research papers in order to widen the scope of the
claims. It is also necessary to do exhaustive searches and analyses
that focus on classification of research papers written in various
languages. To solve these problems, we propose some classification
methods using two machine translation models. When translating
English research papers into Japanese, the performance of a
translation model for patents is inferior to that for research
papers due to the differences in terms used in research papers and
patents. However, the model for patents is thought to be useful for
our task because translation results by patent translation models
tend to contain more patent terms than those for research papers.
To confirm the effectiveness of our methods, we conducted some
experiments using the data of the Patent Mining Task in the NTCIR-7
Workshop. From the experimental results, we found that our method
using translation models for both research papers and patents was
more effective than using a single translation model.