379 results about "Information propagation" patented technology

A method for brain tumor segmentation in multi-parametric 3D magnetic resonance (MR) images, comprising: determining, for each voxel in the multi-parametric 3D MR image sequence, a probability that the voxel is part of brain tumor; extracting multi-scale structure information of the image; generating multi-scale tumor probability map based on initial tumor probability at voxel level and multi-scale structure information; determining salient tumor region based on multi-scale tumor probability map; obtaining robust initial tumor and non-tumor label based on tumor probability map at voxel level and salient tumor region; and generating a segmented brain tumor image using graph based label information propagation. The present invention is capable of achieving statistical reliable, spatially compact, and robust tumor label initialization, which is helpful to the accurate and reliable tumor segmentation. And the label information propagation framework could partially alleviate the performance degradation caused by image inconsistency between images to be segmented and training images.

Mechanisms have been developed for synchronizing information, e.g., password or other access credential information, amongst replicated directory spaces or repositories. In some exemplary realizations, directory spaces are embodied as directory servers, services or similar components of computer operating systems, including LDAP, UDDI, Active Directory or other standardized or proprietary directory environments. In one embodiment in accordance with the present invention, a method includes invalidating an entry of at least one replica store. The invalidation of the entry of the replica store triggers information synchronization of a corresponding invalidated entry of a master store to a corresponding entry of an authoritative store on a next attempt to authenticate against the invalidated entry of the replica store. The method may include propagating information of the synchronized master store entry to at least one other replica store.

One or more techniques and/or systems are disclosed for predicting propagation of a message on a social network. A predictive model is trained to determine a probability of propagation of information on the social network using both positive and negative information propagation feedback, which may be collected while monitoring the social network over a desired period of time for information propagation. A particular message can be input to the predictive model, which can determine a probability of propagation of the message on the social network, such as how many connections may receive at least a portion of the message and/or a likelihood of at least a portion of the message reaching respective connections in the social network.

Modifications to the spanning tree algorithm allow bad news to propagate quickly by providing that protocol entities on bridges process inferior information sent by the designated bridge for each LAN. In addition, bridges use per port hello timers to stimulate information propagation, setting it to suit local link characteristics. No changes to the format of bridge protocol data units (BPDUs) as specified in the IEEE Standard 802.1D are required, and the algorithm for computing the topology of the network remains unchanged. Techniques have been adopted for expiring information and recomputing the spanning tree upon detection of link failure, upon receipt of a message having a message age greater than its accompanying maximum age, or if the port hello time algorithm detects a loss of link. Rules for propagating information are provided allowing rapid propagation of changes. Finally, techniques for burning out information in a configuration message are adopted.

The invention discloses a method for measuring the influence of users on the topic hierarchy for MicroBlog. The method comprises the steps of 1, calculating the similarity of MicroBlog texts; 2, obtaining a topic set according to the dynamic clustering algorithm correlation; 3, measuring the influence of the users on the topic hierarchy according to standards: calculating the information propagation influence of the users, calculating the MicroBlog value influence of the users and calculating the activeness influence of the users; 4, establishing a user influence measurement model. According to the method, the effects of the three factors of information propagation, user activeness and user MicroBlog value on the influence of the users are comprehensively considered, the user influence measurement model is established, the influence of the users on the topic hierarchy can be measured more accurately through the model, then the users playing a key role in the topic propagation can be found, and public opinion monitoring and tracing in the MicroBlog network have the guaranteeing and monitoring effects.

The invention provides a method for predicting social network information popularity on the basis of user characteristics. The method includes the steps of obtaining user data and information data in a social network, extracting part of user attribute characteristics and user behavior characteristics from the user data, classifying the user data according to the user attribute characteristics and the user behavior characteristics, obtaining user broadcasting characteristics corresponding to the information data according to the information data and the classification of a user, obtaining a social network information popularity prediction model according to the user broadcasting characteristics, and predicting the information popularity through the prediction model. The invention provides a system for predicting the social network information popularity on the basis of user characteristics. The system comprises an obtaining module, a characteristic obtaining module, a classification module, a processing module, a prediction model module and a prediction model. Through the combination with the features of user behavior characteristics, information propagation of the social network is more accurately predicted, and the problems that hot spot finding lags and the real-time performance of information pushing and online public opinion monitoring can be hardly ensured are solved.

