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Method and device for processing interactive data by using LSTM neural network model

A neural network model and interactive data technology, applied in the field of processing interactive data using machine learning, can solve problems such as difficulty in feature expression

Active Publication Date: 2020-05-29
ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, the interaction event involves both parties, and the state of each participant can change dynamically. Therefore, it is very difficult to accurately express the characteristics of the interaction participants by comprehensively considering the various characteristics of the interaction participants.

Method used

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  • Method and device for processing interactive data by using LSTM neural network model
  • Method and device for processing interactive data by using LSTM neural network model
  • Method and device for processing interactive data by using LSTM neural network model

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Embodiment approach

[0147] According to another embodiment, the process of combining the time difference may include the following steps:

[0148] After combining the node characteristics of the second node u(t) and the time difference Δ with k hidden vectors corresponding to k associated nodes, input the first transformation function g and the second transformation function with the same algorithm and different parameters f, obtain k first transformation vectors and k second transformation vectors respectively;

[0149] Combine the intermediate vector of the i-th associated node among the k associated nodes with the corresponding i-th first transformation vector and i-th second transformation vector to obtain k operation results, and sum the k operation results , get the combination vector;

[0150] Inputting the node features of the second node together with the k hidden vectors into a third transformation function and a fourth transformation function to obtain a third transformation vector an...

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Abstract

The embodiment of the invention provides a method and device for processing interactive data. In this method, the method comprises the steps that firstly, a dynamic interaction graph constructed according to an interaction event set is acquired, any node i in the graph points to M associated nodes corresponding to N associated events in which an object represented by the node i participates last time through a connecting edge, the object is allowed to participate in the multiple associated events at the same time, and the node is allowed to be connected to more than two associated nodes; and then, in the dynamic interaction graph, a current sub-graph corresponding to the current node to be analyzed is determined, and the current sub-graph is input into the neural network model for processing. The neural network model comprises an LSTM (Long Short Term Memory) layer, and the LSTM layer iteratively processes each node in sequence according to the pointing relationship of the connecting edges among the nodes in the current sub-graph so as to obtain the implicit vector of the current node.

Description

technical field [0001] One or more embodiments of this specification relate to the field of machine learning, and in particular, to a method and device for processing interaction data using machine learning. Background technique [0002] In many scenarios, user interaction events need to be analyzed and processed. Interaction events are one of the basic elements of Internet events. For example, the click behavior when a user browses a page can be regarded as an interaction event between the user and the content block of the page, and the purchase behavior in e-commerce can be regarded as the interaction event between the user and the product. The interaction event between accounts, and the transfer behavior between accounts is the interaction event between users. A series of user interaction events contains the characteristics of the user's fine-grained habits and preferences, as well as the characteristics of the interactive objects, which are important feature sources of ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08
CPCG06N3/049G06N3/08
Inventor 常晓夫文剑烽刘旭钦宋乐
Owner ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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