Category Reformation using Purchase Logs

In item searches on shopping sites, customers must find the items they want from among many products. As one method of narrowing down products, the customer currently selects a category and posts queries related to the item in it. However, in such narrowing down method searches for products, the customer needs to know the category to narrow down the shopping sites. In this paper, after a customer posts a query related to a product, the shopping site recommends a word that is closely related to a new category generated from a query log, and we propose a new search method to combine category and keyword searches. Our evaluation experiment using actual data shows that the categories proposed by recommendations provide sufficient information quantity.