Mass information data recommendation method and device

A recommendation method and massive data technology, applied in the field of information processing, can solve the problem that users cannot obtain the required information in a timely and effective manner

Active Publication Date: 2018-01-12
中广核工程有限公司 +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of this, the embodiments of the present invention provide a method and device for recommending massive information data, aiming at solving the problem that users cannot obtain the required information in a timely and effective manner

Method used

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  • Mass information data recommendation method and device
  • Mass information data recommendation method and device
  • Mass information data recommendation method and device

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0031] figure 1 The implementation flow of the method for recommending massive information data provided by Embodiment 1 of the present invention is shown, and the implementation flow is described in detail as follows:

[0032] Step S101, obtaining metadata information from the enterprise content management system ECM.

[0033] In the embodiment of the present invention, the enterprise content management system ECM may be a nuclear power enterprise content management system, and the ECM contains a large amount of enterprise content, including but not limited to metadata information, unstructured file text content, system access And retrieve related logs and personnel information.

[0034] Step S102, generating a metadata clustering template according to the metadata set sample space of the metadata information.

[0035] Specifically, the complex metadata structure is simplified to generate a metadata clustering template, that is, through the clustering method, the content re...

Embodiment 2

[0049] figure 2 The implementation flow of the method for recommending massive information data provided by Embodiment 2 of the present invention is shown, and the implementation flow is described in detail as follows:

[0050] Step S201, obtaining metadata information from the enterprise content management system ECM.

[0051] This step is the same as step S101, for details, please refer to the relevant description of step S101, and details will not be repeated here.

[0052] Step S202, generating a metadata clustering template according to the metadata set sample space of the metadata information.

[0053] This step is the same as step S102, for details, please refer to the relevant description of step S102, and details are not repeated here.

[0054] Optionally, generating a metadata clustering template according to the metadata set sample space of the metadata information includes:

[0055] Step 1, arbitrarily selecting K objects from the sample space of the metadata set...

Embodiment 3

[0089] image 3 It shows a schematic diagram of the composition of the device for recommending massive information data provided by Embodiment 3 of the present invention. For the convenience of description, only the parts related to the embodiment of the present invention are shown, and the details are as follows:

[0090] A metadata information acquisition module 31, configured to acquire metadata information from the enterprise content management system ECM;

[0091] Metadata aggregation template generating module 32, for generating metadata clustering template according to the metadata set sample space of the metadata information;

[0092] Static attribute space acquisition module 33, for obtaining the static attribute space of the user according to the relevant information of the user;

[0093] Static mass data template acquisition module 34, for obtaining corresponding static mass data templates according to the static attribute space of the user and the metadata cluster...

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Abstract

The invention belongs to the technical field of information processing, and provides a mass information data recommendation method and device. The method comprises the following steps of: obtaining metadata information from an enterprise content management system ECM; generating a metadata clustering template according to a metadata set sample space; obtaining a static attribute space of a user according to related information of the user; obtaining a corresponding static mass data template according to the static attribute space of the user and the metadata clustering template; monitoring behavior logs of the user and obtaining attention words of the user in a preset time according to the behavior logs of the user; forming a text index according to text analysis of a mass data unstructured document; and searching to-be-recommended content according to the text index, the attention words of the user in the preset time and the static mass data template. Through the method and device, the problem that users cannot timely and effectively obtain required information is solved.

Description

technical field [0001] The invention belongs to the technical field of information processing, and in particular relates to a recommendation method and a recommendation device for massive information data. Background technique [0002] The content information and data of nuclear power engineering enterprises are complex, and the number of documents and materials is huge, reaching the level of one million, especially project engineering documents, technical documents, business contracts, correspondence and transfer materials of various technical routes (such as AP1000, EPR third-generation nuclear power technology). Since most of the technical materials are semi-structured and stored in the enterprise content management platform (Enterprise Content Management, ECM), the amount of information is huge, and technical personnel cannot obtain relevant knowledge updates in a timely manner. [0003] Therefore, it is necessary to propose a new technical solution to solve the above te...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 白鹤侯斌刘东海杨帆颜斯泰罗亚林王云福涂红兵戴伟琦
Owner 中广核工程有限公司
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