Intelligent question and answer method and system based on pet knowledge graph

A technology of knowledge graph and intelligent question answering, applied in the field of intelligent question answering method and system based on pet knowledge graph

Pending Publication Date: 2019-09-06
袁琦
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  • Application Information

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However, there is no mature intelligent question answerin...

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  • Intelligent question and answer method and system based on pet knowledge graph
  • Intelligent question and answer method and system based on pet knowledge graph
  • Intelligent question and answer method and system based on pet knowledge graph

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[0040] In order to make the above objects, features and advantages of the present invention more obvious and comprehensible, specific implementations of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0041] In the following description, a lot of specific details are set forth in order to fully understand the present invention, but the present invention can also be implemented in other ways different from those described here, and those skilled in the art can do it without departing from the meaning of the present invention. By analogy, the present invention is therefore not limited to the specific examples disclosed below.

[0042] Second, "one embodiment" or "an embodiment" referred to herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. "In one embodiment" appearing in different places in this specification does not all refer to ...

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Abstract

The invention discloses an intelligent question answering method and system based on a pet knowledge graph, and the method comprises the steps: constructing a named entity dictionary, abstracting questions, and facilitating the classification of the questions. A method of combining word2vec with Levenshtein Distance is provided to realize entity linking, and experiments show that the method is effective. Texts are trained by constructing a text classifier based on Naive Bayes, and the improved TF-IDF naive Bayes classification algorithm is provided, the distribution situation of feature wordsin a text set and the category distribution situation are considered, and the improved TF-IDF effectively improves the text classification effect. Through the result of the text classifier, the intention of the natural language question is determined, and the natural language question is matched with the corresponding word sequence graph. The word order graph is converted into a similar SQL querystatement of the OrientDB, and querying is performed in a graph database storing the knowledge graph. Finally, the constructed intelligent question and answer system based on the knowledge graph is displayed in an example, and experiments show that the system has a relatively high application value in question and answer application in the field of pets.

Description

technical field [0001] The invention relates to the technical field of intelligent question answering systems, in particular to an intelligent question answering method and system based on pet knowledge graphs. Background technique [0002] With the improvement of people's living standards, the continuous increase of work pressure, the weakening of urban interpersonal relationships and many other reasons, more and more families start to keep pets. "Sucking dogs" and "stroking cats" have become a trend in the past two years, and the pet economy continues to grow. According to the analysis of the "White Paper on China's Pet Industry in 2018", the number of pets in my country has exceeded 168 million in 2018, of which cats and dogs are the main types. In the field of pets, pet medicine is a subdivision with huge market potential. However, the number of veterinarians in China is very small at present, which is far behind the growth of the number of pets. Platforms represented...

Claims

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Application Information

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IPC IPC(8): G06F16/332G06F16/35G06F16/36G06F17/27
CPCG06F16/3329G06F16/367G06F16/355G06F40/242G06F40/295Y02D10/00
Inventor 袁琦
Owner 袁琦
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