38 results about "Event evolution" patented technology

The embodiment of the invention provides a method and device for generating an evolution diagram of an event group. The method comprises the steps: obtaining a plurality of event evolution diagrams which indicate the evolution state of the popularity of concerned events; sequentially marking the drawing positions of a plurality of events in a combination candidate region according to the time sections of the plurality of events and the popularity of the corresponding events; and respectively enabling the plurality of event evolution diagrams to be copied in the combination candidate region according to the drawing positions, so as to generate the evolution diagram of the event group. When the position of the evolution diagram of any one event in the combined drawing region is determined, there is no need of considering the layout of other events, and the longitudinal drawing position just needs to be determined according to longitudinal heights corresponding to marked time points, thereby reducing the time complexity in layout of the event evolution diagrams, and reducing the time complexity from O(nlgn) to O(n).

The embodiment of the invention provides an analysis method and an analysis system based on an event evolution process of key words. The method comprises the steps of counting the quantity of search results within all time quanta, so as to obtain a sequence that the quantity of the search results changes along with the time quanta; performing peak detection on the sequence, so as to obtain at least one peak window; performing text analysis on the search result corresponding to the peak window, so as to obtain peak description; displaying the sequence that the quantity of the search results changes along with the time quanta, and displaying the peak description in a peak position. According to the analysis method and the analysis system of the embodiment of the invention, the sequence that the quantity of the search results changes along with the time quanta is counted, and the sequence that the quantity of the search results changes along with the time quanta and the peak description are displayed, so that the trend that the microblog information quantity changes along with time is shown, the evolution process of an event related to the key words can be shown by the trend that the microblog information quantity changes along with time, a user can know about main contents of microblog information without reading microblog contents in detail according to the peak description, and the information quantity displayed by the search results is increased.

The invention discloses an event discovery and display method based on a knowledge graph. The method comprises the following steps: S100, preprocessing each piece of government service hotline data; s200, dividing the government service hotline data in the time period selected by the user into data frames according to a time interval specified by the user, and performing event detection on the government service hotline data in each frame through a community discovery algorithm to obtain each city event; and S300, based on a bipartite graph maximum weight matching algorithm, matching events of front and back frames, establishing an event chain of each city event evolution, analyzing z-score values of each city event in the event chain, determining emergencies and emergency degrees of each city event, and performing early warning and multi-dimensional visualization on the city emergencies therein. According to the invention, various events occurring in a city can be clearly known, and detection and early warning can be carried out on emergencies in the city.

The invention discloses an event chain-based network public opinion association deduction prediction analysis method, which comprises the following steps: extracting related node events from microblog article text data according to event development, and forming a theme evolution tree and a public opinion evolution probability graph through clustering association and mode mining matching prediction, wherein corpora of a microblog training set are pre-trained through an ELMO model, and microblog articles are vectorized; combining the similar microblog data through a One-Pass clustering algorithm to obtain a node event set; performing few-label data learning through ActiveLearning, and the label quality is improved through man-machine interaction; and discovering a transfer logarithm between tags through Seq2Pat, and further constructing a Markov chain, forming a topic tree and predicting a node event evolution trend. According to the invention, extraction, association and prediction of sub-events in complex public opinion events are made up, a man-machine interaction label method with expert intervention is fully considered, and the invention is suitable for public opinion deduction analysis positioning and accurate prediction.

The invention discloses a cascading failure emergency blocking method based on an accident chain model. The method comprises the following steps: firstly offline computing and searching a high-risk accident chain by using a electromechanical transient time domain simulation method based on actual power grid data, screening out an accident chain set with first two accidents unconfigured with emergency control measure from the high-risk accident chain by considering the existing emergency control system configuration information; secondly, configuring the emergency control policy for the secondaccident of this class accident chain by adopting the offline computing method, and ensuring that the cascading event evolution process can be blocked; and finally, determining the continuous definitehappening of the first and the second accidents in the accident chain as the necessary condition for triggering the emergency control measure on the basis of accomplishing the real-time matching of the operation way by the emergency control system, wherein the economy and the timeliness of the control are both taken into consideration. Through the method disclosed by the invention, the cascadingfailure caused by the continuous disturbance development unconfigured with the emergency control measure can be timely blocked, the miss of the control opportunity is avoided, and the system loss is reduced.

The invention discloses a news event evolution analysis method based on time sequence distribution information and a topic model and relates to the field of text analysis. The method comprises the following steps: firstly, dividing a corpus into a plurality of sub-corpuses according to time by analyzing distribution characteristics, presented on a time sequence, of a news report, and by using a K-Means clustering algorithm; secondly, sequentially performing topic modeling on each sub-corpus by using the topic model, and learning the model through a Gibbs sampling method to obtain topic distribution information of each sub-corpus; finally, connecting topics between which the distance is minimum in series by calculating a Jensen-Shannon distance between each two topics in the adjacent sub-corpuses, wherein the topics are connected in series to obtain a main topic of an event, and auxiliary topics except the main topic in each sub-corpus are concerns and new developments of the event in each stage. According to the method, the mainline of event development in a news prediction and new concerns burst in each stage can be better described.

The present invention discloses an automatic extracting method of event evolving relationship based on news. The method comprises: preprocessing news information, extracting news leads, extracting news event time, extracting events, extracting event keywords, and analyzing event evolving relationship. The present invention further discloses an automatic extracting system of the event evolving relationship of news. The automatic extracting system comprises a news information preprocessing module, a news lead extracting module, a news event time extracting module, an event extracting module, an event keyword extracting module, and an evolution relationship analyzing module. Through the adoption of the automatic extracting method and system, disclosed by the present invention, the graph of event evolving relationship is more reasonable, and the relationship between events is more clear; the automatic extracting method and system have the advantages that partial problems in the present field of news evolution analysis are solved, so that the evolution analysis achieves better effects, and users can conveniently know the evolutionary skeleton of the whole news topic.

