Color Imagery for Destination Recommendation in Regional Tourism

This paper presents a novel recommender service system that considers the image as a uniform representation for tourists’ expectations, destinations, and local tourism SMEs. Images carried by each stakeholder role is modeled and managed by several system modules, and they also evolve to reflect the real time situations of each entity. In addition, the system is dynamic in terms of its emphasis on the dynamic relationships among these roles and entities. When interactions occur, image mixing will be conducted to derive extra image attributes for the adjustments of the images. Besides, since colors can be mapped onto emotions, this paper adopts colors to operate the image matching and mixing process in order to find good matches of destinations for the recommendations meeting the tourists’ emotional needs. Although this image related approach we proposed is used in tourism domain, we believe our method could also contribute to other areas of either practical applications or academic studies

Color imagery for destination recommendation in regional tourism

本研究提出一創新的旅遊推薦服務系統，以意象模型作為旅客意象(包含自我意象和情感需求)、景點意象、以及中小企業所提供服務之意象在系統裡的一致性表達。以上所提及之利益關係人的意象會經由數個系統模組進行建立與管理，並演化以反映出意象擁有者在真實世界的狀態。除此之外，本系統為動態運行，強調旅遊產業裡各個利益關係人角色之間的互動關係。每當互動發生，相關意象模型會進行混合，演繹出額外的意象屬性，以進行意象模型之調整。另外，基於顏色與情緒可相互對應的相關研究，我們將色彩理論運用於意象媒合與意象混合模組之中，藉此為旅客推薦符合其情感需求的旅遊景點或服務。本研究所提出一系列基於意象衍伸的系統化方法，可被應用於各種不同的領域。我們相信本研究可以為其它領域之實務應用與學術探討帶來顯著的貢獻。This research presents a recommendation service system that considers the image as a uniform representation of tourist images (include self-image and emotional needs), destinations, and local SMEs. Images carried by each stakeholder roles are modeled and managed by several system modules, and they also evolve to reflect the real time situations of each entity. In addition, the system is dynamic in terms of its emphasis on the relationships among these roles. When interactions occur, image mixing will be conducted to derive extra image attributes for the adjustments of the images. Besides, since colors can be mapped onto emotions, we use colors to operate the image matching and mixing process to find good matches of destinations for the recommendation. This image related approach we proposed is domain-independent. We believe our method could contribute to other areas of practical applications and academic studies