On Ontology-Based Tourist Knowledge Representation and Recommendation

Pai, Mao Yuan; Wang, Ding Chau; Hsu, Tz Heng; Lin, Guan-Bo; Chen, Chao‐Chun

doi:10.3390/app9235097

Cited by 6 publications

(6 citation statements)

References 31 publications

(64 reference statements)

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“…OWL, SWRL, Linked data (Pai et al, 2019) An ontology is applied to recommend tourist knowledge in order to assist making the appropriate travel decision. OWL Ontology, which models the possible product compositions (Ardito et al, 2011) It models the possible product compositions that users can perform to support creating products that best meet their desires.…”

Section: Rdf/rdfs Owl Sparqlmentioning

confidence: 99%

Application of Semantic Web Technologies for Supporting Customer Relationship Management: a Systematic Literature Review

Georgieva-Trifonova,

Petrov,

Milev

2023

BRAIN

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The purpose of the present paper is to summarize the current state of the existing research on the application of Semantic web technologies in supporting customer relationship management. Its achievement includes providing answers to a set of research questions as a result of conducting a systematic literature review. A total of 44 scientific publications are identified as relevant to the topic and included in the review. Information is extracted from the selected literature sources, which is then summarized, systemized and analyzed according to the predefined research questions and finally reported. The conducted systematic literature review determines that the development of Semantic web technologies is provoked interest among researchers, as a result of which the advantages of using them for descriptions useful for various CRM purposes are investigated and practically confirmed. In addition to defining semantic models for descriptions supporting a variety of CRM activities and processes (such as customized products and services; supporting users of CRM systems; integrated offerings across channels; improved and innovative products and services; customer complaint management, etc.), various research works identify new approaches to support CRM, that can be achieved through the application of appropriate Semantic web technologies. The detailed study represented in this paper contributes to familiarization with the existing experience in the application of Semantic web technologies in supporting customer relationship management, as well as facilitates the discovery of trends and directions for future research. This is the reason for the expected interest from scientists whose research area cover the considered and similar fields; software engineers implementing CRM systems; data analysts exploring CRM domain.

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Section: Rdf/rdfs Owl Sparqlmentioning

confidence: 99%

Application of Semantic Web Technologies for Supporting Customer Relationship Management: a Systematic Literature Review

Georgieva-Trifonova,

Petrov,

Milev

2023

BRAIN

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“…Moreover, Nisar et al (2019) state that KM systems based on user-generated content are characterised by information richness and informal communication. In this way, eWOM has become the most important source of consumer and travellers' knowledge (Pai et al, , 2019. It can be considered a customer KM tool as it embraces the three levels of customer knowledge: knowledge for customers, knowledge about customers and knowledge possessed by customers (You et al, 2012).…”

Section: Literature Reviewmentioning

confidence: 99%

The impact of electronic word-of-mouth management in hotel ecosystem: insights about managers' decision-making process

Manero

Tartaglione

Russo

et al. 2022

JIC

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PurposeThere is a lack of research proving how electronic word-of-mouth (eWOM) is a valuable source of information in the hospitality industry for developing hotels' intellectual capital. To fill this gap, this study aims to examine hotel managers' decision-making processes regarding the acceptance and management of eWOM and its impact on the Italian hotel ecosystem.Design/methodology/approachThis work takes advantage of the previous contributions to present a hotel's decision-making process model regarding structural capital. It includes eWOM as a context variable and changes implemented as a dependent variable in a comprehensive model. The structural equation modelling applies to a database obtained through a survey addressed to Italian hotel managers.FindingsThe results show that eWOM plays an essential role in managers' motivations to explain hotel changes implementation. The hotel leverages eWOM information and interaction through structural, relational and human capital to enhance products, services and strategies.Research limitations/implicationsThis work contributes to the extant literature by providing a comprehensive framework to explain the consequences of eWOM knowledge management from the intellectual capital view in the Italian hotel ecosystem.Practical implicationsFor practitioners, this research demonstrates how hotel managers should accept and manage eWOM knowledge through intellectual capital to make determinant decisions that improve hotel performance.Originality/valueThere is a scarcity of research on modelling the acceptability and management of eWOM in the hotel ecosystem from practitioners' perspectives. This work is the first attempt to determine how eWOM knowledge management boosts hotel intellectual capital and improves service innovation and performance.

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“…Due to the large amount of OTR information, an ontology has been developed that uses a recommendation system to examine OTR content for popular attractions so that accurate and informed travel decisions may be made (Pai et al , 2019). In the field of gastronomic tourism, there is a framework for analyzing OTRs, extracting useful information from textual and para-textual elements, building a matrix of word frequencies and performing a quantitative and thematic content analysis (Marine-Roig et al , 2019).…”

Section: Related Workmentioning

confidence: 99%

Analyzing tourist data on Twitter: a case study in the province of Granada at Spain

Viñán-Ludeña

Campos

2021

JHTI

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PurposeThe main aim of this paper is to build an approach to analyze the tourist content posted on social media. The approach incorporates information extraction, cleaning, data processing, descriptive and content analysis and can be used on different social media platforms such as Instagram, Facebook, etc. This work proposes an approach to social media analytics in traveler-generated content (TGC), and the authors use Twitter to apply this study and examine data about the city and the province of Granada.Design/methodology/approachIn order to identify what people are talking and posting on social media about places, events, restaurants, hotels, etc. the authors propose the following approach for data collection, cleaning and data analysis. The authors first identify the main keywords for the place of study. A descriptive analysis is subsequently performed, and this includes post metrics with geo-tagged analysis and user metrics, retweets and likes, comments, videos, photos and followers. The text is then cleaned. Finally, content analysis is conducted, and this includes word frequency calculation, sentiment and emotion detection and word clouds. Topic modeling was also performed with latent Dirichlet association (LDA).FindingsThe authors used the framework to collect 262,859 tweets about Granada. The most important hashtags are #Alhambra and #SierraNevada, and the most prolific user is @AlhambraCultura. The approach uses a seasonal context, and the posted tweets are divided into two periods (spring–summer and autumn–winter). Word frequency was calculated and again Granada, Alhambra are the most frequent words in both periods in English and Spanish. The topic models show the subjects that are mentioned in both languages, and although there are certain small differences in terms of language and season, the Alhambra, Sierra Nevada and gastronomy stand out as the most important topics.Research limitations/implicationsExtremely difficult to identify sarcasm, posts may be ambiguous, users may use both Spanish and English words in their tweets and tweets may contain spelling mistakes, colloquialisms or even abbreviations. Multilingualism represents also an important limitation since it is not clear how tweets written in different languages should be processed. The size of the data set is also an important factor since the greater the amount of data, the better the results. One of the largest limitations is the small number of geo-tagged tweets as geo-tagging would provide information about the place where the tweet was posted and opinions of it.Originality/valueThis study proposes an interesting way to analyze social media data, bridging tourism and social media literature in the data analysis context and contributes to discover patterns and features of the tourism destination through social media. The approach used provides the prospective traveler with an overview of the most popular places and the major posters for a particular tourist destination. From a business perspective, it informs managers of the most influential users, and the information obtained can be extremely useful for managing their tourism products in that region.

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On Ontology-Based Tourist Knowledge Representation and Recommendation

Cited by 6 publications

References 31 publications

Application of Semantic Web Technologies for Supporting Customer Relationship Management: a Systematic Literature Review

Application of Semantic Web Technologies for Supporting Customer Relationship Management: a Systematic Literature Review

The impact of electronic word-of-mouth management in hotel ecosystem: insights about managers' decision-making process

Analyzing tourist data on Twitter: a case study in the province of Granada at Spain

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