Unlock instant, AI-driven research and patent intelligence for your innovation.

Reverse k-rank query method based on distance

A query method and distance technology, applied in instruments, data processing applications, commerce, etc., can solve problems such as high algorithm complexity, inability to find potential customers for non-popular merchants, and long model training time.

Active Publication Date: 2021-10-12
EAST CHINA NORMAL UNIV
View PDF9 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The traditional personalized recommendation method based on machine learning requires long model training time and high algorithm complexity, which is difficult to adapt to the real-time requirements of the mobile environment
The existing distance-based reverse ranking query (reverse top-k query) can only find potential customers for some popular merchants, but for less popular merchants, the return result set of the query is often empty because the k value is unpredictable in advance , that is, unable to find suitable potential customers for non-popular merchants

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
  • Reverse k-rank query method based on distance
  • Reverse k-rank query method based on distance
  • Reverse k-rank query method based on distance

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0044] The present invention is named Algorithm 1 (ResponseRkranks). In order to make the implementation process more concise and clear, Algorithm 1 includes Algorithm 2 (FilterBucket).

[0045] figure 1 It is the specific processing flow of Algorithm 1. First, the merchant data set P, mobile user data set M, and mobile user preference data set W are input. Then, build indexes on each data set, including building a grid index on the location of the merchant and the location of the mobile user; build a KD tree index on the full-dimensional space of the merchant, and maintain a minimum circumscribing like the R tree at each non-leaf node Rectangular; build an equal-width histogram H on mobile user preferences.

[0046] After the corresponding index is established, the algorithm locates and queries the grid C where the merchant is located on the grid G, and uses Z to save the query return result, that is, the k users with the best ranking currently, in order to avoid repeated vi...

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 discloses a distance-based reverse k-ranking query method. The method first uses a grid index to index the current positions of merchants and mobile users, uses a KD tree to index all dimensions of merchants, and uses a histogram of equal width to index User preferences are indexed; then, based on the three indexes, the method based on lower bound pruning is used to quickly find k users who are most interested in a specified merchant. The present invention overcomes the natural deficiency in the reverse ranking query based on distance, can return k potential customers for any merchant, is suitable for the orientation of potential customers centered on merchants in a mobile environment, and provides personalized and accurate location-based services. Marketing provides the solution.

Description

technical field [0001] The invention belongs to the field of reverse ranking query in database technology, and in particular relates to a method for searching potential customers centered on merchants in a mobile environment. The distance-based reverse k-ranking query method proposed by the present invention mainly solves the problem of how to quickly return the k potential customers who are most interested in the merchant q given the query merchant q in the mobile environment. Background technique [0002] With the rapid development of wireless positioning technology and the popularization of various mobile devices, as well as the widespread use of Web 2.0 applications, merchants can easily collect user preferences, and can real-time according to the current location and preferences of mobile users. Some promotional information is pushed to some potential customers. The traditional personalized recommendation method based on machine learning has a long model training time ...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/242G06F16/22G06F16/2453G06Q30/06
CPCG06Q30/0601G06F16/2228G06F16/2425G06F16/2453
Inventor 张召金澈清戚晓冬
Owner EAST CHINA NORMAL UNIV