Distributed convergence behavior mining method and system

A distributed and behavioral technology, applied in special data processing applications, instruments, electrical and digital data processing, etc., can solve problems such as the inability to effectively supervise the behavior of mice, the inability to meet the requirements of accuracy and efficiency, and the impracticality of large-dimensional data sets. , to achieve the effect of being easy to implement and understand, improve inefficiency problems, and reduce algorithm complexity

Active Publication Date: 2018-09-21
INST OF COMPUTING TECH CHINESE ACAD OF SCI
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AI Technical Summary

Problems solved by technology

[0009] In the research of the mouse warehouse behavior mining algorithm, the original algorithm is implemented on a single machine using SQL language, which not only has high algorithm complexity, but also cannot be distributed, resulting in low efficiency. It takes several days to dig out the behavior of the mouse barn, which cannot satisfy the effective supervision of the behavior of the mouse ba

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  • Distributed convergence behavior mining method and system
  • Distributed convergence behavior mining method and system
  • Distributed convergence behavior mining method and system

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Embodiment Construction

[0060] In order to make the above-mentioned features and effects of the present invention more clear and understandable, the following specific examples are given together with the accompanying drawings for detailed description as follows.

[0061] Step 1. Data preprocessing and storage process. Obtain a data set composed of quadruple data, the quadruple data includes objects, events, time points and weights, count the event types of the data set, divide the data set into multiple event sets according to the event types, The quadruple data in this event collection all have the same event type.

[0062] Step 2. Build an index tree for the event set, determine the total time length of the index tree according to the minimum time point and maximum time point in the event set, split the total time length into time segments according to the line segment tree method, and each time period of the index tree Each node corresponds to the weight sum of each object in the time period, an...

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Abstract

The invention relates to a distributed convergence behavior mining method and system. The method comprises the following steps of: obtaining a data set formed by four groups of data, and dividing thedata set into a plurality of event sets according to event types, wherein the four groups of data comprise objects, events, time points and weights; constructing index trees for the event sets, determining a total time length of the index trees according to the time points in the event sets, splitting the total time length into time periods according to a segment tree division method, and storingthe index trees to a distributed database, wherein each node of the index trees corresponds to a weight sum of all objects in the time periods; obtaining a to-be-queried event and a to-be-queried timeperiod of a to-be-queried object, searching an index tree corresponding to the to-be-queried event from the distributed database to serve as a to-be-queried index tree, querying a weight sum of all objects in the to-be-queried time period in the to-be-queried index tree to serve as a convergence degree of the to-be-queried object, and selecting the object with the highest convergence degree as amining result.

Description

technical field [0001] The invention relates to the field of data mining, in particular to a distributed trend peer behavior mining method and system. Background technique [0002] Any data that can be abstracted into (object, event, time, weight) quadruples can calculate the degree of convergence between objects. Wherein, "object" refers to it in general, and when it corresponds to a specific application, such as detecting a mouse warehouse in the following embodiment, its "object" is "user". The goal of Lockstep BehaviorMining (LBM) is to mine out the object with the highest degree of convergence in the database under a given behavior set of an object. The behavior set refers to all (events, time, weights) belonging to the object )Triad. [0003] If each object splices the vectors on each event (time is the dimension, and the value on each dimension is the weight) into an object vector in order, and the length of each object vector is |E|*|T|, here E is the set of all e...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06F8/30
CPCG06F8/31
Inventor 李宏伟罗平敖翔庄福振何清
Owner INST OF COMPUTING TECH CHINESE ACAD OF SCI
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