Recommendation of Heterogeneous Cultural Heritage Objects for the Promotion of Tourism

Abstract

The cultural heritage of a region, be it a highly visited one or not, is a formidable asset for the promotion of its tourism. In many places around the world, an important part of this cultural heritage has been catalogued by initiatives backed by governments and organisations. However, as of today, most of this data has been mostly unknown, or of difficult access, to the general public. In this paper, we present research that aims to leverage this data to promote tourism. Our first field of application focuses on the French Pyrenees. In order to achieve our goal, we worked on two fronts: (i) the ability to export this data from their original databases and data models to well-known open data platforms; and (ii) the proposition of an open-source algorithm and framework capable of recommending a sequence of cultural heritage points of interests (POIs) to be visited by tourists. This itinerary recommendation approach is original in many aspects: it not only considers the user preferences and popularity of POIs, but it also integrates different contextual information about the user as well as the relevance of specific sequences of POIs (strong links between POIs). The ability to export the cultural heritage data as open data and to recommend sequences of POIs are being integrated in a first prototype.

Context-aware and Ontology-based Recommender System for e-Tourism

“…Some proposals are supported on users' interaction to obtain their data (i.e., following a PULL paradigm). In (Rajaonarivo et al, 2019), authors model the users' information considering their gender, age category (e.g., kid, adult, or elderly), and preferences, classified as thematic preferences (e.g., museum, theater) and historical preferences (e.g., 12th century), that have to be provided by them through a user interface. In (Santos et al, 2019), only health, physical, and psychological conditions are required with forms filled by users.…”

“…In order to improve suggestions, the trend is to consider context aspects that describe a specif situation in a determined moment for a user, including transportation media, weather, time, or even health conditions. Many works use context-modeling approaches that mainly consider means of transportation, travel time, location, or weather (Bahramian et al, 2017;Kesorn et al, 2017;Arigi et al, 2018;Logesh et al, 2018;Rajaonarivo et al, 2019;Logesh and Subramaniyaswamy, 2019).…”

“…It starts to be a trend to recommend POI. The model considered in (Rajaonarivo et al, 2019), con-siders previous activity of other users to recommend tours of POI, thus reducing overspecialization and increasing serendipity, however experiments with this feature were not made. Authors of (Shen et al, 2016) assert that the proposed system is able to recommend fresh and surprise POI, based on collective intelligence.…”

“…Some systems only count on ontologies to represent tourism POI (García-Crespo et al, 2009;Bahramian et al, 2017;Arigi et al, 2018;Rajaonarivo et al, 2019). Other works consider user profile ontologies, besides tourism ontologies, such in (Ruotsalo et al, 2013).…”

The Navigation of Multi-itineraries for the Cultural Heritage Context

“…In this early phase of our work we focused on the user experience. At variance in respect to [ 7 , 9 , 10 ], the faceted search, the query results, and the itinerary preview are all shown in the same page, in order to facilitate query insertion and path selection. The SearchPath service is the only tourist application that supports a multi-path preview that enables the users to easily compare and select different paths.…”