Development and improvement of a memorandum text retrieval system for business records

Abstract

We describe a new information retrieval system to utilize business records.NAL, the target company of this study, is engaged in contract work for automobile maintenance.NAL undertakes contracts for comprehensive car maintenance with many companies that has cars.The goal of this system is to make it possible to support decision-making.We made a system to search similar sentences in the memorandum text in the business record.The user can find similar situations in the past with the current situation.We use BERT, a transformer neural network, to implement semantic search.However, our trial system could not find the appropriate sentence because the queries or memorandum tests contain the company-specific jargon and abbreviations used in NAL.We proposed a method to improve the semantic search by using Sentence-BERT and creating training data from a small jargon dictionary and a general similar sentence dataset.