Conventional decision support systems, however, aim at specialized user groups, e.g. marketing managers, whereas product finders focus on consumers.
Being part of an e-shop, a product finder ideally leads to an online buy, while conventional distribution channels are involved in product finders that are part of an online presentation (e.g. shops, order by phone).
The following list displays the main approaches, from simple ones to more complex ones, each with a typical example: Product finder has an important role in e-commerce, items has to be categorized to better serve consumer in searching the desired product, recommender system for recommending items based on their purchases etc.
A new method,[4] using hierarchical approach which decomposes the classification problem into a coarse level task and a fine level task, with the hierarchy made using latent class model discovery.
A simple classifier is applied to perform the coarse level classification (because the data is so large we cannot use more sophisticated approach due to time issue) while a more sophisticated model is used to separate classes at the fine level.