Augmented context-based recommendation service framework using knowledge over the Linked Open Data cloud

Sohn, Mye M.; Jeong, Sunghwan; Kim, Jongmo; Lee, Hyun Jung

doi:10.1016/j.pmcj.2015.07.009

Cited by 6 publications

(5 citation statements)

References 27 publications

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“…Only 19 articles mention service delivery as a part of their system. Context-based services can be employed in specific applications (recommendation systems, or healthcare monitoring systems) and delivered through interfaces (Colombo-Mendoza et al, 2015;Sohn et al, 2015). Some articles, particularly, highlight the dissemination by explicitly determining an application layer of delivery services (Afzal et al, 2018;Navarro et al, 2018).…”

Section: Behavioral Aspectmentioning

confidence: 99%

Introduction to the Minitrack on Human-Computer Interaction in the Digital Economy

Schneider,

Valacich,

Jenkins

2024

Proceedings of the Annual Hawaii International Conference on System Sciences

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Context awareness systems, a subcategory of intelligent systems, are concerned with suggesting relevant products/services to users' situations as smart services. One key element for improving smart services' quality is to organize and manipulate contextual data in an appropriate manner to facilitate knowledge generation from these data. In this light, a knowledge-based approach, can be used as a key component in context-aware systems. Context awareness and knowledge-based systems, in fact, have been gaining prominence in their respective domains for decades. However, few studies have focused on how to reconcile the two fields to maximize the benefits of each field. For this reason, the objective of this paper is to present a literature review of how contextaware systems, with a focus on the knowledge-based approach, have recently been conceptualized to promote further research in this area. In the end, the implications and current challenges of the study will be discussed.

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Section: Behavioral Aspectmentioning

confidence: 99%

Introduction to the Minitrack on Human-Computer Interaction in the Digital Economy

Schneider,

Valacich,

Jenkins

2024

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…Another of the mechanisms proposed in [79] where it is used the same knowledge provide by LOD, it is applied to establish trust levels by relying on search spaces that have some kind of recommendation in the context of the users based on their reputation.…”

Section: What Are the Security Mechanisms Most Used In Lod?mentioning

confidence: 99%

Security Aspects in Web of Data Based on Trust Principles. A brief of Literature Review

Cubides

Gaona-García

Montenegro-Marín

et al. 2022

Int. j. commun. netw. inf. secur.

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Within scientific community, there is a certain consensus to define "Big Data" as a global set, through a complex integration that embraces several dimensions from using of research data, Open Data, Linked Data, Social Network Data, etc. These data are scattered in different sources, which suppose a mix that respond to diverse philosophies, great diversity of structures, different denominations, etc. Its management faces great technological and methodological challenges: The discovery and selection of data, its extraction and final processing, preservation, visualization, access possibility, greater or lesser structuring, between other aspects, that allow showing a huge domain of study at the level of analysis and implementation in different knowledge domains. However, given the data availability and its possible opening: What problems do the data opening face? This paper shows a literature review about these security aspects.

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“…A user can access travel-related open data, including weather, location of a hospital or restaurant, public transit schedule and the address of a hotel in Taiwan. Sohn et al [71] developed the ACARDS via the hybrid SPAQL query generation system to increase the degree of user satisfaction. The recommender system collected knowledge from LOD cloud and improved the quality of the context recommendation service using the augmented tag cloud.…”

Section: B Linked Open Data For Tourismmentioning

confidence: 99%

Linked Open Data in Location-Based Recommendation System on Tourism Domain: A Survey

Yochum

Chang

et al. 2020

IEEE Access

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Linked open data is a relatively new topic area with great potential in a wide range of fields. In the tourism domain, many studies are using linked open data to address the problem of location-based recommendation by integrating data with other linked open datasets to enrich data and tourism content for reacting to the needs of tourists. This work aims not only to present a systematic review and mapping of the linked open data in location-based recommendation system on tourism domain, but also to provide an overview of the current research status in the area. First, we classify journal papers in this area from 2001 to 2018 by the year of publication. Second, we analyze and categorize journal papers by the different recommendation applications including problem formulations, data collections, proposed algorithms/systems, and experimental results. Third, we group the linked open data sources used in location-based recommendation system on tourism. Next, we summarize the research achievements and present the distribution of the different categories of location-based recommendation applications via linked open data. Last, we also guide the possible future research direction for the linked open data in location-based recommendations on tourism.

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Augmented context-based recommendation service framework using knowledge over the Linked Open Data cloud

Cited by 6 publications

References 27 publications

Introduction to the Minitrack on Human-Computer Interaction in the Digital Economy

Introduction to the Minitrack on Human-Computer Interaction in the Digital Economy

Security Aspects in Web of Data Based on Trust Principles. A brief of Literature Review

Linked Open Data in Location-Based Recommendation System on Tourism Domain: A Survey

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