Takanobu Watanabe

Shin Kamada, Takumi Ichimura, Takanobu Watanabe

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.

Shin Kamada, Takumi Ichimura, Takanobu Watanabe

An acquisition of a research grant is important for the researchers to conduct a research. The university will build up the organization and reinforce the acquirement of external funds. The researcher becomes aware of grant information and should investigate what kinds of grant it is. Therefore, the staff at the support center for the Industry-Academia collaboration will classify the grant into some categories according to the research fields. However, the task is difficult to realize the matching of the research fields, because the expert knowledge is required to completely classify them. We have developed recommendation system of Grant-in-Aid system for researchers by using JSPS (Japan Society for the Promotion of Science) keywords. The characteristic keywords are extracted from web sites and then the association rules between researchers and grants are determined in the IF-THEN rule format. This paper discusses the experimental results by using the developed system.