A Sightseeing Spot Recommendation System That Takes into Account the Visiting Frequency of Users

Kato, Yudai; Yamamoto, Katsumi

doi:10.3390/ijgi9070411

Cited by 14 publications

(20 citation statements)

References 18 publications

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“…The ease of receiving spatial information can prompt users to visit popular sightseeing websites. Therefore, Kato and Yamamoto [11] proposed the development a sightseeing spot recommendation system that could be useful and efficient for tourists. In the study, they an integrated social networking service, a web-geographic information system, and a recommendation system for interactive maps.…”

Section: Maps and Interactionsmentioning

confidence: 99%

Modern Cartographic Forms of Expression: The Renaissance of Multimedia Cartography

Medyńska-Gulij

Forrest

Cybulski

2021

IJGI

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This article summarizes the Special Issue of “Multimedia Cartography”. We present three main research fields in which multimedia cartography and the study of the effectiveness of multimedia maps are currently taking place. In each of these fields, we describe how published research is embedded in the broader context of map design and user studies. The research refers to contemporary technological trends such as web HTML5 standards, virtual reality, eye tracking, or 3D printing. Efficiency, performance, and usability studies of multimedia maps were also included. The research published in this issue is interdisciplinary. They combine traditional mapping methods with new technologies. They are searching for new places for cartography in, e.g., the environment of computer games. They combine the design of the map with its perception by users.

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Section: Maps and Interactionsmentioning

confidence: 99%

Modern Cartographic Forms of Expression: The Renaissance of Multimedia Cartography

Medyńska-Gulij

Forrest

Cybulski

2021

IJGI

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“…A smart recommendation system that provides suitable tourist attraction and route recommendations for tourists is a research highlight in the field of smart tourism [1]. It can automatically provide potentially interesting tourist attractions for tourists and offer them a convenient service.…”

Section: Introductionmentioning

confidence: 99%

“…Analyzing the related work, it can be seen that the tourism recommendation method has the following problems. Problem (1): Previous studies mainly focus on the principle and theory of the collaborative filtering algorithm in terms of the aspects of algorithm efficiency, accuracy, data sparsity, and the cold start problem. Problem (2): The collaborative filtering algorithm is still a fuzzy recommendation mode without high accuracy.…”

Section: Introductionmentioning

confidence: 99%

“…Step 5: Continue generating neighborhood units until all the points converge. Figure 2 is an example to form the space C. Figure 2a-f illustrate the process of forming the cellular unit (1) C , and Figure 2g-h illustrate the topological process of forming the cellular space C based on the cellular unit (1) C . C , and (g,h) illustrate the topological process of forming the cellular space C based on the cellular unit (1) C .…”

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confidence: 99%

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A Smart Tourism Recommendation Algorithm Based on Cellular Geospatial Clustering and Multivariate Weighted Collaborative Filtering

Zhou

Tian

Peng

et al. 2021

IJGI

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Tourist attraction and tour route recommendation are the key research highlights in the field of smart tourism. Currently, the existing recommendation algorithms encounter certain problems when making decisions regarding tourist attractions and tour routes. This paper presents a smart tourism recommendation algorithm based on a cellular geospatial clustering and weighted collaborative filtering. The problems are analyzed and concluded, and then the research ideas and methods to solve the problems are introduced. Aimed at solving the problems, the tourist attraction recommendation model is set up based on a cellular geographic space generating model and a weighted collaborative filtering model. According to the matching degree between the tourists’ interest needs and tourist attraction feature attributes, a precise tourist attraction recommendation is obtained. In combination with the geospatial attributes of the tourist destination, the spatial adjacency clustering model based on the cellular space generating algorithm is set up, and then the weighted model is introduced for the collaborative filtering recommendation algorithm, which ensures that the recommendation result precisely matches the tourists’ needs. Providing precise results, the optimal tour route recommendation model based on the precise tourist attraction approach vector algorithm is set up. The approach vector algorithm is used to search the optimal route between two POIs under the condition of multivariate traffic modes to provide the tourists with the best motive benefits. To verify the feasibility and advantages of the algorithm, this paper designs a sample experiment and analyzes the resulting data to obtain the relevant conclusion.

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“…Similarly, several real estate companies are showcasing furnished interior spaces to potential buyers by using panoramic images; this helps customers visualize the actual setting of the houses they are interested in [2]. These multimedia approaches integrating image, video, audio, and animations can further obtain better presentation and communication methods [3][4][5][6][7], such as visualization, map, graphical user interfaces, interactive recommendation system, etc.…”

Section: Introductionmentioning

confidence: 99%

Panoramic Mapping with Information Technologies for Supporting Engineering Education: A Preliminary Exploration

Lai

Peng

Chang

et al. 2020

IJGI

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The present researchers took multistation-based panoramic images and imported the processed images into a virtual tour platform to create webpages and a virtual reality environment. The integrated multimedia platform aims to assist students in a surveying practice course. A questionnaire survey was conducted to evaluate the platform’s usefulness to students, and its design was modified according to respondents’ feedback. Panoramic photos were taken using a full-frame digital single-lens reflex camera with an ultra-wide-angle zoom lens mounted on a panoramic instrument. The camera took photos at various angles, generating a visual field with horizontal and vertical viewing angles close to 360°. Multiple overlapping images were stitched to form a complete panoramic image for each capturing station. Image stitching entails extracting feature points to verify the correspondence between the same feature point in different images (i.e., tie points). By calculating the root mean square error of a stitched image, we determined the stitching quality and modified the tie point location when necessary. The root mean square errors of nearly all panoramas were lower than 5 pixels, meeting the recommended stitching standard. Additionally, 92% of the respondents (n = 62) considered the platform helpful for their surveying practice course. We also discussed and provided suggestions for the improvement of panoramic image quality, camera parameter settings, and panoramic image processing.

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A Sightseeing Spot Recommendation System That Takes into Account the Visiting Frequency of Users

Cited by 14 publications

References 18 publications

Modern Cartographic Forms of Expression: The Renaissance of Multimedia Cartography

Modern Cartographic Forms of Expression: The Renaissance of Multimedia Cartography

A Smart Tourism Recommendation Algorithm Based on Cellular Geospatial Clustering and Multivariate Weighted Collaborative Filtering

Panoramic Mapping with Information Technologies for Supporting Engineering Education: A Preliminary Exploration

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