8 results about "Word count" patented technology

The application provides a template engine-based scheme compiling method and system, which comprises the following steps: creating a template, adding directory chapters and generating chapter numbers; distributing chapters to editors according to the directory chapters; when the word count of the edited content is greater than a preset word count, extracting key elements from the edited content by using a key element extraction model; obtaining a historical database, comparing the schemes in the historical database according to the key elements by using a similarity analysis model; taking the scheme with the highest similarity score and a similarity score higher than a preset score as a highly similar scheme, automatically filling the chapter content in the highly similar scheme into the corresponding chapter to be edited, classifying the filled template according to the key elements by using a classification model, and exporting the template to a storage location of the corresponding classification according to a preset format and layout to obtain a final scheme. The application realizes online scheme compilation, simplifies the compiling process, and improves office efficiency.

This application provides a method and system for enterprise risk assessment based on a large language model and text quantitative analysis. The method includes: acquiring and parsing the current first annual report text of a target enterprise to obtain several subheadings and corresponding subtexts; dividing the subtexts corresponding to each subheading into corresponding semantic chapters using a preset large language model, thereby generating corresponding first reconstructed texts; extracting corresponding first target texts from the first reconstructed texts according to preset target semantic chapters; performing a difference comparison analysis on the first target text and the second target text using the large language model to obtain several difference texts and corresponding several change trends; calculating several analysis indicators based on the number of each difference text, each change trend, and the average number of words in each chapter, and conducting a risk assessment of the target enterprise based on each analysis indicator to generate a risk assessment result, thereby improving the effectiveness and accuracy of the risk assessment.

The application discloses a product promotion type script intelligent generation method and system, and relates to the technical field of script intelligent generation.The product promotion type script intelligent generation method and system comprise the following steps: S1, collecting product script generation basic data, audience preference data and script generation hard constraint data and preprocessing; S2, generating a style constraint parameter set according to a collaborative filtering similar neighborhood discriminant analysis result; S3, outputting a feasible structure configuration and script text data according to a structure feasibility discriminant analysis result; S4, jointly evaluating information coverage, format rules, repeated stacking and word number overlimit, and performing directional repair and finalization signing and archiving.The product promotion type script intelligent generation method and system solve the problem that existing product promotion type script intelligent generation methods usually generate first and then cut and repair to meet the constraints of word number, format and forbidden words, but lack structure feasibility determination and consistency repair when multiple hard constraints coexist, which easily leads to the problem of unusable script structure degradation.

The application relates to a document abstract generation method, a computer device, a computer readable storage medium and a computer program product. The method comprises the following steps: reading text content in a document; performing blocking and screening on the text content to obtain a plurality of target text blocks; each target text block is provided with a corresponding attention intensity; for each target text block, the number of abstract words of the target text block is determined according to the attention intensity of the target text block; through a preset large language model, a plurality of target text blocks, the number of abstract words of each target text block and a prompt word for indicating abstract generation are used for multiple rounds of abstract processing, and an abstract result corresponding to the document is output. According to the method, the number of abstract words corresponding to each text block in the document can be determined according to the attention intensity of the text block, the content in the text block with high importance can be ensured to be retained more, different types of documents are processed individually based on the attention intensity of the text block, and the quality of the generated abstract is improved.

Verbal language analysis is provided to users. The user enrolls or subscribes for verbal language analysis or analytics. The user carries out or conducts a conversation with a third party. An intelligence device associated with the user records the conversation. The intelligence device performs verbal language analysis on the conversation. The verbal language analysis generates individual metrics for verbal factors of energy, word count, inflection, tone (e.g. pitch and sentiment), rate, and / or the like. A verbal intelligence index is determined from the individual metrics using aggregation, averaging, weighted averaging, and / or the like. An interface component generates views to display to the user for review of the conversation to facilitate better verbal performance during current and in future conversations.

This invention relates to the field of job descriptions, and more particularly to a deep learning-based method for automatically generating job descriptions. The method includes: preprocessing acquired job description text data to obtain multiple modules; attaching corresponding module tags to word segments in each module; constructing a module aggregation degree reflecting the semantic purity within each module based on the probability distribution of words within each module; extracting boundary local word sequences between adjacent modules and calculating information entropy, and constructing a boundary jump degree based on the module aggregation degree; constructing structural weights for each module based on the boundary jump degree and the word count ratio of each module; using the structural weights as adaptive weighting coefficients to improve the prediction loss function of the ProphetNet model, obtaining an improved ProphetNet model for generating job description text. This invention improves the writing efficiency and quality in recruitment scenarios.

Generating a response to a query from a long input can be difficult because of the number of data units to be analyzed, where a data unit can be a video frame, an image, a page, a slide, a word count, or other data unit. The FRAG process can first reduce the number of data units to be analyzed, such as using down-sampling, temporal proximity, visual similarity, or other algorithms. The reduced number of data units can be further reduced by scoring each data unit and selecting the data units that have the highest likelihood of addressing the query, such as using a Top-K or scoring threshold parameter. The data units that satisfy the scoring algorithm can be processed by an LMM to generate a response to the query. The focusing of the data units for the LMM can improve the quality of the response that the LMM generates.