3 results about "Dependency grammar" patented technology

This invention belongs to the field of computer vision technology, specifically a tree-structured video description generation method based on perceptual grammar knowledge. This invention explicitly utilizes semantic information inherent in language, using dependency structure analysis tools to transform sequential sentences into a syntax tree structure. By analyzing the connections between parent and child nodes in the tree, the dependency grammar structure within the sentence is explicitly modeled. A perceptual context attention network is used to model the contextual information generated along different paths during the generation process. Simultaneously, reinforcement learning and iterative generation training methods are introduced during the training phase to further improve model performance. Qualitative and quantitative experiments demonstrate that the model has the ability to generate more accurate and semantically richer descriptions.

The application discloses a text similarity determination method, device and equipment and a storage medium. The method comprises the following steps: obtaining a plurality of texts to be processed, performing word segmentation processing on each text to obtain a plurality of word segmentation results corresponding to each text respectively; determining CoNLL format data corresponding to each word segmentation result, and constructing a dependency grammar tree corresponding to each text according to the CoNLL format data corresponding to each text respectively; generating a dependency matrix matched with each text according to the dependency grammar tree corresponding to each text respectively, and determining a target similarity between the plurality of texts according to the dependency matrices. The technical scheme of the embodiment of the application can reduce the complexity of the text similarity determination method and improve the accuracy of the text similarity determination result.

The application discloses a rule and dependency grammar-based spatiotemporal correlation degree calculation method, which comprises the following steps: obtaining an open field text sequence, and preprocessing the text sequence to obtain a preprocessed text sequence; performing syntactic analysis on the preprocessed text sequence, formulating a rule matching table, and matching the syntactic analysis result according to the rule matching table to obtain candidate triplets and spatiotemporal information; calculating a spatiotemporal correlation degree value according to a dependency path of a relation predicate in the candidate triplets and the spatiotemporal information, a dependency distance of a head entity and the spatiotemporal information, a spatiotemporal feature of head and tail entity types, and a spatiotemporal semantic feature of the relation predicate; defining two threshold values, comparing the spatiotemporal correlation degree value with the two threshold values, determining a classification result of the spatiotemporal correlation degree, and generating a knowledge expression model. The application accurately calculates spatiotemporal correlation by comprehensively considering the context and spatiotemporal information of the text, thereby obtaining a spatiotemporal knowledge expression model and more accurately conveying the semantics of the text.