Topic Word Extraction using World Wide Web Search Rankings for Computer Conversations

摘要

This paper proposes a method of extracting Web search keywords of interest by gender, age, and day of the week. By using the results of such keywords, it is expected that suitably equipped robots will be able to offer appropriate topics of conversation to the person they are interacting with. In this study, we compiled Web search engine keywords based on rank using the Biglobe Search Shunkan Ranking system. However, such rankings cannot be used independently because the relevant words for a particular day will not be known until that day is over. Accordingly, our method uses Web search rankings compiled for the day prior to day in question to select keywords for use. Because of this, the method cannot determine keywords that appear on the actual day of the conversation. However, it can extract keywords that appear repeatedly in identifiable patterns, as well as topics of general interest to a certain age and gender. In our experiments, we experienced particularly good results by focusing on three concepts: keyword consolidation, forgetting factor, and short-term and long-term memory.