A system for propagating information among wireless communication devices in an efficient manner. More specifically, the invention involves regulating the behavior of a wireless communication device (WCD) between a primarily passive mode where client or slave availability is maximized and a primarily active mode where information propagation or master behavior is maximized. The regulation of the WCD is controlled based on the environment surrounding the WCD, including the devices in effective transmission range of the device, and the current condition of the WCD.

A method for brain tumor segmentation in multi-parametric 3D MR images. The method comprises: pre-processing an input multi-parametric 3D MR image; classifying each voxel in the pre-processed multi-parametric 3D MR image, determining the probability that the voxel is part of a brain tumor, and obtaining an initial label information for the image segmentation based on the classification probability; constructing a graph based representation for the pre-processed image to be segmented; and generating the segmented brain tumor image using the initial label information and graph based representation. This method tries to exploit the local and global consistency of the image to be segmented for the tumor segmentation and can alleviate partially the performance degradation caused by the inter-subject image variability and insufficient statistical information from training.

An information propagation analyzing system and method of information propagation analysis. Information propagation analyzing apparatus (3) analyzes the relationship among multiple message informations exchanged within a community space monitored by web server (24) and creates information on inter-message chain structure. The information propagation analyzing apparatus (3) computes the message propagation capacity for each of the message informations on the basis of the inter-message chain structure. The information propagation analyzing apparatus (3) computes the degree of information propagation between members belonging to the community on the basis of the message propagation capacity. The information propagation analyzing apparatus (3) constructs a social network consisting of a group wherein information is likely to easily propagate on the basis of the degree of information propagation between members.

Propagating information in a computer network, in one aspect, may include detecting an online action performed by a user on a content presented on a computer. The content may be annotated with an identifier. A semantic graph may be searched for a semantic node representing the identifier. The semantic graph may be searched for one or more other semantic nodes representing one or more other identifiers that meet a semantic similarity threshold based on weighted distances between the semantic node and the one or more other semantic nodes. One or more other users represented in a social graph may be determined that have interest in one or more topics represented by the identifier and the one or more other identifiers. The online action on the content may be propagated to the one or more other users.

The invention discloses a method for quickly and accurately identifying key blog collections in blog information dissemination, the steps of which are: 1) collecting and determining the attention relationship and link relationship between blogs in units of blogs; 2) taking blogs as a unit Nodes build a blog network graph, and the edges of the graph are the associations between blogs; 3) Determine the weight of associations (directed edges) between blogs according to the information dissemination model; 4) Calculate the influence of each blog on other blogs based on the blog network graph Expected value; 5) Identify the set of key nodes with the greatest influence on information dissemination in the blog network graph. The invention combines the information dissemination model, applies the relationship between blogs, and quickly identifies key blog collections in blog information dissemination by calculating information dissemination expectations, so as to facilitate the supervision of blog information.

The invention provides a modeling method of a dynamic social network information propagation model. The modeling method of the dynamic social network information propagation model is characterized in that a network element dynamicity and a network structure dynamicity are introduced based on a static society network evolution game model; two kinds of the dynamicity are combined with a evolution game method for performing cooperative evolution game, thereby obtaining a final evolution stable state in information propagation and forming a dynamic social network cooperative evolution model. According to the modeling method, a special background in information propagation is combined. The modeling method is more similar with reality in social network evolution. Furthermore the network element dynamicity and the network structure dynamicity are combined so that the model is more reasonable. The modeling method has advantages of simple principle, clear flow and easy realization. The modeling method improves predication accuracy in network information propagation. Furthermore the modeling method supplies an effective model support in fields of public sentiment controlling, network group event predicating, enterprise advertisement input product propaganda strategy, etc.

The invention belongs to the research category of information propagation influence on a social network in a complex network research system, relates to a detection method for a key propagation path and a central node on a microblog platform and solves the detection problem of the central node on microblog advertising communication flow on the microblog platform. According to the detection method, the abstract problem of detection of the central node is tightly combined with the problem of the shortest propagation path in a complex network, and a detection model of the shortest propagation path of the advertising communication flow on the Sina microblog is established, so that the problem of detection of the central node on a microblog advertising propagation path, namely the detection problem of an advertising typhoon eye, is solved.

