Cross recommendation method and system based on local weighted linear regression model
A linear regression model and local weighting technology, applied in the field of information processing, can solve problems such as overfitting, affecting the accuracy and recall of cross-recommendation systems, and affecting the accuracy and recall of cross-recommendation, so as to improve accuracy and recall rate effect
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0040] An embodiment of the present invention provides a cross-recommendation method based on a locally weighted linear regression model, such as figure 1 As shown, the cross-recommendation method based on the locally weighted linear regression model includes:
[0041] Step S1: Obtain the user's scoring record for at least one target item in the target object and the auxiliary scoring record for at least one auxiliary item in auxiliary objects related to the target object.
[0042] Step S2: Establish an item vector to be evaluated of the target item to be evaluated according to the scoring record and the auxiliary scoring record.
[0043] Step S3: expand the vector of items to be evaluated into an augmented vector, and establish a locally weighted linear regression model according to the augmented vector.
[0044] Step S4: Using the stochastic gradient descent algorithm to solve the locally weighted linear regression model to obtain an optimal solution.
[0045] Step S5: Cal...
Embodiment 2
[0089] Embodiments of the present invention provide a cross-recommendation system based on a locally weighted linear regression model, such as Figure 4 As shown, the cross-recommendation system based on the local weighted linear regression model includes: a score record acquisition module 1, which is used to obtain the score record of the user on at least one target item in the target object and at least one target item in the auxiliary object related to the target object. An auxiliary scoring record of an auxiliary item; the target vector construction module 2 to be evaluated is used to establish the item vector to be evaluated of the target item to be evaluated according to the scoring record and the auxiliary scoring record; the local weighted linear regression model construction module 3 is used to The item vector is expanded into an augmented vector, and a locally weighted linear regression model is established according to the augmented vector; the optimized solution sol...
Embodiment 3
[0109] An embodiment of the present invention provides a non-transitory computer storage medium, the computer storage medium stores computer-executable instructions, and the computer-executable instructions can execute the locally weighted linear regression model-based cross-recommendation method in any of the first embodiments above. Wherein, the above-mentioned storage medium can be a magnetic disk, an optical disk, a read-only memory (Read-OnlyMemory, ROM), a random access memory (Random Access Memory, RAM), a flash memory (FlashMemory), a hard disk (Hard Disk Drive, Abbreviation: HDD) or solid-state drive (Solid-State Drive, SSD), etc.; the storage medium may also include a combination of the above types of storage.
[0110] Those skilled in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented through computer programs to instruct related hardware, and the programs can be stored in a computer-readable storage me...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com