RECOMMENDATION METHOD FOR ITEMS BASED ON PREDICTED PREFERENCE CONTRAST OF SIMILAR GROUPS

摘要

The present invention relates to an item recommendation providing method based on a predicted preference contrast of similar groups which calculates a completed predicted preference from real preferences granted by all users for an item, and when recommending a specific item to a specific user, recommends an item with highest preference among items having highest similarity and lower real preferences than predicted preference. The method comprises: (a) receiving preference data of users for an item; (b) using a matrix completion and clustering algorithms and producing a completed predicted preference matrix from an incomplete preference matrix granted by multiple users for multiple items; (c) calculating similarity between items by calculating cosine similarity between all items; and (d) when recommending a specific item, recommending the same along with an item which has the highest cosine similarity with the specific item and has the highest real preference among items having a lower real preference than a predicted preference for the specific item. By such method, the present invention informs users of an item that provides a better experience, along with a recommended item, thereby providing a better user experience compared with a recommending method by the existing technology.;COPYRIGHT KIPO 2016