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Project recommendation method based on similarity

A project recommendation and similarity technology, applied in the information field, can solve problems such as large errors, sparse data, and limitations in similarity calculations, and achieve the effects of reducing errors, making better use of data samples, and solving sparse data samples

Inactive Publication Date: 2018-11-27
CHONGQING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] (1) The problem of data sparseness: when the same items selected by two users are relatively small or there are no identical items, the similarity calculation has limitations;
[0005] (2) When the number of selected items is unbalanced, the error is relatively large

Method used

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  • Project recommendation method based on similarity
  • Project recommendation method based on similarity
  • Project recommendation method based on similarity

Examples

Experimental program
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Embodiment Construction

[0050] The present invention will be further described below in conjunction with embodiment:

[0051] combine figure 1 It can be seen that the similarity-based item recommendation method includes the following steps:

[0052] S1: extract the original user data and the scoring data of the user's corresponding item;

[0053] S2: Calculate the similarity between any two items;

[0054] The calculation of the similarity between the two items in the step S2 includes the following steps:

[0055] S2-1: Count the distribution of each score of the two items;

[0056] Calculate the ratio of the number of users for each rating to the number of users who choose the item;

[0057]

[0058]

[0059] the p im is the proportional coefficient, N im is the number of users rated m in project i, N i is the number of users who choose item i;

[0060] the p jm is the proportional coefficient, N jm is the number of users who rated m in project j, N j is the number of users who choo...

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PUM

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Abstract

The invention discloses a project recommendation method based on similarity, and belongs to the technical field of information. The original user data and the score data of the corresponding project of the user are extracted; firstly the similarity between any two projects is calculated, and then the similarity between any two users is calculated by taking the project similarity as the weight; andthe scores of the nearest neighbor user for the projects are selected on the basis of the user similarity so as to form a recommendation list. The problem of data sparsity is solved by calculating the project similarity through the relative entropy algorithm, and the problem of excessive error caused by data imbalance can be solved by considering the number proportion of project selection.

Description

technical field [0001] The invention belongs to the field of information technology, in particular to a similarity-based item recommendation method. Background technique [0002] The present invention belongs to the field of information technology. At this stage, users in the information field are somewhat at a loss when choosing items. The existing item recommendation system calculates the similarity based on the selection of the same item by two users, and there are limitations when the two users select few or no identical items. The present invention forms a personalized item recommendation list for each user by analyzing the similarity between items and the similarity between users. Users can select items through the item recommendation list. [0003] Using user similarity to recommend items faces several difficulties: [0004] (1) The problem of data sparseness: when the same items selected by two users are relatively small or there are no identical items, the simil...

Claims

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Application Information

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IPC IPC(8): G06Q10/10G06Q10/06
CPCG06Q10/0639G06Q10/103
Inventor 周庆温亚梅陈自郁唐代高智峰廖凤露王卫芳
Owner CHONGQING UNIV
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