Abstract
With the development of the Internet, technology, and means of communication, the production of tourist data has multiplied at all levels (hotels, restaurants, transport, heritage, tourist events, activities, etc.), especially with the development of Online Travel Agency (OTA). However, the list of possibilities offered to tourists by these Web search engines (or even specialized tourist sites) can be overwhelming and relevant results are usually drowned in informational "noise", which prevents, or at least slows down the selection process. To assist tourists in trip planning and help them to find the information they are looking for, many recommender systems have been developed. In this article, we present an overview of the various recommendation approaches used in the field of tourism. From this study, an architecture and a conceptual framework for tourism recommender system are proposed, based on a hybrid recommendation approach. The proposed system goes beyond the recommendation of a list of tourist attractions, tailored to tourist preferences. It can be seen as a trip planner that designs a detailed program, including heterogeneous tourism resources, for a specific visit duration. The ultimate goal is to develop a recommender system based on big data technologies, artificial intelligence, and operational research to promote tourism in Morocco, specifically in the Daraa-Tafilalet region.
Highlights
In the field of tourism, recommender systems could be a great help when planning a trip or searching for a service among many destinations, attractions, and activities[1].Strictly speaking, these systems are defined as information filtering systems that makeThe principle is to use the interests of a user collected during his navigation as inputs, to predict the degree of interest that this user may have for a given item[6]
This architecture is based on a hybrid recommendation approach, which aims to improve user access to tourism resources in information retrieval systems, such as tourism portals and service providers’ documentary Extranets
When preparing a trip, we start by researching sites, portals, and mobile applications to get information and make choices, we prepare our itinerary on the spot with services and personalized content, and we finish by multiplying ourselves on social networks, blogs, and forums
Summary
In the field of tourism, recommender systems could be a great help when planning a trip or searching for a service among many destinations, attractions, and activities[1].Strictly speaking, these systems are defined as information filtering systems that makeThe principle is to use the interests of a user collected during his navigation as inputs, to predict the degree of interest that this user may have for a given item[6]. In the field of tourism, recommender systems could be a great help when planning a trip or searching for a service among many destinations, attractions, and activities[1]. Speaking, these systems are defined as information filtering systems that make. The approaches used to estimate these degrees of appreciation are numerous They are traditionally classified by the literature into several categories according to the source of information used[3,7]. One of these approaches is based on ratings given by a set of users on a set of items. It consists in recommending to a given user the items that have been highly evaluated in the past by other users who have similar preferences, we speak here about collaborative
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