A Personalized Heritage-Oriented Recommender System Based on Extended Cultural Tourist Typologies

Abstract

Recent developments in digital technologies regarding the cultural heritage domain have driven technological trends in comfortable and convenient traveling, by offering interactive and personalized user experiences. The emergence of big data analytics, recommendation systems and personalization techniques have created a smart research field, augmenting cultural heritage visitor’s experience. In this work, a novel, hybrid recommender system for cultural places is proposed, that combines user preference with cultural tourist typologies. Starting with the McKercher typology as a user classification research base, which extracts five categories of heritage tourists out of two variables (cultural centrality and depth of user experience) and using a questionnaire, an enriched cultural tourist typology is developed, where three additional variables governing cultural visitor types are also proposed (frequency of visits, visiting knowledge and duration of the visit). The extracted categories per user are fused in a robust collaborative filtering, matrix factorization-based recommendation algorithm as extra user features. The obtained results on reference data collected from eight cities exhibit an improvement in system performance, thereby indicating the robustness of the presented approach.

Tangible and Personalized DS Application Approach in Cultural Heritage: The CHATS Project

“…Therefore, the basic function of the CHATS personalization module is the definition of the user's requirements and characteristics by defining his profile. Most similar surveys have used the questionnaire to categorize users according to their answers [39,40,9,41]. Viewing a small questionnaire with simple but targeted questions about the user's profile and interests at the beginning of the CHATS application is a common and effective method in corresponding cases of personalized information to gather the necessary information about the user profile.…”

Understanding Preferences in Tourism Email Marketing

“…Ross [25]'s study on Alentejo in Portugal showed that more personalized individual-based guiding activities can be used in co-creating experiences by cultural tourism providers to deliver more meaningful experiences also appealing to visitors with alternative sets of beliefs and motivations. Konstantakis et al [26]'s work demonstrated that it is possible to provide higher quality and more relevant cultural recommendations when including information regarding the cultural background of tourists. In the context of audio tours, Shilov et al [27] proposed automatically generated personalized audio tours based on the context and tourists' preferences.…”

ACUX Typology: A Harmonisation of Cultural-Visitor Typologies for Multi-Profile Classification

“…The most recent CUX studies [3][4][5][6][7][8] show that users of applications and services of cultural content tend to carry their own cultural characteristics and preferences when visiting destinations of cultural interest, learn and interact differently with cultural content, thus obtaining a virtually unique cultural experience. To cope with this tendency, cultural spaces need to search for novel ways of providing more personalised experiences to their visitors [4,9,10]. To that end, various research efforts have been made to identify different profiles of cultural visitors based on their background and preferences, and classify them into distinct visitor types [9,[11][12][13][14][15][16] .…”

“…To cope with this tendency, cultural spaces need to search for novel ways of providing more personalised experiences to their visitors [4,9,10]. To that end, various research efforts have been made to identify different profiles of cultural visitors based on their background and preferences, and classify them into distinct visitor types [9,[11][12][13][14][15][16] .…”