What is of interest for tourists in an alpine destination: personalized recommendations for daily activities based on view data

Majeed, Tahir; Stämpfli, Aline E.; Liebrich, Andreas; Meier, René

doi:10.1007/s12652-019-01619-1

Cited by 4 publications

(2 citation statements)

References 39 publications

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“…Considerations on psychological factors when using applications in the reality-virtuality continuum are also being addressed more and more (Ibili and Billinghurst 2019;Hoppenstedt et al 2019). In addition to this, the behavior of mobile users should be generally considered in future for any mobile application (Beierle 2019;Majeed 2019). Finally, in patents, engineering aspects are also covered (Hill et al 2019).…”

Section: Related Workmentioning

confidence: 99%

Flexible development of location-based mobile augmented reality applications with AREA

Schickler

Reichert

Geiger

et al. 2020

J Ambient Intell Human Comput

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Mobile applications have garnered a lot of attention in the last years. The computational capabilities of mobile devices are the mainstay to develop completely new application types. The provision of augmented reality experiences on mobile devices paves one alley in this field. For example, in the automotive domain, augmented reality applications are used to experience, inter alia, the interior of a car by moving a mobile device around. The device’s camera then detects interior parts and shows additional information to the customer within the camera view. Another application type that is increasingly utilized is related to the combination of serious games with mobile augmented reality functions. Although the latter combination is promising for many scenarios, technically, it is a complex endeavor. In the AREA (Augmented Reality Engine Application) project, a kernel was implemented that enables location-based mobile augmented reality applications. Importantly, this kernel provides a flexible architecture that fosters the development of individual location-based mobile augmented reality applications. The work at hand shows the flexibility of AREA based on a developed serious game. Furthermore, the algorithm framework and major features of it are presented. As the conclusion of this paper, it is shown that mobile augmented reality applications require high development efforts. Therefore, flexible frameworks like AREA are crucial to develop respective applications in a reasonable time.

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Section: Related Workmentioning

confidence: 99%

Flexible development of location-based mobile augmented reality applications with AREA

Schickler

Reichert

Geiger

et al. 2020

J Ambient Intell Human Comput

View full text Add to dashboard Cite

show abstract

“…With the development of information technology, the Internet is becoming an important source for people to plan their travels [2]. In the field of tourism, various forms of tourism temporal and spatial trajectory data have been formed, such as GPS trajectory, BeiDou navigation information, and check-in records.…”

Section: Introductionmentioning

confidence: 99%

Personalized Travel Recommendation Based on the Fusion of TGI and POI Algorithms

Lü¹,

Zhang

2022

Wireless Communications and Mobile Computing

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On the way to travel, the public expect to get a tourism experience with low cost, convenient travel, and high comfort. At the same time, they also have different tourism needs such as history and culture, natural landscape, and food shopping. To address the problem that traditional travel route recommendation algorithms have limited accuracy and only analyze text or pictures alone, we propose a personalized travel route recommendation algorithm that integrates text and photo information from travelogues and obtain the historical tourism footprint of tourists by analyzing travel notes. According to the frequency and cooccurrence of scenic spots in the travel notes and the number of photos taken by each scenic spot, the popularity of scenic spots and the interest preferences of various types of tourists are analyzed. Under the given starting and ending points or passing points, the optimal tourism route generation method is designed. Experiments on the real data set of Ctrip Travel website show that the recommendation accuracy of this algorithm is significantly improved compared with the traditional algorithm which only uses travel notes text or photos. Compared with the algorithm that only considers the popularity of interest points or tourists’ interest preferences, the accuracy of the route recommended by the algorithm is improved. Compared with the algorithm that only considers the cooccurrence of scenic spots or only considers the influence of photos, this algorithm can obtain a better popularity score of scenic spots. This method integrates the two kinds of information including picture and text, fully considering the interest of users with high practicability.

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A collaborative filtering recommendation algorithm based on normalization approach

Panda

Bhoi

Singh

2020

J Ambient Intell Human Comput

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What is of interest for tourists in an alpine destination: personalized recommendations for daily activities based on view data

Cited by 4 publications

References 39 publications

Flexible development of location-based mobile augmented reality applications with AREA

Flexible development of location-based mobile augmented reality applications with AREA

Personalized Travel Recommendation Based on the Fusion of TGI and POI Algorithms

A collaborative filtering recommendation algorithm based on normalization approach

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