Collaborative recommendation method and device and terminal device

A technology of item recommendation and search algorithm, which is applied in the computer field and can solve problems such as low accuracy

Active Publication Date: 2019-01-11
SHENZHEN INSTITUTE OF INFORMATION TECHNOLOGY
View PDF3 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of this, the embodiment of the present invention provides a collaborative recommendation method, device

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Collaborative recommendation method and device and terminal device
  • Collaborative recommendation method and device and terminal device
  • Collaborative recommendation method and device and terminal device

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0069] Example 1

[0070] figure 1 A schematic diagram of an implementation flow of the collaborative recommendation method provided by Embodiment 1 of the present invention is shown. like figure 1 As shown, the collaborative recommendation method specifically includes the following steps S101 to S104.

[0071] Step S101: Acquire a predetermined number of item data set information, where the item data set information includes user rating information for items in the item data set.

[0072] Wherein, the item data set information includes user rating information for items in the item data set. It can be understood that one item information may correspond to the rating information of multiple users.

[0073] Step S102: Based on the item data set information, an iterative search is performed according to the crow search algorithm to find the position of the cluster center of the optimal fuzzy C-means clustering.

[0074] Step S103: The position of the cluster center of the op...

Example Embodiment

[0077] Embodiment 2

[0078] figure 2 A schematic diagram of the implementation flow of the collaborative recommendation method provided by the second embodiment of the present invention is shown. like figure 2 As shown, the collaborative recommendation method includes the following steps S201 to S210:

[0079] Step S201: Acquire a predetermined number of item dataset information.

[0080] Among them, the item can be a movie, a book, etc. Taking a movie as an example, the movie dataset information includes movie metadata information, user attribute information and rating information. Specifically, the data set is the Movielens data set provided by the GroupLens project team of the School of Computer Science and Engineering, University of Minnesota, USA. This data set mainly uses the combination of Collaborative Filtering and Association Rules. Movies of interest. The dataset contains a total of 700 users' rating data information on 9,000 movies of various categories, a...

Example Embodiment

[0135] Embodiment 3

[0136] Please refer to image 3 , which shows a schematic diagram of an apparatus for collaborative recommendation provided by an embodiment of the present invention. The collaborative recommendation device includes: a data acquisition module 31 , a calculation module 32 , a construction module 33 and a score prediction module 34 . The specific functions of each module are as follows:

[0137] The data acquisition module 31 is used to acquire a predetermined number of item data set information, and the item data set information includes the user's rating information for the items in the item data set;

[0138] The calculation module 32 is used for iterative search based on the project data set information, according to the crow search algorithm, to find the position of the cluster center of the optimal fuzzy C-means clustering;

[0139] The building module 33 is used to take the position of the cluster center of the optimal fuzzy C-means clustering as ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention is applicable to the field of computer technology, and provides a collaborative recommendation method and device and a terminal device. The method comprises the following steps of: acquiring a predetermined amount of item data set information, wherein the item data set information comprises user scoring information of items in the item data set; based on the project data set information, carrying out an iterative search according to a crow search algorithm to find the position of the cluster center of the optimal fuzzy C-means cluster; taking the position of the cluster center ofthe optimal fuzzy C-means cluster as the position of the initial cluster center; based on the optimized position of the initial cluster center, calculating the similarity between users according to the fuzzy C-means clustering method and classifying the users according to the similarity to construct a recommendation model; based on the recommendation model, predicting the items that are not graded by the target user, obtaining the prediction score by similarity measurement, and recommending the first N items to the target user based on the ranking information of the prediction score.

Description

technical field [0001] The invention belongs to the technical field of computers, and in particular relates to a collaborative recommendation method, device and terminal equipment. Background technique [0002] With the update of information technology, the rapid development of Internet technology and cloud computing, the amount of data is also increasing exponentially. While these data provide rich information for human beings, it also creates the problem of information overload. It is difficult for people to find the information they are interested in or useful in the massive data information. Search engines cannot fully meet the needs, and sometimes the needs are not clear. In response to this problem, the recommendation system came into being. It plays a vital role in information filtering, information classification and refinement, and providing users with personalized services. Update and automatically recommend various demand information to users, which can greatly i...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F16/9535G06F16/28G06N3/00
CPCG06N3/006
Inventor 马超
Owner SHENZHEN INSTITUTE OF INFORMATION TECHNOLOGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap