7 results about "Delimiter" patented technology

A system and method guide an Artificial Intelligence engine to determine the semantic and grammatical correctness of a user-expanded sentence in real-time. The sentence validation process involves receiving input from the user, the input includes sentence fragment that the user wishes to expand and user-expanded sentence that the user constructs on the fragment provided. The inputs are broken down into tokens. The word-level tokenization algorithm is used, which identifies tokens by splitting the text into spaces, punctuation marks, and other delimiters. Further, a token comparison algorithm is used to assess the relationship between the sentence fragment and the user-expanded sentence to analyze order and placement. Once the token comparison is complete, a prompt is generated using prompt generator to evaluate grammatical and semantic evaluation of the user-expanded sentence. Real-time feedback is provided to the user based on grammatical and semantic evaluation.

The application provides a kind of based on SSE's stream data processing display method, system and related equipment, method includes based on the preset parameter construction and initiates HTTP request, establishes the SSE connection with server;In the data stream of the SSE connection, continuously receive data segment and append to data buffer;The data buffer is scanned and identified pre-defined message separator, to extract one or more independent SSE message from the data buffer and store in message queue;From the message queue, the SSE message is obtained, and the SSE message is split into character sequence and stored in character queue;According to the preset timer, periodically take out single or multiple characters from the character queue, render the character to user interface.The application realizes the smooth typewriter display effect by constructing double-layer queue rendering technology, and improves the response performance of SSE stream data in complex business scenarios.

This invention discloses a hierarchical perception-based method and system for analyzing complex English sentences, relating to the interdisciplinary fields of natural language processing and intelligent education. By defining structural delimiters, sentences are divided into syntactic levels according to the number of effective delimiters, first eliminating invalid parallel structural delimiters; then, a syntactic encoding module completes text segmentation, hierarchical tagging, word embedding, and feature fusion; a hierarchical perception module calculates feature weights and generates target syntactic features; finally, a syntactic decoding module outputs the sentence's main body and modifier decomposition results. The hierarchical framework constructed by this invention fully covers the core modifiers of English, is suitable for the scenario of complex sentences in the College Entrance Examination (Gaokao), and can achieve accurate and lightweight decomposition of all types of complex sentences. It effectively solves the problems of irregular decomposition, poor generalization, and poor adaptability of traditional methods, and the analysis process is clear and teachable.

The application provides a URL-based API asset merging method and system, which comprises the following steps: obtaining host access record log data; based on the access record log data, extracting a URL, using a specific separator to split the URI, and forming a word set array; according to the word set data, sequentially taking two words as a relationship, taking the words as nodes, constructing a word relationship graph, and calculating the out-degree and in-degree of the words; according to the out-degree and in-degree obtained in the foregoing step, selecting words with out-degree or in-degree less than a specified threshold value by specifying the threshold value; based on the words obtained in the foregoing step, screening out URIs containing the corresponding words, and calculating the URIs with high similarity in the full-amount URIs by using minhash; based on the URIs selected in the foregoing step, calculating the support degree of the selected corresponding words, and replacing the words with a wildcard string if the support degree is less than a specified threshold value, so as to realize API normalization. The application solves the technical problems of a large API asset list and high dependence on manual operation experience.

Extractive schema linking includes generating a tokenized schema from an SQL schema, a tokenized natural language question, and tokenized candidates. The tokenized candidates are generated by tokenizing candidates from the SQL schema. Each tokenized candidate is formed by a string of tokens having a first token representing an initial delimiter and a last token representing an end delimiter. Vectorial representations of the tokenized schema, the tokenized natural language question, and tokenized candidates are generated, and transformed vectorial representations generated by processing the vectorial representations through a decoder-only model. Concatenated vectors are generated from the transformed vectorial representations of the tokenized candidates, the concatenated vectors generated by concatenating a first transformed vectorial representation corresponding to the first token with a last transformed vectorial representation corresponding to the last token of each tokenized candidate. Quantitative relevancies of the plurality of candidates from the SQL schema are generated based on the concatenated vectors.

Methods in a system for programming in natural language, comprising the steps - Machine capture and analysis (S100) of digital input information, which includes a plurality of input elements in natural language, - Determine (S200), by the system, based on analyzing the input information, an elementary data type of an input element of the input information, and - Generating (S300) source code for the elementary data type, the step of which includes capturing the input information: - Dividing the input information into sentences, where a sentence comprises a sequence of consecutive input elements in the input information and ends with a separator; and where the step of determining (S200) the elementary data type comprises the following substeps: - Recognizing a first set comprising a first sequence of input elements and a second set comprising a second sequence of input elements, wherein the first sequence and the second sequence differ only at one position, wherein the first sequence includes a first difference input element at this position and the second sequence includes a second difference input element at this position, - Determining the elementary data type for the difference input elements; assigning the specified elementary data type to each of the difference input elements.

To provide a decoder and a method for deriving a necessary parameter from an access unit.SOLUTION: A video decoder 20 comprises an in-loop filter 90 which filters a reconfiguration version of a decoded picture, and a parameterizing unit. The parameterizing unit reads in-loop filter control information for parameterizing the in-loop filter from a parameter set located in an access unit of a decoded picture following a video encoding unit along the sequence of a data stream 14 and / or a part of a video encoding unit following data included in a video encoding unit carrying block-based prediction parameter data and predicted residue data along the sequence of the data stream, and also parameterizes the in-loop filter so as to filter the reconfiguration version of the encoded picture by a method corresponding to the in-loop filter control information.SELECTED DRAWING: Figure 2