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Automatic knowledge venation construction method based on massive digital books

A digital book, automatic construction technology, applied in knowledge expression, electronic digital data processing, structured data retrieval, etc., can solve problems such as being stuck in a large number of similar books and unable to learn efficiently

Active Publication Date: 2018-04-13
ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem that users are stuck in a large number of similar books and unable to learn efficiently when they learn the knowledge of a certain topic, the present invention proposes a method for automatically building knowledge context based on massive digital books, which can greatly facilitate users to carry out efficient knowledge learning

Method used

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  • Automatic knowledge venation construction method based on massive digital books
  • Automatic knowledge venation construction method based on massive digital books
  • Automatic knowledge venation construction method based on massive digital books

Examples

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Embodiment

[0115] Below in conjunction with the method of this technology describe in detail the concrete steps that this example implements, as follows:

[0116] (1) if figure 1 As shown, obtain a large number of e-books related to "computer network", analyze their directory structure, and clean the chapter titles;

[0117] (2) if figure 1 As shown, next, the similarity between directories is obtained through the weighted word2vec method, and then the knowledge unit is constructed according to the clustering algorithm. Then, according to the partial order relationship between the book catalogs, the connection relationship between the knowledge units is obtained, and then the knowledge graph is constructed;

[0118] (3) if figure 1 As shown, after obtaining the knowledge map, according to the proposed path selection method, select TOP K important, orderly and less redundant learning paths to build the knowledge context;

[0119] (4) The knowledge context constructed in step (3) is vi...

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Abstract

The invention discloses an automatic knowledge venation construction method based on massive digital books. The method comprises the steps that metadata information of the digital books is stored in aLucene index file, and if a user retrieves a theme q, a set of the books related to the q can be obtained; the similarity of directory titles is calculated through a weighted word2vec method, first-level directories of the q-related textbooks are clustered through a bottom-to-up condensation-type hierarchical clustering algorithm to obtain a knowledge unit set; the connection relation among knowledge units is established according to the partial ordering relation among chapters in the books, and finally a complete knowledge map is constructed; and TOP K important, ordered and little-redundancy learning paths are mined out from the knowledge map, and the knowledge venation formed by the learning paths is visually displayed by imitating the form of a subway map. According to the method, a digest extraction framework based on the massive digital books is proposed for the first time, the knowledge venation extracted by the framework can comprehensively consider the informativity, the smoothness and the coverage, and therefore a user can quickly and efficiently learn knowledge.

Description

technical field [0001] The invention relates to a knowledge mining method based on massive digital books, in particular to a method for automatically building knowledge context based on massive digital books. Background technique [0002] Books are an important medium for transferring knowledge between teachers and students. In the last decade, projects such as Google Books and the Million Books Project have embarked on large-scale book digitization efforts. This provides great help for users to find and read books. However, the abundance of books also creates a certain amount of distraction, and when learning a subject, we tend to get bogged down in thousands of books. Therefore, combining these thousands of books into a concise but comprehensive picture will greatly facilitate the learning of knowledge. [0003] At present, some researchers have begun to study how to extract and visualize abstracts in the fields of news, scientific literature, user-generated content, an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06N5/02G06N99/00
CPCG06F16/21G06F16/2228G06N5/022G06N20/00
Inventor 鲁伟明马朋坤魏宝刚庄越挺
Owner ZHEJIANG UNIV
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