The invention request to protect an information propagation prediction model based on the chaotic theory, and belongs to the information propagation analysis field; the model is formed by the flowing steps: obtaining true data sources from social networks, building a user-static multidimensional forwarding factor attribute mechanism, predicting user dynamic behavior characteristics, and building a hot topic propagation model. The following steps are listed: firstly, obtaining related data, and obtaining a data set; secondarily, extracting various behavior characteristics affecting the user from the user, information and user relation angles, and quantifying the information propagation probability; then, using the chaotic theory to predict user dynamic behaviors; finally, combining information diffusion and infectious disease propagating similar propagation mechanisms on the basis of a conventional infectious disease SIR model, fully considering the dynamic behavior characteristics, and improving so as to obtain the information propagation model based on the chaotic theory and user behaviors. The method and model can effectively represent the information propagation dynamic trends in the social networks, thus finding the important influence factors in information propagation.

The invention relates to the technical field of industrial surface defect detection, and provides a plate strip steel surface defect detection method based on a significance label information propagation model. The method comprises the following steps of firstly, acquiring a plate strip steel surface image I; then, extracting a bounding box from the image I, and executing a bounding box selectionstrategy; then, performing super-pixel segmentation on the image I, and extracting a feature vector from each super-pixel; then, constructing a significance label information propagation model, constructing a training set based on a multi-example learning framework to train a classification model based on a KISVM, classifying a test set by using the trained model to obtain a category label matrix,calculating a smooth constraint item and a high-level prior constraint item, and optimizing and solving a diffusion function; and finally, calculating a single-scale saliency map under multiple scales, and obtaining a final defect saliency map through multi-scale fusion. The surface defects of the strip steel can be efficiently, accurately and adaptively detected, a complete defect target can beuniformly highlighted, and a non-significant background area can be effectively inhibited.

The invention discloses a social network-oriented multi-information and multi-dimensional network information propagation model and method, and belongs to the field of social network analysis. The method comprises the following steps of: firstly, obtaining social network data and preprocessing the data; secondly, extracting user information, user behaviors and user relationships from real data, and constructing a multi-dimensional network space by using a cosine similarity method; thirdly, establishing a model, importing influence factors on the basis of traditional epidemic models through using an epidemic model mechanism for reference, so as to express interaction relationships and intensities between different pieces of information, and then constructing a multi-information and multi-dimensional space network-based information propagation model; and finally, carrying out simulation analysis, constructing a kinetic equation from a micro perspective and a macro perspective so as to analyze a common evolution trend of two messages. The model and method more accord with real scenes of information propagation and are more beneficial for research of information propagation processes.

The invention provides an advertisement publishing method and relates to the information propagation field. By using current poster publishing means, a publicity effect is poor. By using the method of the invention, the above problem can be solved. The method comprises the following steps that: NFC equipment detects a hand-held terminal in a signal coverage scope; when the hand-held terminal which is newly entered into the signal coverage scope is detected, the NFC equipment sends advertisement poster data to the hand-held terminal. A technical scheme provided in the invention is suitable for fixed point poster advertisement publishing and various kinds of high-efficient advertisement publishing modes are realized.

The invention discloses a location-based social contact data information maximizing method. According to the method, the social contact relations of a social network and the historical check-in data of each user are utilized; the degree of influence of the probability of user' willingness to share and the distances of the users on the behaviors of the users are mainly considered; the propagation process of information in the online social network is modeled; a method for selecting K seed nodes is provided; and the seed nodes and users influenced by the seed nodes influence the friends of the seed nodes and the users through friendship in the online social network, so that information propagation can be performed, and therefore, the number of influenced people can be maximum, namely, the maximization of information (target locations) can be realized.

The invention belongs to the field of data mining of a semantic social network of the source tracing category and particularly relates to a micro blog topic source tracing method based on the topic influence. The micro blog topic source tracing method based on the topic influence comprises the steps that according to a latent semantic query expansion method of the field of information retrieval, semantic expansion is conducted on an input topic word group tp, and first k topics relevant to the given topic are obtained; a user relation and the information propagation law in the micro blog network are determined, and the topic influence TIN is determined; according to an influence computational formula, the influence of the topic is worked out with one hour as one time step, the variation trend, generated as time passes by, of the influence of the topic is obtained, the intensity of the influence gradually increases in the initial stage of the topic and then increases sharply, finally, the intensity of the influence reaches the stable state, and in other words, the topic becomes a hot spot; a topic source tracing recursion formula is deduced, the topic source tracing recursion ending condition is determined, and the source triggering the top is output. By the adoption of the micro blog topic source tracing method based on the topic influence, the topic source tracing recursion ending condition is more accurate, and topic tracing is more accurate and more effective.