Location and Activity Recommendation by Using Consecutive Itinerary Matching Model

Location and Activity Recommendation by Using Consecutive Itinerary Matching Model

許多人都有過這樣的經驗，因為事前未詳細規劃旅遊行程而導致不知道該選擇何處或何種活動做為下一步行程。本研究提出連續行程媒合模型（CIMM），針對行動裝置使用者當下最新的打卡資訊，找出使用者下一步的地點及活動需求。雖然我們提出的CIMM在初步的實驗指得到的30%的top-1 inclusion rate，但是我們利用打卡資訊探勘連續行程，然後推薦給行動裝置使用者及時的下一步地點及活動需求卻是一項創新技術。

In fact, most people have had the experience that they haven't made detailed itinerary in advance before a journey, and as a result they don't know what place or what kind of activity is suitable as the next visit location and activity after they engage in an activity in a certain place. To alleviate such problem, in this paper, we proposed the Consecutive Itinerary Matching Model to help mobile users find next locations and activities in line with their leisure needs. This model effectively utilizes time, location, user, and activity as features to find the most possible“Consecutive Itinerary”and then recommend mobile users next locations and activities. In this preliminary study, although our approach achieved only about 30% top-1 inclusion rate, however, to our knowledge, this work is novel for the recommendation of location and activity based on consecutive itinerary discovery from check-in data.