The present application relates to an event prediction method, device and terminal equipment based on event evolution knowledge ontology. Among them, the method includes: by constructing an event evolution ontology knowledge base with event evolution relationship, extracting the first event chain and the first event tuple from the event evolution ontology knowledge base, adopting remote supervision, using the first event element The group and the first event chain carry out relational data back-labeling on unstructured texts to obtain event data with event evolution relationship, and use event data training to establish an event prediction model, which can effectively and quickly obtain a large number of marked training based on knowledge. data, thereby effectively improving the accuracy of event prediction.

The present invention provides a method for constructing a legal event map, a legal event reasoning method, a device, and an electronic device, wherein the method includes: obtaining a legal event map; obtaining the first element and the second element of a legal event described by an interactive object based on a multi-round interaction strategy An element relationship; using the first element and the first element relationship to dynamically update the legal event graph to obtain a legal event evolution interaction graph. Constructing an interactive graph of legal event evolution based on multiple rounds of interactive information eliminates the static and incomplete features of the event graph, adds two features of interaction and evolution to the event graph, and constantly analyzes a legal event in the process of interacting with users and experts Supplementing the elements and relationships of the law, as well as adjusting the current legal reasoning events, and finally obtaining complete relevant information to ensure that the materials required for reasoning are accurate and complete.

The embodiment of the invention provides a method and device for generating an evolution diagram of an event group. The method comprises the steps: obtaining a plurality of event evolution diagrams which indicate the evolution state of the popularity of concerned events; sequentially marking the drawing positions of a plurality of events in a combination candidate region according to the time sections of the plurality of events and the popularity of the corresponding events; and respectively enabling the plurality of event evolution diagrams to be copied in the combination candidate region according to the drawing positions, so as to generate the evolution diagram of the event group. When the position of the evolution diagram of any one event in the combined drawing region is determined, there is no need of considering the layout of other events, and the longitudinal drawing position just needs to be determined according to longitudinal heights corresponding to marked time points, thereby reducing the time complexity in layout of the event evolution diagrams, and reducing the time complexity from O(nlgn) to O(n).

The invention provides a method for immediately tracking random event evolution based on Internet mass information. According to the method, an initial spatial vector of an event is constructed by using basic characteristic elements, in the tracking process, entropy values of frequently-used words of Internet increment information are computed and counted on the basis of the initial spatial vector, the growth and structural change of the initial spatial vector of the event are determined by taking the entropy values as event evolution power, and the stable fission of new event space is realized by the entropy value comparison of an increment information vector and an event critical space vector, so that the identification and tracking of a derivative / secondary event are realized. By the method, the entropy values of the increment information are taken as the power of the event evolution, so that the requirements of work such as tracking, pre-warning / predicting emergency events and random events can be effectively met; and meanwhile, the method is high in topicality, reliability and expandability, and the common phenomenon that the load of computational nodes and a network is heavy in a mass information processing activity is avoided.

The embodiment of the invention provides an analysis method and an analysis system based on an event evolution process of key words. The method comprises the steps of counting the quantity of search results within all time quanta, so as to obtain a sequence that the quantity of the search results changes along with the time quanta; performing peak detection on the sequence, so as to obtain at least one peak window; performing text analysis on the search result corresponding to the peak window, so as to obtain peak description; displaying the sequence that the quantity of the search results changes along with the time quanta, and displaying the peak description in a peak position. According to the analysis method and the analysis system of the embodiment of the invention, the sequence that the quantity of the search results changes along with the time quanta is counted, and the sequence that the quantity of the search results changes along with the time quanta and the peak description are displayed, so that the trend that the microblog information quantity changes along with time is shown, the evolution process of an event related to the key words can be shown by the trend that the microblog information quantity changes along with time, a user can know about main contents of microblog information without reading microblog contents in detail according to the peak description, and the information quantity displayed by the search results is increased.

The invention discloses a method for deducing an event evolutionary graph path. The method comprises the following steps: S1, presetting an event evolutionary relation template; S2, obtaining various types of source data from the data source according to an event detection algorithm; S3, analyzing the obtained source data; S4, preprocessing the analyzed source data, and performing event extraction to form a data network; S5, carrying out prediction in combination with the data network, and obtaining prediction information; S6, establishing an event evolutionary graph according to a preset event evolutionary relation template and the prediction information; and S7, summarizing the event evolutionary relation events to generate an event evolutionary event library. According to the method, the analyzed source data is preprocessed, events are extracted, the data network is formed, and the corresponding event evolutionary graph is established, so that the integrity and continuity of a generated event evolution process can be effectively improved, and the complexity of deducing an event evolutionary graph path is reduced.

The invention relates to an improved script learning method and device based on an event evolution diagram. The method comprises the following steps: constructing an abstract event evolution diagram by utilizing a specific event network formed by specific event chains; mining event evolution knowledge contained in the event evolution diagram to learn initial embedded representations of context events and candidate events; inputting the initial embedding representations of the context event and the candidate event into a bidirectional LSTM network to obtain updated embedding representations of the context event and the candidate event, including time sequence information of an event chain and event evolution knowledge contained in an event evolution diagram; and carrying out similarity calculation on the context events and the candidate events by utilizing the updated embedded representation to obtain a similarity score of each candidate event, probabilizing the similarity scores, and selecting the candidate event with the highest probability as a final predicted event. The method has high accuracy for script event prediction, and can be used in the fields of privacy stealing attack event prediction and the like.