Now, searching for what you want, there is a convenient thing called the Internet. When searching, enter “keyword” such as “bag” or “T shirt”. But here is a little problem.
Even saying “bag”, there are various kinds as rucksacks, tote bags and handbags. Also the design is various. Like a backpacks and tote bags, “what you can be expressed by words” can be narrowed down by keywords. However, it is difficult to express the design in words. Even if expressed in words like “cool bags” or “pretty bags”, there are individual differences such as “I think it is cool, other don’t think so much”.
The sensitivity of people is different. Modern search systems don’t fully understand human sensitivity and show search results.
In this kind of search system, we are conducting research related to basic model of system that can understand people’s sensitivity and can recommend products. So far, we have proposed and verified a model called Kansei retrieval agent. At first, Kansei retrieval agent learns the tendency of evaluation on user’s data. After that, the agent acts like a concierge to search what the user likes from a huge database instead of the user.
System outline of Kansei retrieval agent.
Various meta-heuristics techniques such as evolutionary computation and pattern recognition are applied to the Kansi retrieval agent.