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Method and system for calculating relevant knowledge points of domain knowledge points

A technology of domain knowledge and knowledge points, applied in the field of electrical data processing, can solve the problems of insufficient utilization of digital resources and semantic vector processing methods, and achieve the effect of simple and convenient calculation and good accuracy

Inactive Publication Date: 2016-03-30
PEKING UNIV FOUNDER GRP CO LTD +2
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Problems solved by technology

[0007] For this reason, the technical problem to be solved by the present invention is that information recommendation in the prior art has limitations, and the existing digital resources and semantic vector processing methods are not fully utilized, so a method for obtaining semantic vectors and its use in information Method and system for determining relevant knowledge points applied in recommendation

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  • Method and system for calculating relevant knowledge points of domain knowledge points
  • Method and system for calculating relevant knowledge points of domain knowledge points
  • Method and system for calculating relevant knowledge points of domain knowledge points

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Embodiment 1

[0030] The semantic vector of knowledge points is a way to describe knowledge points in the vector space. By obtaining the semantic vectors of knowledge points, knowledge points can be made more computable. Fields such as text classification have potential application value.

[0031] This embodiment provides a method for calculating related knowledge points of domain knowledge points by means of semantic vectors, including the following steps:

[0032] S1. First, acquire domain knowledge points, which are basic units representing a certain type of information. General knowledge points are classified based on domains, such as historical domains and military domains. If you need to obtain knowledge points in the field of history, you can obtain the entries in the historical encyclopedia as knowledge points in this field.

[0033] S2. Then, select a reference text, perform word segmentation on the reference text, and obtain a word segmentation result. The words in the word seg...

Embodiment 2

[0055] In this embodiment, a method for calculating related knowledge points of domain knowledge points is provided, and the related knowledge points are used to recommend knowledge points. The specific steps are as follows.

[0056] The first step is to extract the name set of domain knowledge points from the domain encyclopedia O={o 1 , o 2 ,...,o n}, the number of domain knowledge point names is n. Add the names of domain knowledge points to the tokenizer dictionary.

[0057] In the second step, a certain number of e-books are selected from the domain digital publishing resources, and texts are extracted from the selected e-books.

[0058] The third step is to use a tokenizer to segment the extracted text, and use all the words obtained after word segmentation as knowledge points. Since there are enough digital resources in the selected field, the knowledge points include domain knowledge points and other Some other knowledge points besides. All these knowledge points...

Embodiment 3

[0072] In this embodiment, a system for calculating related knowledge points of domain knowledge points is provided, and the structural block diagram is as follows image 3 shown, including

[0073] Extraction unit: obtain domain knowledge points;

[0074] Word segmentation unit: determine the reference text, perform word segmentation on the reference text according to the domain knowledge points, obtain word segmentation results, use the words in the word segmentation results as knowledge points, and the knowledge points include the domain knowledge points and other knowledge point;

[0075]Index unit: build an index for each knowledge point in the word segmentation result in turn;

[0076] Training unit: determine the semantic vector of each field knowledge point according to the index of the knowledge point and the sequence of the knowledge point;

[0077] Similarity calculation unit: for each domain knowledge point, determine the similarity between the domain knowledge ...

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Abstract

The invention provides a method for calculating relevant knowledge points of domain knowledge points. The domain knowledge points are obtained at first; all knowledge points are obtained from a reference text through word separation; the knowledge points include the domain knowledge points and other knowledge points; then, an index is established for each knowledge point in a word separation result; semantic vectors of the domain knowledge points are obtained in a neural network model training manner according to the index and the sequence of each knowledge point; therefore, semantic information of the knowledge points is quantified; semantic features of the semantic information are embodied in a digital manner; therefore, the knowledge points are more convenient to analyze subsequently; then, the similarity among the domain knowledge points is determined according to the semantic vectors of various domain knowledge points; relevant knowledge points can be easily distinguished according to the degree of the similarity; the number of the relevant knowledge points can be selected according to requirements; and the method is simple and convenient to calculate and high in accuracy and is applied to the aspects, such as recommendation and retrieval.

Description

technical field [0001] The invention relates to the field of electrical data processing, in particular to a method for calculating related knowledge points of knowledge points in the field. Background technique [0002] Digital publishing resources have become one of the main ways of information provision. People have shifted from paper reading to electronic reading in large numbers. Digital publishing resources include e-books, digital encyclopedias, digital periodicals, digital newspapers, etc. The information provided by digital publishing resources is usually more authoritative and accurate than that of the Internet. Therefore, how to improve people's learning or reading experience according to the characteristics of digital publishing resources has become particularly important. [0003] In Technology Enhanced Learning (TechnologyEnhancedLearning), the development of recommender systems is getting more and more attention. However, most recommendation systems use use...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06F17/27
Inventor 叶茂汤帜徐剑波马佳乐杨亮
Owner PEKING UNIV FOUNDER GRP CO LTD
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