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Personalized recommendation method of tourism route based on group intelligence perception

A technology for crowd perception and travel routes

Active Publication Date: 2018-10-19
ANHUI NORMAL UNIV
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

The traditional route recommendation does not involve the user's interest preference, but only considers the information of the scenic spot itself, thus causing the problem that the recommendation effect does not meet the user's preference

Method used

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  • Personalized recommendation method of tourism route based on group intelligence perception
  • Personalized recommendation method of tourism route based on group intelligence perception
  • Personalized recommendation method of tourism route based on group intelligence perception

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0067] Such as figure 1 As shown, the personalized recommendation method of tourist routes based on crowd sensing includes the following steps:

[0068] S1. Carry out ArcGIS modeling on the actual road network, such as figure 2 shown.

[0069] S2. Build user u d The multivariate constraint interest model.

[0070] In the embodiment of the present invention, we take image 3 For reference, for user u d start position, next in {a 1 ,a 2 ,...,a n} to select several points and add them to the path collection.

[0071] Constraint 1 Time Constraint

[0072] Remember to add point a j with the previous point a i The distance between the distances is T(a i ,a j ), (i∈{0,1,…,n}; j∈{0,1,…,n}; i

[0073]

[0074] This constraint is for any single POI that joins the route collection.

[0075] Here, the attraction a j After meeting the conditions and joining the travel route, a j The arrival time of is constantly changing. In order to express it more clearly,...

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Abstract

The invention discloses a personalized recommendation method of a tourism route based on group intelligence perception, which integrates the POI social score of group intelligence perception and the POI location score of group intelligence perception on the basis of user interest matching, so that the scoring rules are more comprehensive. In addition, the proposed scenic spot recommending algorithm suitable for the condition of no must-go scenic spots namely, the variable nearest neighbor tour route recommendation algorithm, and the single / multi-POI two-stage greedy tourism route recommendation algorithm for the must-go scenic spots are not only low in time complexity, but also more suitable for users' preference and have rationality.

Description

technical field [0001] The invention relates to the field of big data analysis based on computer technology, in particular to a method for personalized recommendation of travel routes based on crowd intelligence perception. Background technique [0002] In recent years, with the vigorous development of the Internet, all kinds of information have exploded. The birth of recommendation technology can help people obtain the resources they are interested in. Since the recommendation technology has developed very maturely in e-commerce, domestic representative companies such as Alibaba, Tencent, Baidu, Jingdong and other large companies have used recommendation technology to recommend various similar interests to users in varying degrees. The recommendation techniques currently used include collaborative filtering, content-based recommendation, knowledge-based recommendation, and combined recommendation. [0003] However, since travel routes are affected by many factors, such as...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q10/04G06Q10/06G06Q30/06
CPCG06Q10/04G06Q10/06393G06Q30/0631
Inventor 郑孝遥尤浩徐致云罗永龙汪祥舜胡朝焱孙丽萍胡桂银郭良敏
Owner ANHUI NORMAL UNIV
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