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A tourist attraction recommendation method based on multiple data sets and collaborative tensor decomposition

A technology of tensor decomposition and recommendation method, which is applied in data processing applications, electrical digital data processing, digital data information retrieval, etc.

Active Publication Date: 2020-04-07
ZHEJIANG HONGCHENG COMP SYST
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the introduction of additional time context information will cause the established recommendation model to encounter more serious data sparsity problems, because the sparsity of the established user-attraction-time tensor is larger than that of the user-attraction matrix

Method used

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  • A tourist attraction recommendation method based on multiple data sets and collaborative tensor decomposition
  • A tourist attraction recommendation method based on multiple data sets and collaborative tensor decomposition
  • A tourist attraction recommendation method based on multiple data sets and collaborative tensor decomposition

Examples

Experimental program
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Embodiment

[0075] Example: such as figure 1 As shown, a tourist attraction recommendation method based on multi-datasets and collaborative tensor decomposition, the method is divided into three stages: obtaining information of multiple datasets, inferring user travel preferences, and recommending tourist attractions.

[0076] (1) The stage of obtaining multiple data set information, the process is as follows figure 2 As shown, the steps are as follows:

[0077] Step 1, use the public API of the photo sharing website to download the photo dataset D with geographic location information in the tourist city photo , these photo data usually include the identification information of the photo, the time when the photo was taken, the latitude and longitude information of the place where the photo was taken, etc.

[0078] The specific steps for obtaining photo data include:

[0079] a) Through the public API provided by the photo sharing website (such as: Flickr), download the photos taken in...

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Abstract

The invention relates to a multi-data set and collaborative tensor decomposition-based scenic spot recommendation method. According to the method, user behavior information of different data sources is utilized to provide fine-grit travel recommendation services for the users. The method comprises the following steps of: firstly obtaining information of a plurality of data sets from a social network site; constructing a user-scenic spot-time tensor on the basis of user travel history information, combining a collaborative tensor decomposition model to decompose and complement the tensor so as to obtain travel preferences of the users; and finally recommending proper scenic spots according to the complemented user-scenic spot-time tensor and travel cities and time scene information input by users. According to the method, time perception-based scenic spot recommendation services can be provided for the users.

Description

technical field [0001] The invention relates to the technical field of information recommendation, in particular to a tourist attraction recommendation method based on multiple data sets and collaborative tensor decomposition. Background technique [0002] In recent years, with the widespread application of mobile Internet, smart phones, and digital cameras with GPS devices, people can take some photos with geographic location information anytime and anywhere, and upload them to photo-sharing sites like Flickr for Share it with people all over the world. At present, the number of photos with geographic location information contributed by groups shows a trend of rapid growth. These photos with geographic location information create feasible conditions for making full use of collective wisdom to discover popular attractions, obtain user travel preferences, and further provide users with personalized scenic spot recommendation services. [0003] At present, the tourist attrac...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/9537G06F16/9536G06Q50/14
CPCG06F16/9535G06F16/9537G06Q50/14
Inventor 吴勇陈岭徐振兴施彦
Owner ZHEJIANG HONGCHENG COMP SYST
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