306 results about "Hot topics" patented technology

A tabulating system and method analyzes content posted and / or queried by an online community. The content can be searched based on a search filter executed at defined intervals, and the system can also reach through to locate and extract content from other remote systems. Community postings and queries can be tabulated to determine “hot topics” of interest to the community, to enhance the appeal and stickiness of a website. Furthermore, subscribers can also formulate and define their own custom searches to be run on their behalf to identify the existence of particular content on the website.

The invention relates to a device and a method for identifying and evaluating an emergency hot topic. The device is provided with four component parts including a text acquisition unit, a text expression unit, a topic clustering unit and a topic evaluation unit. The device and the method are characterized in that only a title, introduction, relevant features and other information of a text of a news report are extracted and regarded as an effective sample set identified by the hot topic. Compared with the existing full text extraction, the experiment result shows that the result of the existing full text extraction is similar to the result of the partial text extraction, but the operation of the device and the method is greatly simplified. Compared with a classical model, an improved feature weight calculation model is good in execution efficiency and strong in adaptability of text representation capability. The model is used for evaluating the hot value of clustered topics, and the calculated hot topic accords with the expected effect and is adaptive to the features of the emergency news report. In a word, in the process of processing the text of the emergency news report, the device and the method have good performance in aspects of calculation complexity, result accuracy and timeliness.

The invention discloses a method for monitoring and displaying Internet hot spots, which comprises the following steps of: querying a microblog search engine inlet and an RSS reader to acquire recommended link information, and calculating rank values of the recommended links to determine hot links; monitoring and searching search hot words with the quickest engine rise, combining the hot words, searching associated news through the hot words, calculating the hot degree value of the associated news, and determining hot topics; and performing text similarity calculation on the headers and texts of the hot links and hot words of the hot topics and a search word list thereof, and combining the hot links with the hot topics to acquire Internet hot spot information. The technical scheme can quickly monitor the latest hot spots of the Internet, effectively establish the association among the hot key words, hot links, news, pictures, video and the like, and fully display the Internet hot spots.

A regional public opinion monitoring and decision-making auxiliary system based on big data comprises an information acquisition and storage module, a data pre-processing module, a big data public opinion analysis module, a public opinion monitoring, early warning and decision-making auxiliary module and a background management module, wherein the information acquisition and storage module is used for carrying out structuralized storage management on acquired public opinion source information to form a regional big data public opinion knowledge base which is updated in real time; the data pre-processing module is used for pre-processing data in the regional big data public opinion knowledge base to form a complete and ordered data set; the big data public opinion analysis module is used for carrying out public opinion analysis and tendency prediction on hot topics with appointed conditions and the like to obtain a public opinion analysis and tendency prediction result; the public opinion monitoring, early warning and decision-making auxiliary module is used for carrying out real-time monitoring and tracking, management and persuasion on customized public opinions dug and analyzed by sensitive word pairs in a pre-defined sensitive word bank, and announcing the customized public opinions to a decision maker in manners of in-station messages, short messages and mails; and the background management module is used for carrying out public opinion information classification management, user and authority management, keyword management, acquisition management, content management, special topic management and analysis report management.

The invention discloses a news public opinion monitoring system. The news public opinion monitoring system comprises a news information gathering module, a news data pre-processing module, a news public opinion analyzing module and a news public opinion result display module; the news data pre-processing module comprises a primary filtering sub-module, a text extracting sub-module, a word segmentation sub-module, a feature phrase filtering sub-module, a text emotion tendency analyzing sub-module, a picture analyzing sub-module and a public opinion popularity acquiring sub-module. A distributed cloud computing mode is used for the data pre-processed by the news data pre-processing module, various news public opinion monitoring algorithm sub-modules are used for acquiring the hot spots of news public opinions, and the hot spots of news public opinions are comprehensively judged, classified and evaluated to effectively and precisely monitor hot topics of the news public opinions.

The invention discloses a topic detecting device and a topic detecting method based on distributed multistage cluster. The topic detecting device mainly comprises a news acquiring module, a news classifying module, a topic detecting module, a topic integrating module and a topic displaying module. The topic detecting method is characterized by comprising the steps of A, acquiring news; B, classifying the newly acquired news; C, performing multistage cluster for various channels concurrently; and D, computing hotness of all topics, and screening hot topics of a total system and hot topics in each channel. By the topic detecting device and the topic detecting method, a sharp contradiction between a detecting effect and time cost in topic detection under the condition of quick updating of a large number of files in an internet environment can be solved.

