Beijing Xiaomi Intelligent Technology Co., Ltd.

Beijing Xiaomi Mobile Software Co., Ltd.

Beijing Xiaomi Pinecone Electronics Co., Ltd.

Fushun Research Institute of Petroleum and Petrochemicals

China Petroleum Corporation

Qun Guo

Erli Meng

Bin Wang

Liang Shi

Xiao Lu

Hongxu Ji

Shuo Wang

Yupeng Chen

Baoyuan Qi

Lei Sun

Minghua Guan

Xiangchen Fang

Fenglai Wang

Ling Lan

Xiaobing Song

Guang'an Jiang

Zhengnan Yu

A keyword extraction method includes: extracting candidate words from an original document to form a first word set; acquiring a first association degree between each first word thereof and the original document, and determining a second word set according to the first association degree; for each second word in the second word set, inquiring, in a word association topology, at least one node word satisfying a condition of association with the second word and forming a third word set, the word association topology indicating an association relation among multiple node words in a predetermined field; and determining a union set of the second and third word sets, acquiring a second association degree between each candidate keyword in the union set and the original document, and selecting, according to the second association degree, at least one candidate keyword from the union set, to form a keyword set of the original document.

Keyword extraction method, apparatus and medium

A method and device for keyword extraction and a storage medium. The method includes receiving, at a terminal, an original document, acquiring, at the terminal, a candidate set by extracting at least one candidate phrase from the original document, acquiring, at the terminal, an association degree between the at least one candidate phrase in the candidate set and the original document, acquiring, at the terminal, a divergence degree of the at least one candidate phrase in the candidate set, and updating, at the terminal, a key phrase set of the original document by selecting the at least one candidate phrase from the candidate set as at least one key phrase based on the association degree and the divergence degree.

Method and device for keyword extraction and storage medium

A method for optimizing a training set for text classification includes: the training set for text classification is acquired; part of samples are selected from the training set as a first initial training subset, and an incorrectly tagged sample in the first initial training subset is corrected to obtain a second initial training subset; a text classification model is trained according to the second initial training subset; the samples in the training set are predicted by the trained text classification model to obtain a prediction result; an incorrectly tagged sample set is generated according to the prediction result; a key incorrectly tagged sample is selected from the incorrectly tagged sample set, and a tag of the key incorrectly tagged sample is corrected to generate a correctly tagged sample corresponding to the key incorrectly tagged sample; and the training set is updated by using the correctly tagged sample.

Method and device for optimizing training set for text classification and storage medium

Text content is determined. The text content is input to a content classifying model. The content classifying model is adapted to determine a probability of the text content belonging to a category. An evaluated value of quality of the text content is determined according to the probability of the category and a weight of the category. The weight represents importance of the category.

Method and device for evaluating quality of content, electronic equipment, and storage medium

The present disclosure relates to a method and a terminal for performing word segmentation on text information, and a storage medium. The method includes: acquiring the text information and configuration information, in which the configuration information includes at least two first word segmentation rules; converting the first word segmentation rules into second word segmentation rules according to a predetermined rule; in response to determining that an intersection exists between character strings of the text information matched by two of the second word segmentation rules, determining that two first word segmentation rules corresponding to the two of the second word segmentation rules associated with the intersection conflict; and processing the text information according to the configuration information, and outputting a result of the word segmentation on the text information.

Method and terminal for performing word segmentation on text information, and storage medium

The present disclosure, belonging to the technical field of natural language processing, provides a text sequence segmentation method. The method can include acquiring n segmentation sub-results of the text sequence, the n segmentation sub-results being acquired by segmenting the text sequence by n segmentation models, and processing the n segmentation sub-results by a probability determination model branch in a result combination model to acquire a segmentation probability of the each segmentation position. The method can further include processing the segmentation probability of the each segmentation position by an activation function in the result combination model to acquire a segmentation result of the text sequence. According to the present disclosure, using each segmentation position in the text sequence as a unit, segmentation results of a plurality of segmentation models are combined, such that the accuracy of segmentation of a new text can be improved.

Text sequence segmentation method, apparatus and device, and storage medium thereof

The present invention relates to a medium-pressure hydrocracking process which uses a fresh hydrogen resource and a hydrosaturation catalyst with reduced metals of group VIB and/or group VIII as the active ingredients to selectively and deeply hydrosaturate jet fuel and/or diesel cuts derived in the medium-pressure hydrocracking process.

Medium-pressure hydrocracking process

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Beijing, China

Qun Guo