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Multilevel classification retrieval method and system

A multi-level classification and classification table technology, applied in the field of database retrieval, can solve the problems of poor scalability, bloated structure, low retrieval efficiency, etc., and achieve good scalability and improve efficiency

Inactive Publication Date: 2010-09-22
PEKING UNIV FOUNDER GRP CO LTD +2
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the existing retrieval methods, in order to solve the problem of low retrieval efficiency, there is also a method of storing multiple classification attributes in multiple fields of the data table, and then using the database index for retrieval
For example, in the above example, "Asia", "China", and "Beijing" can be stored in three fields. Although this method can improve the retrieval efficiency to a certain extent, its scalability is extremely poor. When adding more When a classification is added (for example, column classification, genre classification, etc. need to be stored in the above example), many fields will be added, which will make the structure of the table more and more bloated

Method used

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Examples

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Embodiment 1

[0069] In this embodiment, it is assumed that the data has the following classification methods: A, B, C, and D. Among them, A is the root node, the level ID is 1, and the classification node ID is 100; B is the child node of A node, the level ID is 2, and the classification node ID is 101; C is the child node of B node, the level ID is 3, The classification node ID is 102; D is a child node of node C, the level ID is 4, and the classification node ID is 103.

[0070] Assume that a classification table with the following structure is established:

[0071] Classification Hierarchy ID

Classification node ID

Category Name

parent node

1

100

A

0

2

101

B

1

3

102

C

2

4

103

D

3

[0072] After obtaining the classification node ID according to the classification table, it is assumed to establish a data table with the following structure:

[0073] field 1

...

Embodiment 2

[0081] The difference from Example 1 is that the classification field in the data table stores multiple classification paths, assuming that its structure is as shown in the following table:

[0082] field 1

[0083] In the above table, the hierarchical relationship between different classification levels in the classification field is separated by ";", of course, other symbols can also be used, as long as different classifications can be distinguished. The structure of the generated classification association table is shown in the following table:

[0084] field 1

[0085] Among them, the contents of "Field 1", "Field 2" and "Field 3" of the three records are the same.

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Abstract

The invention discloses a multilevel classification retrieval method and a system, which belong to the technical field of the database retrieval. In the prior art, the retrieval efficiency of the classified data is low or the expandability is poor. The method and the system are characterized in that a classified field is arranged in a data sheet according to data classification information, and hierarchical relationship between classified nodes is stored; each node is divided into an independent field according to the hierarchical relationship between the classified nodes, the field is combined with other fields in the data sheet so as to generate a classified association list; and database index is used for retrieving data in the classified association sheet during the retrieval. The method and the system improve the retrieval efficiency of the classified data, have strong expandability, and are particularly applicable to the retrieval of the database of large data volume.

Description

technical field [0001] The invention belongs to the technical field of database retrieval, and in particular relates to a multi-level classification retrieval method and system. The invention is especially suitable for database retrieval of massive data. Background technique [0002] In information systems, data is often classified and stored, which is convenient for users to classify and retrieve data and view classified data, especially in the case of massive data, which can improve the efficiency of retrieval. For example, suppose an article contains a region classification attribute: Asia→China→Beijing. This is a typical multi-level classification structure. If the classification attribute of the region is set to "China", the system usually stores only one node, that is, "China" or hard-codes the classification path to one or more fields. . When searching, perform fuzzy query through the like statement in SQL. On the one hand, this retrieval method is inefficient whe...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 王洪昌卢作伟宫丽杰
Owner PEKING UNIV FOUNDER GRP CO LTD
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