9 results about "Typing Classification" patented technology

Improved systems and methods for automated machine-learning, zero-day malware detection. Embodiments include a system and method for detecting malware using multi-stage file-typing and, optionally pre-processing, with fall-through options. The system and method receive a set of training files which are each known to be either malign or benign, partition the set of training files into a plurality of categories based on file-type, in which the partitioning file-types a subset of the training files into supported file-type categories, train file-type specific classifiers that distinguish between malign and benign files for the supported file-type categories of files, associate supported file-types with a file-type processing chain that includes a plurality of file-type specific classifiers corresponding to the supported file-types, train a generic file-type classifier that applies to file-types that are not supported file-types, and construct a composite classifier using the file-type specific classifiers and the generic file-type classifier.

The invention discloses an intention recognition method and device, equipment and a medium. The method comprises the steps that a first input text is acquired; performing intention type judgment based on the first input text, wherein the intention type comprises a single intention, multiple intentions and a fuzzy intention; determining a first processing mode based on the intention type judgment result; processing the first input text by adopting the first processing mode to obtain a target input text; and performing intention recognition based on the target input text to obtain an intention recognition result. Due to the fact that different processing methods are adopted for different types of problems after complex intention type classification is conducted on the text, the problem that complex intention recognition is not accurate is better solved.

The invention discloses a multi-page bidding document-oriented classification and key information extraction method and system, and the method comprises the steps: obtaining bidding document image data containing a plurality of pages, and constructing a corresponding document representation data set; performing structured modeling on bidding document image data corresponding to each page in the document representation data set, extracting and fusing multi-modal features, and constructing unified page representation; based on the unified page representation, document module type classification is carried out on the pages, and structure category labels which all the pages belong to are obtained; on the basis of the structure category labels of the pages, in combination with the multi-modal features of the corresponding pages, key information extraction operation is executed, and target field information contained in the corresponding pages is extracted; and outputting a structured result, wherein the structured result comprises the structure category label to which each page belongs and the corresponding target field information. According to the method, accurate classification of the pages in the bidding and tendering document is realized, targeted key information extraction is performed, and the method has relatively high accuracy, maintainability and actual landing capability.

The present invention relates to a consumer inner tendency typing analysis model production system and method using generative AI, and the present invention can automatically produce a consumer typing module that can classify consumer's inner tendencies into 256 types based on four tendency topics simply by inputting a client company's topic. Through this consumer typing module, the client company can provide customized customer services and customized marketing strategies for each consumer type, along with product recommendations and personalized services.

The present invention relates to a system for producing a consumer inner disposition typing analysis model by using generative AI. The present invention may allow companies to customize production to be suitable for various customers by generating a final typing module including a question and answer set for consumer type classification according to disposition topics using generative AI and allow customer companies to establish customized customer services and customized marketing strategies for each consumer type and provide product recommendation and personalization services through a consumer typing module.

Systems and methods for text analysis are provided. Various embodiments of the present technology provide systems and methods for improved text analysis by providing a comprehensive robust solution that solves character-set identification and print type classification along with text detection from scene text images / documents. Systems and methods for improved text analysis integrate text detection, character-set identification, and print type classification into a unified framework.

The invention provides a text multi-type classification method based on a self-iteration rule model, and the method comprises the steps: carrying out the word segmentation of a type of related texts and unrelated texts one by one, and obtaining a related word set and an unrelated word set; determining lexical item scores according to the lexical item frequency of the related word set, and cutting down the lexical item scores of the lexical items in the irrelevant word set to form an initial classifier; each text is scored and sorted by using the initial classifier, and iterative training of the primary classifier is completed; and iteration training of the classifier is continuously carried out according to the set accuracy and iteration times. According to the method, multi-type classification of unstructured text data is realized by training multiple types of classifiers which work in parallel and independently, and meanwhile, the rule model is used as the classifier, so that the classification result has interpretability.

The invention discloses a violation speech processing method and device based on NLP, and computer equipment. The method comprises the following steps: acquiring a speech text, and preprocessing the speech text to obtain a preprocessed speech text; extracting multi-dimensional features from the preprocessed speech text by using a pre-training language model, and fusing the multi-dimensional features to obtain a comprehensive violation risk representation; performing main violation type classification and fine-grained label identification on the comprehensive violation risk representation through a multi-task learning model, and calculating a confidence score to obtain a prediction result; wherein the prediction result comprises a confidence score and a severity level; wherein the confidence coefficient is used for representing the degree of mastering the correctness of the current result and the measurement of the reliability of the multi-task learning model. By implementing the method provided by the invention, accurate identification and intelligent grading disposal of various complicated violation types can be realized, the adaptability of the system to new violation forms and low-resource languages is enhanced, and the manual auditing cost and pressure are reduced.