Extraction of Word Set for Increasing Human-Computer Interaction in Information Retrieval

We present a mechanism that provides word sets which can make human-computer interaction more active in the course of information retrieval, with natural language processing technology and a mathematic measure for calculating degree of inclusion. We show what type of words should be added to the current query, i.e. keywords which previously had been input, in order to make human-computer interaction more creative. We try to extract related word sets with taxonomical and non-taxonomical relations from documents by employing case-marking particles derived from syntactic analysis. Then, we verify which kind of related words is more useful as an additional word for retrieval support and makes human-computer interaction more fruitful.