SMaRT: A Framework for Social Media Based Recommender for Tourism

Renjith, Shini; Sreekumar, A.; Jathavedan, M.

doi:10.1007/978-3-030-49500-8_26

Cited by 4 publications

(3 citation statements)

References 42 publications

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“…Therefore, employing social media as a key marketing technique has effectively enhanced the brand recognition of Sam Poo Kong Temple and heightened tourists' inclination to visit this attraction. This highlights the significance of social media's influence in the tourist sector, particularly in appealing to millennial, who are a highly promising and engaged market demographic in the current digital age (Pramudhita, 2021;Renjith et al, 2021).…”

Section: Discussionmentioning

confidence: 95%

The Change of Millennial Tourist Interests in Sam Poo Kong Temple, Semarang

Gulo,

Octafian

2024

Pancasila Int. J. Appl. Soc. Sci.

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The advent of the fourth industrial revolution signifies not only significant technological progress compared to earlier eras, but also the ability to revolutionize traditional business practices. The Sam Poo Kong Temple, which was once intended as a site of prayer for Confucian adherents, has transformed into a well-liked tourist destination where people engage in selfie activities, thereby enhancing their social standing. This research aims to understand the factors influencing the change in millennial tourists' interest towards Sam Poo Kong Temple. To evaluate the impact of social media usage and digital technology on the interests and behaviors of millennial tourists. To identify the preferences and motivations of millennial tourists in choosing tourist destinations such as Sam Poo Kong Temple. This study employs a qualitative methodology using a case study technique. Data is gathered via extensive interviews with relevant individuals, including temple administrators, tour guides, and tourists, with a particular focus on millennial. The findings indicate that social media plays a key role in marketing Sam Poo Kong Temple and attracting millennial tourists' interest. The dissemination of engaging content such as photos, videos, and narratives on social media has increased the visibility of the temple and sparked significant interest from tech-savvy millennial. Sam Poo Kong Temple has transformed from a traditional place of worship into a highly sought-after tourist destination, especially for photo opportunities and showcasing social status on social media. This impacts the preferences and motivations of millennial tourists in selecting tourist locations, with a primary focus on architectural beauty, unique experiences, and visibility on social media.

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Section: Discussionmentioning

confidence: 95%

The Change of Millennial Tourist Interests in Sam Poo Kong Temple, Semarang

Gulo,

Octafian

2024

Pancasila Int. J. Appl. Soc. Sci.

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“…Text clustering can be leveraged in multiple business contexts, such as spam filtering, targeted advertisements, customer churn prediction, product/service recommendations, content grouping, and so on. We could find multiple articles explaining such applications, which include References 47–54.…”

Section: Related Workmentioning

confidence: 99%

Taxonomy grooming algorithm ‐ An autodidactic domain specific dimensionality reduction approach for fast clustering of social media text data

Renjith

Sreekumar

Jathavedan

2022

Concurrency and Computation

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Social media being the most eminent source toward the growth of big data is important for information retrieval‐based applications to improve the efficiency in proportional to the volume it must deal with. One way to achieve better performance is to upgrade the processing capacity and the alternative option is to improve the processing methodology. The latter can be achieved using smarter processing techniques and/or better algorithms. Reducing the data volume that needs to be processed is a good strategy and it can be achieved by extracting only the relevant information via user segmentation by adopting an appropriate clustering technique. However, while dealing with text content, clustering algorithms do suffer due to the very high dimensions to be dealt with. Since the domain‐specific aspects are getting lost while applying traditional dimensionality reduction approaches, it is important to device an alternate strategy. This work proposes a taxonomy grooming algorithm (TGA), an autodidactic domain‐specific dimensionality reduction approach, for fast clustering of social media text data. Our experiment results are very promising and the dimensionality reduction using TGA resulted in better results in comparison with the traditional dimensionality reduction approaches.

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“…Recommender system, as an effective tool, can customize the information provided for users based on their personal characters and necessities. Since recommender system emerged in the 1990s (Adomavicius & Tuzhilin, 2005), recommender systems have been applied in a variety of domains to tackle the information overload problem and ameliorate customer relationship, such as e-commerce (Guia et al, 2019), e-tourism (Renjith et al, 2020). Apart from creating profits for enterprises, recommender system can even save lives and make social impact (Vercruyssen et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

A Recommender System Based on Hesitant Fuzzy Linguistic Information with MAPPACC Approach

Xu¹,

Chen²,

He³

2020

STUD INFORM CONTROL

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Recommender systems can make contributions to enterprises by meeting the demands of users and improving their satisfaction. However, because of the uncertainty and complexity of users' preferences, the classical techniques are insufficient to sort out the suitable recommendations. Scholars have made progress to address uncertainty in recommender systems, but the existing studies neglected the uncertain linguistic information and failed to use them to efficiently provide personalized recommendations for individuals. Therefore, this paper demonstrates an item-based recommendation program combined with the Hesitant Fuzzy Linguistic Multi-criteria Analysis of Preferences by means of Pairwise Actions and Criterion Comparisons (HFL-MAPPACC) method to analyze hesitant fuzzy linguistic information. To provide personalized recommendations, preference degrees of the used items and tendency of evaluations are considered in the construction of this algorithm. Then, the proposed approach is implemented in a doctor recommender system to show its applicability. Ultimately, the validity of the proposed method and its superiority are discussed by comparative analyses.

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SMaRT: A Framework for Social Media Based Recommender for Tourism

Cited by 4 publications

References 42 publications

The Change of Millennial Tourist Interests in Sam Poo Kong Temple, Semarang

The Change of Millennial Tourist Interests in Sam Poo Kong Temple, Semarang

Taxonomy grooming algorithm ‐ An autodidactic domain specific dimensionality reduction approach for fast clustering of social media text data

A Recommender System Based on Hesitant Fuzzy Linguistic Information with MAPPACC Approach

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