Legal information retrieval system relevant to R&D projects based on word-embedding of core terms

Generally, Research and development projects have relationship with statutes. Sometimes, new technologies developed in R&D projects can't be applied because they are restricted by newly enacted statutes. The situation comes from the fact that researchers don't know well about statutes that might affect their R&D projects. Therefore, we proposed a methodology to find relevant statutes with the R&D plan, based on cosine similarity of document vectors. R&D plan is a document which is written by researchers before they get into R&D, and it contains the main concepts about the project. In our method, a R&D plan is represented as a vector using network centrality. Then cosine similarity between the vector and TF-IDF vectors of statutes is calculated. After the calculation, statutes are provided with their ranks based on similarity values, so researchers can review and check them with priority. Compared to our previous study, this study differs in that we applied new variants of vectors to enhance the performance of our methodology and find a better representation for documents.