39 results about "Web news" patented technology

The invention provides a tool for quantitatively analyzing internet news influence based on information retrieval and a method thereof. The tool comprises a webpage content duplication determine module, a relevant information extracting module, a news reprint rate calculating module, a newsletter source website influence determine module, a news recovery rate calculating module and a news influence calculating module, wherein, the webpage content duplication determine module determines whether a webpage is an approximate webpage or not; the relevant information extracting module extracts relevant information in the webpage; the news reprint rate calculating module reprints a website technorati authority value; a news source website and the news reprint rate are found out; the newsletter source website influence determine module determines the popularity index of the news source website to acquire a newsletter source website influence factor; the news response rate calculating module determines a network news recovery rate; and the news influence calculating module calculates the news influence value. The method comprises the following steps: determining that whether the webpage is the approximate webpage or not; extracting news webpage reprint information and recovery information; calculating the news reprint rate; calculating the recovery rate of the news; calculating the technorati authority of the news source website; calculating the influence factor of the news source website; and calculating the news influence. The quantitative calculating result is combined with qualitative analysis of a user to help the user determine the news influence.

The invention discloses a negative news recognition method based on emotion calculation and a multi-head attention mechanism, relates to the technical field of network public opinion monitoring, and solves the technical problem of how to solve the problem that objective negative news is difficult to identify, and the negative news recognition method comprises the following specific steps: (1) collecting and preprocessing network news text data; (2) establishing and expanding a negative emotion seed word bank and calculating the susceptibility; (3) performing vectorization representation, and determining the input of a discrimination model; (4) establishing a negative news discrimination model; and (5) carrying out negative news recognition. According to the method, the problem that the negative news is difficult to identify is effectively solved, and a good effect is achieved in the aspects of recognition accuracy and effectiveness of the negative news text.

The invention relates to an online Web news content extraction method. The method comprises the following steps: obtaining a DOM tree of an extracted Web news webpage; traversing the DOM tree to construct a text node information sequence and a label path information sequence; calculating a label path characteristic value sequence; fusing the label path characteristic value sequence by a weighted DS evidence theory to obtain a label path comprehensive characteristic value sequence; constructing a text node comprehensive characteristic value sequence; and extracting the text content of the Web news webpage according to the text node comprehensive characteristic value sequence. The invention furthermore discloses an online Web news content extraction system which consists of an analysis module, a calculation module, a fusion module and an extraction module. The label path characteristics are not based on templates of the webpages and have diversity, and the whole extraction process only comprises simple mathematical elements, so that massive heterogeneous Web news webpages can be effectively extracted online.

The invention discloses an automatic prediction method of network news expression distribution. The network news expression distribution indicates that multiple network users vote different news expressions to form the news expression distribution after browsing a piece of network news. The invention comprises the following steps: collecting network news data comprising network news samples and news expression user vote data of each sample; utilizing the collected data to carry out keyword selection and extracting the characteristics of each new sample; utilizing a probability label propagation algorithm to modify the distribution of the vote data; and automatically predicting the news expression distribution of a new network news sample by utilizing a machine learning algorithm based on instances. The automatic prediction method of the invention can be applied to predict the news expression analysis of network news and the news expression distribution of a new network news sample.

The invention discloses a text generation method and device based on dynamic weights and a storage medium, and the method comprises the steps of constructing a hot word library which stores hot search words obtained every a first preset time period and a hot search weight of each hot search word, and the hot search weight of each hot search word is generated according to the frequency parameter of each hot search word and the construction time of each hot search word; receiving any input text; extracting a plurality of subject terms from any text; matching the subject terms with a hot word library to obtain a hot search weight of each subject term; and generating an updated text according to the subject term containing the hot search weight. According to the dynamically weighted news event multi-topic automatic generation method, the corresponding weight is dynamically given to the hot word according to the hot word constructed by incremental automatic search in combination with the frequency information of the word and the hot search time information, and the invention is used for processing quickly updated real-time network news data.

The invention relates to a news-oriented Chinese food safety news event information automatic extraction method comprising the following steps: S1, collecting network news to construct a food news corpus; arranging the domestic geographic information knowledge base and constructing the geographic information knowledge base; collecting the food category information from the network and constructingthe food category knowledge base; S2, performing text classifying of the news corpus of the food news corpus by using the text classification model so as to obtain the food safety news corpus; S3 firstly extracting the event occurrence time in the food safety news corpus; secondly, extracting the event occurrence place in the food safety news corpus by utilizing the geographic information knowledge base; finally, extracting the food name and the category information involved in the food safety news corpus by utilizing the food category knowledge base; S4, counting the extracted time, place and food information; and S5, displaying the time, place and food statistical information by using the visualization technology. The information of three dimensions of the time, the place and the food category of the food safety event can be accurately extracted from the network news, statistics on the information can be performed and finally the statistical result can be visually displayed.

The invention discloses a method and system for automatically cleaning network news data based on webpage label distribution characteristics, and the method comprises the steps of crawling the networknews data through an offline crawler system, namely carrying out tree node analysis on the crawled offline news data, and extracting the attribute information, such as label name, attribute, text, link, etc., in a node; predicting the information of other node blocks through a current node by adopting an idea based on n-gram2vec, obtaining the word embedding information of the label through training, constructing an intelligent model discrimination system based on the pre-trained word embedding information, and determining the leaving of tiled nodes, namely dividing an intelligent model intoa text discrimination model and a picture discrimination model according to the type of an article label, training the two types of models by adopting different feature engineering, finally predicting, and combining the results of the two types of models according to the previous node sequence.

The invention relates to a multi-scale visualization method for news, which is used for realizing map-oriented network news multi-scale expression and comprises the following steps: 1) crawling different news events within a certain time period, acquiring news text contents, titles and publishing time, and storing news sources; 2) geocoding the crawled news to obtain a news place and corresponding latitude and longitude coordinates; 3) performing scale division on the news according to place names involved in the news; 4) performing span calculation on the news according to the longitude and latitude of the related place in the news; and 5) constructing a map visualization model according to the scale and span of the news, thereby displaying the news with the corresponding scale and span according to different map scaling scales. According to the method, the scale of the news and the scale of the map are combined, multi-scale presentation of the news data is achieved, the browsing dimension of news information is increased, news browsing and reading are more convenient and efficient, and the news multi-scale visualization technology under the space-time dimension is achieved.