6 results about "Cybertext" patented technology

This invention provides a method and apparatus for identifying online nuisance text, comprising: preliminarily judging the target online text by extracting URL links from the target online text; if the judgment cannot be made, calculating the invalid information score and generating a pinyin list, a keyword list, and a keyword pinyin list for the target online text; calculating the online nuisance score for each keyword by analyzing the distribution of the character elements of each keyword in the target online text and the distribution of the keyword pinyin in the pinyin list of the target online text; revising the online nuisance score based on the invalid information score, and obtaining the online nuisance text recognition result based on the revision result. This invention can accurately identify online nuisance text through fuzzy matching of online nuisance keyword characters and pinyin, and can effectively address information hiding methods such as segmentation, reverse order, vertical text arrangement, and homophones in the target text.

The invention discloses a campus forum content management method based on artificial intelligence, and relates to the field of web text processing. The method comprises the following steps: firstly, obtaining post data in a preset time range in a campus forum to obtain a post set; preprocessing the post set, inputting the post set into a pre-trained identification model, identifying posts involving negative contents, and taking the posts as a target set; constructing a topological structure chart of the posting set according to the overlapping degree of the topics involved among the posts and the sequence of the publishing time, and calculating the connectivity of each post according to the topological structure chart; and calculating the influence of the negative content in the campus forum by integrating the connectivity of each post in the target set. The invention further provides a corresponding device, equipment and a storage medium, the recognition accuracy of the negative content in the campus forum is improved, and comprehensive evaluation on the influence of the negative content in the campus forum is achieved.

The invention belongs to the technical field of natural language processing and information summarization, and particularly relates to a semantic integrity driven iterative event venation construction method and a computer program product, the method comprises the following steps: 1, preliminary event venation construction: screening a document related to a target event from a multi-source web text, and constructing an initial event development sequence; step 2, semantic integrity detection and reflection analysis: performing semantic integrity detection on each event in the initial event development sequence, identifying missing basic semantic elements, and generating a list of semantic elements to be complemented; step 3, iterative completion and final event venation output: based on the to-be-completed semantic element list, generating element-oriented query to perform directional retrieval, and integrating new information obtained by retrieval into the event venation; and 4, repeatedly executing the steps 2 to 3 to form an iteration closed loop of generation-reflection-complementation until an iteration termination condition is reached, and outputting a final event context.

The application discloses a network text public emotion mining method and system based on supervised learning, and establishes a coding framework of network text multidimensional public emotion according to research literature, expert opinions and experience of dissemination science; coding training is conducted on each coder so that each coder reaches consistency; network text is captured, and each coder carries out scoring processing according to the given coding framework; a text feature expressing a topic and content in the network text is extracted by using a LIWC dictionary, and a text data set is constructed; a supervised machine learning method is used, network text scoring and the text data set are combined for training, a text analysis model is obtained through matrix parameter adjustment and cross-validation methods; and the evaluation subject attribute in new network text and multidimensional public emotion scores are obtained by using the text analysis model. The application can accurately and professionally evaluate the public emotion of short texts, and solves the problem of lack of Chinese annotation materials of short text public emotion in the evaluation of daily situations.

The application provides a text security judgment method and device based on consensus verification, and belongs to the technical field of natural language processing. The method comprises the following steps: obtaining a target text; inputting the target text into a judgment model to obtain a judgment result output by the judgment model, wherein the judgment result is used to indicate whether the target text is a safe text, the safe text does not include harmful expressions, the harmful expressions include a first harmful new word, and the first harmful new word is a word with harmful word meaning in the target text; wherein the first harmful new word is determined based on consensus verification, and the consensus verification is based on information searched by a search engine. The harmful new word with different word meanings in the context and the independent use can be accurately identified, the identification ability of implicit harmful network expressions is enhanced, and the accuracy and comprehensiveness of network text harmful content detection are improved.