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Adaptive Push Method of Command Elements Based on Collaborative Filtering

A collaborative filtering and adaptive technology, applied in data processing applications, special data processing applications, unstructured text data retrieval, etc., can solve problems such as cold start and data sparseness

Active Publication Date: 2020-11-17
崔翛龙
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention provides an adaptive push method for command elements based on collaborative filtering, which overcomes the deficiencies of the prior art and can effectively solve the problems of data sparseness and cold start in traditional recommendation algorithms

Method used

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  • Adaptive Push Method of Command Elements Based on Collaborative Filtering
  • Adaptive Push Method of Command Elements Based on Collaborative Filtering
  • Adaptive Push Method of Command Elements Based on Collaborative Filtering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0069] Embodiment 1: as attached figure 1 , 2 As shown, the adaptive push method of command elements based on collaborative filtering includes the following steps:

[0070] The first step is to build an anti-terrorism resource pool to store and record comprehensive real-time update data of anti-terrorism operations;

[0071] The second step is to build a pre-collaborative filtering based on combat type-command elements and send the calculation results to the commander;

[0072] The third step is to construct a two-stage collaborative filtering scoring matrix based on commander-command elements, including the following process:

[0073] (1) Using "commander-command elements" to construct a two-dimensional m×n scoring matrix, its structure is as follows:

[0074]

[0075] Among them, T represents a combat task, I represents a command element, m represents the number of combat tasks T, and n represents the number of command elements I;

[0076] (2) According to the weighte...

Embodiment 2

[0130] Embodiment 2: as attached Figure 3.1 , 3.2As shown in , 3.3, 4, 5, and 6, two terrorists hijacked 3 hostages at gunpoint in W City, and drove a van in an attempt to crash into a temporary inspection roadblock on ZS Road, paralyzing some road sections in the urban area and causing extreme panic among the citizens. After being besieged by the traffic police, the group of terrorists fled to the textile factory bridge, abandoned their cars and entered a nearby residential building, trying to confront the police by taking advantage of the terrain. The situation was very critical. The Joint Command ordered the W City Detachment of the Armed Police Force to move quickly to the mission area and complete the tasks of sealing and controlling deployment, on-site disposal and hostage rescue; the detachment planned to send 20 officers and soldiers from the 1st and 3rd Squadrons to handle the mission according to the situation, and the deputy The detachment captain acts as the comm...

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Abstract

The invention relates to the field of the personalized recommendation technology, particularly to a collaborative-filtering-based adaptive command element pushing method. The method comprises: step one, constructing an anti-terrorism resource pool and storing comprehensive real-time updating data recording anti-terrorism operations; step two, constructing pre-collaborative filtering based on combat type-command element and sending a calculation result to a commander; and step three, constructing commander-command-element-based two-stage collaborative filtering and sending the calculated structure to the commander. According to the method provided by the invention, command element data that may be needed can be filtered for different types of anti-terrorism command tasks and thus the commander can search for relevant information based on the distributed command task, so that a problem that the commander does not know how to deal with the task when facing lots of data can be solved and thus the anti-terrorism data pushing efficiency can be improved. Most needed data are pushed respectively in the anti-terrorism combats based on commander roles; data demand differences of commanders at different levels in one same anti-terrorism combat can be eliminated; and accuracy of the anti-terrorism data pushing can be improved.

Description

technical field [0001] The invention relates to the technical field of personalized recommendation, and relates to a method for adaptively pushing command elements based on collaborative filtering. Background technique [0002] At present, in view of the characteristics of the diversification of anti-terrorism missions, massive command elements, and networked command levels, the direct construction of a collaborative filtering relationship between commanders and command elements has to face difficulties such as data sparseness and cold start, which is not only inefficient, but also Accuracy is also difficult to guarantee. The anti-terrorism accusation platform is the data interaction hub for each command node to implement anti-terrorism operations. Researching the information interaction mode of the accusation platform is of great significance for improving the data flow rate and thus improving the auxiliary decision-making ability of anti-terrorism operations. At present, ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q50/26G06F16/35
CPCG06F16/35G06Q50/265
Inventor 崔翛龙杜波袁琛
Owner 崔翛龙
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