Toward a semantic-based location tagging news feed system: Constructing a conceptual hierarchy on geographical hashtags

Davarpour, Mohammad Hossein; Sohrabi, Mohammad Karim; Naderi, Milad

doi:10.1016/j.compeleceng.2019.07.005

Cited by 3 publications

(1 citation statement)

References 23 publications

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“…In reality, other users are also searching for POIs that are near enough to their current location [77,78]. Only those users that are located close to GPS trajectories form their travel experiences pattern [11,17,20,[79][80][81]. The authors of [82] utilized the POIs' popularity to optimize the probability estimate of the relative distance between the recipient and the POI, taken from semantic tags.…”

Section: Location-basedmentioning

confidence: 99%

Systematic Review of Contextual Suggestion and Recommendation Systems for Sustainable e-Tourism

et al. 2021

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Agenda 2030 of Sustainable Development Goals (SDGs) 9 and 11 recognizes tourism as one of the central industries to global development to tackle global challenges. With the transformation of information and communication technologies (ICT), e-tourism has evolved globally to establish commercial relationships using the Internet for offering tourism-related products, including giving personalised suggestions. The contextual suggestion has emerged as a modified recommendation system that is integrated with information-retrieval techniques within large databases to provide tourists with a list of suggestions based on contexts, such as location, time of day, or day of the week (weekdays or weekends). This study surveyed literature in the field of contextual suggestion and recommendation systems with a focus on e-tourism. The concerns linked with approaches used in contextual suggestion and recommendation systems are highlighted in this systematic review, while motivations, recommendations, and practical implications in e-tourism are also discussed in this paper. A query search using the keywords “contextual suggestion system”, “recommendation system”, and “tourism” identified 143 relevant articles published from 2012 to 2020. Four major repositories are considered for searching, namely, (i) Science Direct, (ii) Scopus, (iii) IEEE, and (iv) Web of Science. This review was carried out under the protocols of four phases, namely, (i) query searching in major article repositories, (ii) removal of duplicates, (iii) scan of title and abstract, and (iv) complete reading of articles. To identify the gaps in current research, a taxonomy analysis was exemplified into categories and subcategories. The main categories were highlighted as (i) review articles, (ii) model/framework, and (iii) applications. Critical analysis was carried out on the basis of the available literature on the limitations of approaches used in contextual suggestion and recommendation systems. In conclusion, the approaches used are mainly based on content-based filtering, collaborative filtering, preference-based product ranking, and language modelling. The evaluation measures for the contextual suggestion system include precision, normalized discounted cumulative, and mean reciprocal rank, while test collections comprise Internet resources. Given that the tourism industry contributed to the environmental and social-economic development, contextual suggestion and recommendation systems have presented themselves to be relevant in integrating and achieving SDG 9 and SDG 11 in many ways such as web-based e-services by the government sector and smart gadgets based on reliable and real-time data and information for city planners as well as law enforcement personnel in a sustainable city.

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Section: Location-basedmentioning

confidence: 99%

Systematic Review of Contextual Suggestion and Recommendation Systems for Sustainable e-Tourism

et al. 2021

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Multi-Task Learning Framework for Detecting Hashtag Hijack Attack in Mobile Social Networks

Lyu

Chi

2022

2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS)

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Semantic Knowledge Graphs for the News: A Review

Opdahl

Al-Moslmi²,

Dang-Nguyen

et al. 2022

ACM Comput. Surv.

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ICT platforms for news production, distribution, and consumption must exploit the ever-growing availability of digital data. These data originate from different sources and in different formats; they arrive at different velocities and in different volumes. Semantic knowledge graphs (KGs) is an established technique for integrating such heterogeneous information. It is therefore well-aligned with the needs of news producers and distributors, and it is likely to become increasingly important for the news industry. This paper reviews the research on using semantic knowledge graphs for production, distribution, and consumption of news. The purpose is to present an overview of the field; to investigate what it means; and to suggest opportunities and needs for further research and development.

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Toward a semantic-based location tagging news feed system: Constructing a conceptual hierarchy on geographical hashtags

Cited by 3 publications

References 23 publications

Systematic Review of Contextual Suggestion and Recommendation Systems for Sustainable e-Tourism

Systematic Review of Contextual Suggestion and Recommendation Systems for Sustainable e-Tourism

Multi-Task Learning Framework for Detecting Hashtag Hijack Attack in Mobile Social Networks

Semantic Knowledge Graphs for the News: A Review

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