The embodiment of the invention discloses a method and device for detecting network hot topics found based on a maximal clique. The method comprises the following steps of: acquiring data of a network news website, a forum, a blog and a microblog in a real time; carrying out word segmentation, word frequency statistics and other processing on the acquired data to find all hot point word pairs and construct a hot point word pair set; expressing each hot-point word by using a unique serial number; viewing the hot point word pair set as an undirected graph and excavating the undirected graph to obtain all maximal cliques; and transforming each maximal clique into a word combination for expressing one hot point topic. The invention also discloses a device for detecting the network hot topics. According to the embodiment of the invention, the hot point topics in the network can be accurately found in a real time, the detection speed and precision of the hot point topics are improved and higher practical value is obtained.

Provided are a system capable of providing a highlight of a real-time event using message streams of social media and a highlight service providing method using the same. The disclosed highlight providing system includes: a hot event session detection unit detecting a hot event session where a hot event occurs using message streams of social media; a keyword detection unit detecting keywords related with the hot event from the hot event session detected by the hot event session detection unit using a predetermined algorithm; a hot event generating unit generating the hot event using a semantic relation between the keywords detected by the keyword detection unit; and a highlight providing unit providing a highlight of the social media along with a description in a natural language based on the hot event generated by the hot event generating unit.

According to some embodiments, systems, apparatus, methods and computer program code are provided for receiving data from a plurality of remote data sources, the received data being associated with a plurality of search terms, analyzing the received data to identify at least a first trending search term, comparing the trending search term with a database of topical terms to determine whether the trending search term is relevant to a predetermined topic, querying a content database using the trending search term to identify a caption to be associated with the trending search term, and storing the trending search term and the caption in a database.

The invention discloses methods for labeling and searching advanced semantics of images based on network hot topics and a device. The method for labeling the advanced semantics of the images comprises the step of: searching images similar to the entity semantics of images to be labeled and accompanying texts by using an entity semantic work of the images to be labeled based on a search engine of text key words, then extracting topics from the accompanying texts, establishing association relationship among topics, among images, and between images and topics, based on the association relationship, classifying the images with similar topics and visual features into a type, and classifying similar topics corresponding to the images with the similar visual features into a type; and selecting image types which are the most similar to the images to be labeled in the visual features of the images, and taking the corresponding topics as hot topics. According to the invention, by means of the process, the advanced semantic labeling the images is realized, and in addition, the obtained advanced semantics can be used to accurately describe the images to be labeled through denoising.

The invention provides a microblog-oriented dynamic topic detecting and evolution tracking method and belongs to the technical field of intelligent information processing. The method includes the steps of 1, establishing a distributed crawler to acquire microblog data; 2, pre-processing the microblog data; 3, performing Chinese word segmentation to remove stop words, and acquiring a word set VOC; 4, subjecting the microblog data to LDA (latent Dirichlet allocation) clustering in each time interval so as to extract latent topics; 5, screening out microblog hot topics in each time interval; 6, subjecting the hot topics of a global time to hierarchical clustering to acquire inter-topic aggregation and differentiation relations; 7, visualizing a topic evolution process according to the inter-topic aggregation and differentiation relations. The method has the advantages such that topic word distribution of an event in different times and a fine-grained topic of a same topic in different times are mined under low time complexity, efficiency is high, and robustness is high; the method has greater practical value.

The invention provides a method and a system for tracking and detecting information based on behavior patterns of a network structural user. The method comprises the following steps: firstly, obtaining all target information in Internet forums, and further extracting the information to obtain the information such as titles, contents, user names, publication time of related posts; secondly reconstructing the network structure of the Internet forums to the extracted information by a network building arithmetic, and establishing an integral graph and calculating the correlative character of the graph; and thirdly, carrying out correlative calculations by using a fitness estimation arithmetic, an activity estimation arithmetic and a heat degree estimation arithmetic to obtain hot topics in the Internet forums. The method considers the network structure of the Internet forums and the importance of users in the Internet forums, so the method can judge sensibility and controversial hot topics in the Internet forums quickly, thus reducing the calculation amount.

