現今推薦系統大多在於找出更有效率的演算法則來進行推薦，但在新使用者或新項目加入時，卻難以推薦有效的項目給使用者，容易產生冷開機(cold-start)問題。因此，現今推薦系統面臨的問題是如何改善系統限制問題並提升推薦效率。
在研究過程中發現，現今推薦系統尚未考慮到使用者生活層面而無法深入瞭解使用者喜好，導致降低推薦品質。因此，本研究將應用生活型態導入推薦系統中，予以深入探討使用者的特性及喜好，並發展以生活型態為核心之推薦系統來改善系統限制問題。本系統將應用博物館展示項目之推薦服務做為先導性研究，予以改善博物館標準化展示服務、提升參訪者的滿意度。
本研究透過生活型態的調查結果，找出四種族群的分群規則並建立其推薦路徑，據以建構成生活型態導覽推薦系統。研究結果顯示，生活型態導覽推薦系統在使用者觀看時間、各推薦項目滿意度評比分數，均顯著高於現今推薦系統。因此，研究發現將生活型態導入推薦系統後，能夠有效解決現今系統的限制問題，並提升系統的推薦成效。

The recommendation systems modify the algorithms to increase recommended efficiency. However, when there are new users or new displaying contents added in, it is hard to recommendation items to new users effectively and caused a “cold-start” problem. Therefore, the recommendation system faces a problem how to improve the system limitation problem and increased the efficiency of recommendation.
In this study, the recommendation system did not take the lifestyle of the users into consideration, it is unable to know the actual factors of the favorite recommended items of the users thus it tended to decrease the recommendation quality in practical. Therefore, we applied the concept of lifestyle merge the recommendation system to find out the demands of users and solve the system limitation problems. We will take the museum displaying items recommend as a plot study. It improve the standard of displaying items and increase satisfaction of visit。
The results of study showed: We found out the group classification rules and the recommendation way, and develop a Lifestyle-oriented recommendation system. In the result, the Lifestyle-oriented recommendation system was higher than the current recommendation system significantly. Therefore, the Lifestyle-oriented recommendation system can solve the system limitations problems effectively, and increased the efficiency of recommendation.

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