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A method of writing off-topic detection

A detection method and composition technology, applied in the computer field, can solve problems such as text similarity calculation threshold dependent composition feature extraction, etc.

Active Publication Date: 2020-06-23
NORTH CHINA UNIVERSITY OF TECHNOLOGY
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

This research method based on text similarity is mainly considered from the content of the composition itself. It can use the semantic information of the composition text to conduct digression detection research, but the disadvantage is that the threshold value calculated by text similarity is heavily dependent on the extraction of composition features.

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  • A method of writing off-topic detection
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Embodiment Construction

[0056] In order to better explain the present disclosure and facilitate understanding, the present disclosure will be described in detail below through specific implementation manners in conjunction with the accompanying drawings.

[0057] All technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terms used herein in the description of the present disclosure are for the purpose of describing specific embodiments only, and are not intended to limit the present disclosure. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0058]In the relevant embodiments of the present disclosure, the following methods are used to realize the composition digression detection:

[0059] The first one uses a classification method to discriminate off-topic English compositions under the same topic that have been marked and sc...

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Abstract

An embodiment of the present disclosure relates to a composition digression detection method, which includes: performing topic model training on a composition set to obtain a Biterm-LDA topic model for a composition, and performing Doc2vec model training on a document set to obtain a Doc2vec document vector model; Combine the LDA topic model and the text representation of the Doc2vec document vector model to obtain the combined features; perform dimension reduction and feature optimization on the combined features of the composition based on the multi-layer perceptron of the Siamese network; divide the topic composition after dimension reduction and feature optimization into topic-specific Composition and off-topic composition, construct a topic center for a part of the on-topic composition, and calculate the remaining part of the on-topic composition and off-topic composition according to the topic center, and obtain a set of thresholds for the same topic; use the ROC curve according to a set of thresholds Filter to get the best threshold. The disclosure can dynamically calculate the optimal threshold for different topic compositions.

Description

technical field [0001] The present disclosure relates to the field of computer technology, in particular to a method for detecting digressions in composition. Background technique [0002] In the review of composition in primary and secondary schools, relevance to the topic is the basic requirement for the quality of a composition, and it is also a key point of examination for a composition. To be relevant to the topic of a composition means that a composition is carried out around a theme as a whole. In addition to clarifying the scope and requirements of the topic, it is also required that the theme of the entire composition runs through the whole text, that is, all the content of the composition is consistent with the topic. Therefore, it is necessary to carry out digression detection on primary and middle school compositions, which can detect the situation where the writer organizes language randomly and makes up words blindly, and can also examine the relevance of the e...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F40/30G06F16/35
CPCG06F16/353G06F40/30
Inventor 刘杰周建设张凯史金生骆力明马晓丽
Owner NORTH CHINA UNIVERSITY OF TECHNOLOGY
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