The invention discloses a time window based LDA microblog topic trend detection method and apparatus. The method comprises: extracting a topic word from a word set by utilizing an LDA model in each time window, and obtaining global topics; performing similarity computing on the global topics, and performing K-means clustering to obtain hot topics conforming to public opinion analysis; extracting feature words of each hot topic in each time window in sequence in combination with the hot topic through the LDA topic model; and in combination with results of the feature words, computing a popular value of the hot topic in each time window, and drawing a trend graph of the hot topic. The apparatus comprises a first acquisition module, a second acquisition module, an extraction module and a drawing module. According to the detection method and apparatus, the precision of microblog topic detection is improved, so that a trend index is more expressive, and a more accurate basis is provided for analyzing a hot topic trend.

The invention discloses a microblog hot topic analyzing method. The method comprises the following steps that a microblog collection module obtains microblog data in the mode of combination of a web spider and a microblog third-party api technology according to a collection strategy; key words and sensitive words are called from a word bank through a word segmentation technology, and key words and sensitive words are analyzed out from microblog text data; the microblog webpage text data are filtered according to the analyzed key words, the analyzed sensitive words and emotional tendency words; a hot topic module marks the content involved between the symbols of # and # and between the symbols of [] as a topic through a clustering analysis technology, so that the number of microblog comments is counted; a hot people module analyzes the number of microblog fans and the number of the comments through the clustering analysis technology; a microblog early warning module analyzes out microblog information related to the key words and the sensitive words from the network microblog; an analyzing and counting module automatically generates a brief report through relevant data analyzed out from the system. The accuracy of topic analysis is improved, and detection efficiency is improved.

Cardiac computed tomography (CT) has been a hot topic for years because of the clinical importance of cardiac diseases and the rapid evolution of CT systems. In this application, we disclose a novel strategy for controlled cardiac CT (CCCT) that may effectively reduce image artifacts due to cardiac and respiratory motions and reduce the scan time. Our approach is radically different from existing ones and is based on controlling the x-ray source rotation velocity and powering status in reference to the cardiac motion. By such a control-based intervention the data acquisition process can be optimized for cardiac CT in the cases of periodic and quasi-periodic cardiac motions. Specifically, we present the corresponding coordination / control schemes for either exact or approximate matches between the ideal and actual source positions.

The invention relates to a network-based system for analyzing opinion information in a discrete text, belonging to the field of network information safety. The system comprises the following modules: a discrete text information acquisition module which acquires network information in a preset analysis cycle, a discrete text information tracking and restoring module which restores ellipsis and remote anaphora in the original content to obtain a text which contains a relatively complete text structure and semantic information, a semantic information mining and characteristic extracting module which realizes semantic information mining and characteristic extracting on text information by utilizing a latent semantic indexing technology, an opinion information clustering module which realizes information clustering by combining a niche genetic algorithm with a K-Means method, a hot opinion event discovery module which mines the hot opinion in the obtained topic and event, and a background information processing and data supporting center which analyzes data and provides a repertoire specially for a network, new words in the network, the existing class information and the existing hot topics. By applying the invention, the problem that information analysis is influenced as the text structure of the existing network opinion information is incomplete, ellipsis and remote anaphora are more and the new works in the network are more is solved, and the accuracy for discovery of the opinion and hot event is improved by adopting a high-efficiency clustering method.

The invention discloses a method and device for automatic detection of microblog hot topics, relating to the technical field of internet. According to the invention, key words are extracted from a to-be-detected microblog text, then key terms are acquired, next, the key terms are clustered, so that candidate key word clusters are obtained; finally, the concern degree of the topic corresponding to each candidate key word cluster is computed, and the hot topics are selected according to the concern degrees. Through adoption of the method and device, hot topic detection becomes simple and the hot topics can be detected effectively.

The invention discloses a network consensus prediction method and a network consensus prediction system. The method comprises the following steps of: preprocessing network consensus information to acquire a time sequence needed for prediction; establishing a corresponding prediction model according to the time sequence acquired by preprocessing; and predicting a development trend of network consensus based on the prediction model. By the method and the system, the development trend of each hot topic on the network during a short period in the future can be predicted within the shortest time, so that topics which promote social stability are continuously kept by a guide method of the consensus; moreover, topics which destroy social harmony are led to extinction gradually.

