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Data preprocessing method and device for knowledge graph

A data preprocessing and knowledge graph technology, applied in the computer field, can solve the problem of large number of parameters and insufficient comprehensiveness, and achieve the effect of improving the expression ability

Pending Publication Date: 2020-06-19
ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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Problems solved by technology

Conventional technology is either not comprehensive enough or the number of parameters is too large in the expression of these intricate entity relationships

Method used

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  • Data preprocessing method and device for knowledge graph
  • Data preprocessing method and device for knowledge graph
  • Data preprocessing method and device for knowledge graph

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Embodiment Construction

[0026] The solutions provided in this specification will be described below in conjunction with the accompanying drawings.

[0027] For ease of illustration, combine figure 1 A specific application scenario of the illustrated embodiment of this specification will be described. figure 1 Shown is a schematic diagram of a knowledge graph describing the relationship between entities. Such as figure 1 As shown, the knowledge graph may contain multiple entities (or concepts), for example, Zhang San, Li Si, Company A, Company B, Hangzhou, and each entity corresponds to a node in the knowledge graph. Nodes with a certain association relationship are connected by directed edges, and the directed connection edge shows the connection relationship between the two connected nodes. There can be many types of relationships between entities in the knowledge graph, which can be called connection relationship categories. For example in figure 1 Among them, the directed connection edge from...

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Abstract

The embodiment of the invention provides a data preprocessing method and device for a knowledge graph. The method comprises the steps of when vector expressions of nodes and connection relationship categories in a knowledge graph are determined, fusing the Hadamard product of a first node vector corresponding to a head node in the triple and a first relationship vector corresponding to a connection relationship category between the head node and a tail node to obtain an intermediate vector; and taking the distance between the intermediate vector and a second node vector corresponding to the tail node as a reference evaluation index, and updating the corresponding node vector and the relationship vector based on the adjustment of the values of the positive and negative samples on the reference evaluation index. According to the method, on the basis of saving parameters, common association relationships such as a symmetric relationship, an opposite relationship and a combined relationship can be expressed at the same time, and the expression capability of the knowledge graph is improved.

Description

technical field [0001] One or more embodiments of this specification relate to the field of computer technology, and in particular to a data preprocessing method and device for determining a vector representation of a knowledge graph by a computer. Background technique [0002] With the development of the Internet, the content of network data presents an explosive growth trend. Due to the characteristics of large-scale, heterogeneous and diverse, and loose organizational structure of Internet content, it poses challenges for people to effectively obtain information and knowledge. Knowledge Graph, with its powerful semantic processing capabilities and open organization capabilities, has laid the foundation for knowledge-based organizations and artificial intelligence applications. [0003] Knowledge graphs are mainly used to describe various entities and concepts that exist in the real world, as well as the relationship between them, and have strong data description capabili...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/28G06F16/36G06N3/02
CPCG06F16/288G06F16/367G06N3/02
Inventor 巢林林何建杉王太峰褚崴
Owner ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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