Collaborative filtering method, collaborative filtering device and collaborative filtering system

A collaborative filtering and collection technology, applied in marketing, advertising, instruments, etc., can solve the problems of high time complexity, long similarity calculation time, and low recall rate of highly relevant effective listings.

Active Publication Date: 2020-09-01
KE COM (BEIJING) TECHNOLOGY CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a collaborative filtering method, collaborative filtering device and system to solve the problem of low recall rate of high-correlation effective listings, long similar calculation time, Technical issues such as high time complexity and excessive hardware resource occupation

Method used

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  • Collaborative filtering method, collaborative filtering device and collaborative filtering system
  • Collaborative filtering method, collaborative filtering device and collaborative filtering system
  • Collaborative filtering method, collaborative filtering device and collaborative filtering system

Examples

Experimental program
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Effect test

Embodiment 1

[0074] The embodiment of the present invention provides a collaborative filtering method, such as figure 1 , the collaborative filtering method includes:

[0075] S1) Determine the first set of house sources, and form the preference data of the houses in the first set of house sources into a first preference data set corresponding to the selected user, wherein the houses in the first set of house sources are recorded have behavioral data of said selected users;

[0076] S2) Determine the range of the location area, and select some users according to the range of the location area, and then determine the second set of housing sources, and form the preference data of the housing sources in the second set of housing sources into a list corresponding to the part of users A second preference data set, wherein the houses in the second house source set are recorded with the behavior data of the part of the users;

[0077] S3) Determine the vector decomposition model to be trained, ...

Embodiment 2

[0127] Based on the inventive concept of Embodiment 1, the embodiment of the present invention provides a collaborative filtering device, which may include:

[0128] The first selection module can be used to determine a first house source set, and form the preference data of the house sources in the first house source set into a first preference data set corresponding to the selected user, wherein the first house source The listings in the collection are recorded with the behavior data of the selected users;

[0129] The second selection module can be used to determine the range of the location area, select some users according to the range of the location area, and then determine the second set of house sources, and form the preference data of the house sources in the second set of house sources with the The second preference data set corresponding to the part of users, wherein the houses in the second house source set are recorded with the behavior data of the part of the us...

Embodiment 3

[0150] Based on the inventive concept of Embodiment 1, the embodiment of the present invention provides a system for recommending house sources, the system includes: one or more programs, one or more programs can form one or more services in some production environments, Each program or each service can execute one or more steps; in some specific implementations, one or more programs can be compiled or encrypted to become an executable engine, which can call some executable programs The output data of the engine can also rely on or have some function libraries and model libraries; the engine can be a recommendation engine, and the processing granularity of the recommendation engine can be the granularity determined by the administrative region;

[0151] The recommendation engine is configured to execute instructions corresponding to the method described in Embodiment 1.

[0152] The present invention utilizes administrative area granularity constraints and the co-occurrence st...

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Abstract

The invention provides a collaborative filtering method, a collaborative filtering device and a collaborative filtering system, and belongs to the technical field of house information processing. Themethod comprises the following steps: determining a first house resource set, and forming a first preference data set corresponding to a selected user from preference data of house resources in the first house resource set; determining a position area range, selecting a part of users according to the position area range, determining a second house resource set, and forming a second preference dataset corresponding to the part of users from the preference data of the house resources in the second house resource set; and obtaining a trained vector decomposition model through the second preference data set, obtaining a feature vector set corresponding to the house resources in the second house resource set by utilizing the second preference data set and the trained vector decomposition model, calculating the similarity of the feature vector set, and forming a similarity set after the calculation is completed. The method and system are used for determining the recommended house resourceswith the user preference characteristics through similarity calculation.

Description

technical field [0001] The present invention relates to the technical field of house information processing, in particular to a collaborative filtering method, a recommendation method, a collaborative filtering device, a recommendation device, a system, a device and a computer-readable storage medium. Background technique [0002] In an item-based collaborative filtering algorithm, the similarity between items is usually used to generate a recommendation list, and this type of algorithm has a time complexity of O(n 2 ). However, in the current era of information overload, there are countless item information, such as housing information (housing source, as an item to be processed); as the amount of data n gradually increases, the calculation of any two Items between The time cost and hardware resource consumption of similarity are very high, so an effective computing strategy is needed to reduce the computing cost and save computing resources. Contents of the invention ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9536G06F16/9537G06Q30/02G06Q50/16
CPCG06Q30/0255G06Q30/0259G06Q30/0261G06Q30/0271G06Q50/16G06F16/9536G06F16/9537
Inventor 李政浩董天南
Owner KE COM (BEIJING) TECHNOLOGY CO LTD
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