Abstract
Online hotel reservation makes travel easier, But a large number of online hotel information also makes people become unable to follow. Online hotel reservation websites need try to gain exposure to customers' eyes and recommend a personalized hotel list. Nowadays, Personalized Intelligent Hotel Recommendation Systems have been researched widely, but rarely in online hotel reservation. The paper summarizes representative online hotel reservation websites' personalized recommendation system situation, such as qunar, kuxun, ctrip and elong etc. personalized recommendation have poor performance. This research firstly extracts Hotel Characteristic factor , attempts to analyze customers' browsing and purchasing behaviors and secondly constructs a personalized online hotel marketing recommendation system polymerization model for Multi-level customer ,at last presents an achieve Matlab procedure implementing the core arithmetic of the personalized recommendation.
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