Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 226-230.doi: 10.11896/jsjkx.200900119

• Big Data & Data Science • Previous Articles     Next Articles

Intelligent Travel Route Recommendation Method Integrating User Emotion and Similarity

SUN Zhen-qiang, LUO Yong-long, ZHENG Xiao-yao, ZHANG Hai-yan   

  1. School of ComputerandInformation,Anhui Normal University,Wuhu,Anhui 241000,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:SUN Zhen-qiang,born in 1996,postgraduate.His main research interests include intelligent computing and recom-mendation system.
  • Supported by:
    National Natural Science Foundation of China(61972439).

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Abstract: In recent years,with the development of social networks,how to design a path recommendation method that meets the individual needs of users has become an important research hotspot.This paper considers the relevant characteristics of POI (point of interests),integrates the user's emotion and product similarity into the heuristic function of the ant colony algorithm,adopts the improvement strategy of EMAS,MMAS.By using the particle swarm algorithm to improve the first pheromone distribution of ant colony algorithm,combined with the scores of 593 tourists in the dataset and text comment data,this paper proposes the PS-AC (Particle Swarm-Ant Colony algorithm for user emotion and similarity) algorithm,and uses the improved ant colony algorithm to realize the user's travel route recommendation of the highly popular scenic spots in the scenic spots.Tests on real data sets show that the PS-AC algorithm has good performance in accuracy,recall,and F measurement.

Key words: Ant colony algorithm, Particle swarm optimization, Personalized recommendation, Travel route recommendation, User similarity

CLC Number: 

  • TP391
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