A Recommendation System of Grants to Acquire External Funds

by   Shin Kamada, et al.
Prefectural University of Hiroshima

The recommendation system of the competitive grants to university researchers by using the Grants-in-Aid for Scientific Research (KAKEN) keywords has been developed. The system can determine the recommendation order of researchers to each grant by the using the association rules between KAKEN application and various information from the web site of the corresponding grant. However, our developed previous system has some fatal errors in the retrieval algorithm. We modify the algorithm and extend the retrieval data for web mining. If the grant information is not enough to determine the relation, the system investigates the past KAKEN records in the database for the researcher who acquired the past grant. Moreover, the system retrieves the papers of the researchers to search their interests. As a result, the agreement degree of the researcher's interest to the grant increases. This paper discusses some simulation results.


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