The invention relates to the technical field of social networks, in particular to a micro-blog hot word and hot topic mining system and method. The method includes the following steps that content data released in a micro-blog are preprocessed to acquire a candidate hot word sequence; according to the frequency of occurrence and suddenness of candidate hot words in a candidate hot word set at the current moment and in a given historical time window, the vitality of each candidate hot word is worked out, and a hot word set is formed by screening the candidate hot words; according to the hot word set formed by screening the candidate hot words, hot word correlation is worked out, and a hot word co-occurrence network is constructed; according to the hot word co-occurrence network, the hot word set is partitioned through the hot word clustering algorithm based on multi-label propagation to acquire a hot topic set. By means of the micro-blog hot word and hot topic mining system and method, efficient micro-blog hot word and hot topic mining is achieved, and mining precision and processing efficiency are improved.

The invention provides a topic detection method and device based on big data. By means of the topic detection method and device, accuracy and timeliness of detection effects can be guaranteed at the same time under the condition that a large amount of web page text is updated quickly in the internet environment. The method includes the following steps: extracting hot web pages according to user network behavior data; collecting contents of the hot web pages; extracting and acquiring web page feature vectors of the hot web pages according to the contents of the hot web pages; clustering the hot web pages according to the web page feature vectors of the hot web pages to acquire corresponding potential hot topic classes; carrying out incremental clustering on newly-added web pages with the potential hot topic classes as seed classes, wherein the newly-added web pages comprise on-line web pages; and judging whether the potential hot topic classes after the incremental clustering are hot topic classes through analyzing corresponding user attention degree parameters of the potential hot topic classes.

The invention provides a hot topic recommendation method and device. The method includes the steps that the behavior characteristics of users to objects are extracted from user historical behavior data; the attention degrees of the users to the objects are determined according to the behavior characteristics of the users to the objects; hot topics associated with the objects with the attention degrees meeting preset conditions are determined; a hot topic recommendation set recommended to the users is formed according to the determined hot topics. In other words, the hot topics which the users are possibly interested in are determined based on the potential interest of the users in the objects and the association relation between the objects and the hot topics, and then the hot topics are recommended to the users, so that the recommendation way has higher pertinence and individuation.

The invention discloses a device and method used for mining microblog hot topics. The method comprises the following steps of: acquiring microblog information through an open interface; performing segmentation on acquired microblog content, and extracting hot key terms; performing statistics on microblog number related to the hot key terms, and performing weighted calculation according to the microblog number and the microblog parameter of a corresponding microblog to obtain hot values of the hot key terms; and sorting the hot values of the hot key terms to obtain the ranking of the microblog hot topics. The method also comprises the following steps of acquiring the microblog content related to every microblog hot topic in the ranking of the microblog hot topics after the ranking of the microblog hot topics is obtained; and displaying the microblog content related to the corresponding microblog hot topic according to a user request to a user or actively displaying the microblog content related to the corresponding microblog hot topic to the user. By means of the technical scheme disclosed by the invention, the microblog hot topics can be accurately judged, so that objective facts of Internet public opinions can be further reflected by mining results.

The invention discloses an automatic hot topic mining system based on internet corpora. The system is composed of two routes: 1) crawling hot words of existing hot word statistics sites, and generating a series of hot topics through the steps of clustering, entity extraction and key word mining; and 2) extracting n-gram from massive news documents, mining high-frequency hot words from the massive news documents by calculating mutual information and conditional entropy values of the n-gram, and recognizing new topics by using an event detection method based on a time sequence. By adopting the system, not only can current hot events be mined in real time, but also can relevant keywords and named entities of a hot topic be mined when the topic is generated.

The invention discloses a method for microblog hot event online detection based on emotion analysis. According to the method for microblog hot event online detection based on emotion analysis, emotion extraction is conducted on online microblog texts according to emotion analysis, the bursting state of emotions and emotion texts is detected according to the improved Kleinberg algorithm, hot topics are extracted according to an affinity propagation clustering algorithm in the bursting period, so that only a small part of texts with a large amount of effective information participate in event extraction, the data volume is reduced, meanwhile a large amount of data noise is filtered out, and therefore the purpose that online real-time detection of the microblog hot events is achieved.

