2020
DOI: 10.1007/s12525-020-00416-5
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A personalized point-of-interest recommendation system for O2O commerce

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Cited by 14 publications
(9 citation statements)
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“…Enormous progress has been made in the fields of business, social communication, connectivity and organization. The shift of companies to the internet has led to a strong dynamization and acceleration of economic activities [167,168]. From the above, it is reasonable to expect that this circumstance will also contribute to the dynamism of social mobility, so that more and more people will have the opportunity to start their own business (e.g., on digital platforms) with little or no investment, thereby constantly improving the economic situation of the lower classes and increasing prosperity.…”
Section: Automated Content Analysis Results For Articles From 5/1996 mentioning
confidence: 99%
“…Enormous progress has been made in the fields of business, social communication, connectivity and organization. The shift of companies to the internet has led to a strong dynamization and acceleration of economic activities [167,168]. From the above, it is reasonable to expect that this circumstance will also contribute to the dynamism of social mobility, so that more and more people will have the opportunity to start their own business (e.g., on digital platforms) with little or no investment, thereby constantly improving the economic situation of the lower classes and increasing prosperity.…”
Section: Automated Content Analysis Results For Articles From 5/1996 mentioning
confidence: 99%
“…By recording users' usage habits and combining with corresponding artificial intelligence algorithms, the platform makes targeted recommendations to target customers, creating fan product economy, achieving accurate marketing, and realizing traffic realization while harvesting large traffic [17]. In order to achieve accurate marketing, decisionmaking will be more and more based on data and analysis, and enterprises will optimize their operations based on data 2 Scientific Programming analysis [18]. e essence of machine learning is to count and find similar data with certain statistical laws, and its goal is to find an optimized model from the regular data space [19].…”
Section: Intelligent Algorithmmentioning
confidence: 99%
“…Jiao et al [31] used the Gowalla and Foursquare datasets to simulate travel decision-making processes in order to recommend POIs for users. Using the Gowalla and Foursquare datasets, Kang et al [32] demonstrated the applicability of LBSN data in recommending locations for online-to-offline commerce. Wei and Zhang [33] used the Foursquare dataset to demonstrate their recommendation systems based on consumption habits within LSBNs.…”
Section: Overview Of Existing Social Network and Lbsnsmentioning
confidence: 99%
“…Logesh et al [10] and Huang et al [11] developed systems to recommend travel routes suitable for groups instead of individual users. Kang et al [32] developed a recommendation system for online-to-offline commerce.…”
Section: Recommendation Systems Using Data Acquired From Lbsnsmentioning
confidence: 99%