Research Article

Tourism Destination Recommendation Based on Association Rule Algorithm

Table 1

Travel itinerary planning algorithm based on time frame.

TitleContributionResearch gap/limitations

Tourism route decision support based on neural net buffer analysisA knowledge-based tourism recommendation system is designed. The system provides users with interesting travel information through their operation behaviorsEmphasis is placed on the functional development and operation mode of websites, but there is little research on website reviews
Schinas O. Energy supply security for the Aegean islands: a routing model with risk and environmental considerationsBased on the MapReduce framework, quantitative association rules in big data environment are studiedThis study improved the traditional tourism information service, but failed to reflect the connotation of smart tourism
Analysis of tourist systems predictive models applied to growing sun and beach tourist destinationA knowledge-based recommendation system is proposed, which simulates the way of human tour guides and provides users with interesting travel information according to their operation behaviorsEmphasis is placed on the functional development and operation mode of websites, but there is little research on website reviews
A performance evaluation of a fault-tolerant path recommendation protocol for smart transportation systemIn this study, the efficient association rule mining considering itemset constraints is studied. By pruning the uninterested itemsets and the rules that users are not interested in during the generation of frequent itemsets, the efficiency of algorithm mining is improvedThis method can better discover users’ interests, but it lacks the function of autonomous feature learning
A new point-of-interest approach based on multi-itinerary recommendation engineThis study studies the mining of temporal and spatial association rules without time constraints and demonstrates its application in global terrorism event miningThe problem of repeated mining in the mining process is reduced, but there is still a lack of personalization in recommendation
Attraction recommendation: towards personalized tourism via collective intelligenceAiming at the orderliness of event sequences, a mining method of association rules with order constraints is proposedThis study improved the traditional tourism information service, but failed to reflect the connotation of smart tourism
A stochastic approach towards travel route optimization and recommendation based on users constraints using Markov chainAiming at the problem of travel itinerary planning with multiple constraints, a travel itinerary planning algorithm based on time frame is proposedEmphasis is placed on the functional development and operation mode of websites, but there is little research on website reviews