The invention discloses a subject-oriented customized new information extraction system which comprises a news collecting subsystem, a text processing subsystem and a human-computer interaction subsystem, wherein the news collecting subsystem completes the functions of searching related news about related subjects customized by a user and extracting news texts; the text processing subsystem divides the texts into different categories, detects and tracks topics in the content of the texts on that basis, automatically generates abstracts and establishes corresponding indexes; and the human-computer interaction subsystem firstly analyzes the topics, calculates the hot degree of the topics, presents the hot topics in the groups of subjects of the topics for the user in the sequence of hot degree and simultaneously provides topic retrieval, and the user can artificially screen the obtained content and store intelligence obtained by artificially extracting the screened information into an intelligence library. With the system, news on the internet can be comprehensively collected in time and can be automatically detected, classified and tracked, and intelligence required by the user can be extracted from immense network news by exerting the cognitive ability of the user on intelligence.

The invention discloses a network burst hotspot event detection method based on a topic model, which comprises the following steps of: 1, firstly, carrying out participle treatment on a file data set to obtain a word list, a file word relation matrix, a word file distribution matrix and a word date distribution matrix; 2, screening the data set according to relevant words in an emerging process of network hotspot events and burst characteristics of a file; 3, obtaining characteristic words and characteristic texts of the burst hotspot events through topic modeling; and 4, figuring out attention date distribution of the hotspot events. Compared with the prior art, the invention has the advantages that the topic modeling is carried out by using the topic model, thus a topic event can be more accurately described; and a burst characteristic computing method of words is introduced and then the data set is screened, thus time-unrelated topics are removed through filtering, and an actual burst hotspot event is obtained.

The invention discloses a method for performing emotional tendency classification to microblog by using emoticons. The method comprises the following steps: building a neutral emotion set, a passive emotion set and a positive emotion set; building a neutral emotion Bayes classifier by using the neutral emotion set, the passive emotion set and the positive emotion set; building a polar emotion Bayes emotion classifier by using the passive emotion set and the positive emotion set; performing emotion classification to the microblog by using the neutral emotion Bayes classifier and the polar emotion Bayes classifier. According to the method for performing emotional tendency classification to microblog by using emoticons, two sections of classification is built, namely, building the neutral emotion classifier to remove the microblog with neutral emotion, and building the polar emotion classifier to divide the microblog with the polar emotion into the passive emotion and the positive emotion; the classifier is rapid in classifying speed, small in occupied space and robust; attitude of people to current hot topics or events and emotion of net citizens can be accurately understood through the microblog, so that the method for performing emotional tendency classification to microblog by using emoticons has important help for social scientific research and survey.

The invention discloses a method for mining the orientation of Web themes and supporting decisions. The method includes steps of S1, extracting and storing network information, acquiring information on the internet via a network mining technology, and storing results in a database and a local file system; S2, detecting and tracking viewpoint themes of the information, detecting and identifying interested viewpoint themes with complete semantic information by the aid of thematic comment data and keeping tracking and following the viewpoint themes; and S3, identifying the emotion orientation of the viewpoint themes, classifying the emotion orientation of hot topics of an enterprise, and mining the emotion orientation of the view themes. The method has the advantages that related business information is acquired from the internet, so that the tendency of the orientation of the themes related to the enterprise can be quickly and effectively mined from the massive network information, real-time business intelligence can be realized, and decision support service can be effectively provided for the enterprise.

The invention discloses a microblog topic detection and hotspot evaluation method based on semantic expansion, belongs to the field of text information processing, and particularly relates to microblog noisy data filtering and a microblog topic detection and topic hotspot evaluation method and system based on semantic expansion. The method comprises the steps of firstly giving out a microblog noisy data filtering method for filtering microblogs with low information content, then supplementing effective semantic information in microblog comments into microblog semanteme so as to improve the detection effect of microblog topics, finally carrying out microblog topic hotspot evaluation, and thus obtaining hot topics.

The invention discloses a microblog hot topic detection method based on multi-information fusion. Firstly, influences of a blogger is calculated according to social relations of a microblog promulgator, and a sum of weights of a feature word in all microblogs in a given time period is further calculated based on influence information of the blogger and frequency information of the feature word; then a sudden feature word is detected according to information of the sum of the weight of the feature word along with time changes, microblog data are expanded by introducing Web news linguistic data to calculate an incidence relation valve between sudden features, and an association graph of the sudden feature word can be further constructed; finally, the association graph of the sudden feature word is divided, each strong connected subgraph indicates a topic, and accordingly detection on a microblog hot topic can be achieved. The microblog hot topic detection method comprehensively uses microblog feature word information, blogger social relation information and relative Web news document information to detect the microblog hot topic, and improves detection efficiency of the microblog hot topic.