139 results about "Incremental computing" patented technology

The invention relates to the field of a social network and is applied to a network system with social elements. The invention discloses a method and a system for calculating user influence in a social network, and in the method, the behaviors of users are analyzed so that a model of the behavior of influence spread among users is established and the mold is used for identifying the most influential people in the social network. The system records user access logs in real time. The method comprises the following steps that: (1) an influence behavior extracting module filters the interactive behaviors in the logs; (2) an influence spread calculating module determines the influence of the current behavior spread according to the type and the actor of the behavior and the emotion tendentiousness analysis of the relative content; (3) an influence updating module mergers the data generated through the increment; (4) a user ranking module incrementally calculates the most influential people; and (5) a service module appoints a target user range and sequences the target users according to the influence. The method and the system can dynamically reflect the change condition of the user influence according to the interactive behaviors of the users in the social network.

A method and a system implementing web-based incremental computing. A webpage updates when a data value relevant to displayed information is altered and updates only those affected elements. A watch system monitors relevant data values and in conjunction with a dependency tree, may execute functions to alter only altered elements of a webpage. A framework to automatically track data dependencies and propagate data changes is disclosed.

A method is provided to update information in a computer system comprising providing a reactive value hierarchy structure in a non-transitory computer readable storage device; in response to a change in a reactive value corresponding to a node in the hierarchy, marking nodes within the hierarchy that share as dirty a path with a node corresponding to a changed reactive value; traversing down through the hierarchy to a level where a reactive value is located that is either dirty or clean; if the reactive value is dirty, traversing back up to a dependent node in the hierarchy and compute a new reactive value and repeating the traversing down step; if the reactive value is clean, traversing back up to a dependent node and repeating the traversing down step; and producing at least one side-effect in the computer system in response to a compute of a new reactive value.

Systems and methods for instance counting and for the identification of a temporal pattern in an event sequence. The system addresses the use of “earliest-first” and “no-reuse” policies as criteria for the correctness of counting. The system also achieves higher performance than conventional methods by utilizing incremental computation.

Systems and methods for data processing using incremental algorithms. Embodiments of the invention decompose complex or monolithic data processing problems into one or more incremental computations called flows. These flows may be distributed across a networked cluster of commodity computers, facilitating the easy scaling of the system and robust recovery functionality. Once a request is submitted to the system, its solution may be maintained from that point in time forward, such that whenever changes are made to a problem's data the solution is efficiently recomputed.

A treatment planning method and system for optimizing a treatment plan used to irradiate a treatment volume including a target volume, such as a tumor, is disclosed. According to the method, two dose calculation algorithms are used to develop the optimized treatment plan. A first dose calculation algorithm is used to obtain substantially complete dose calculations and a second, incremental, dose calculation algorithm is used to make more limited calculations. The incremental calculations may be performed, for example, with less precision, less accuracy or less scope (e.g., focused on a specific subvolume within the treatment volume) in order to reduce the time required to achieve an optimized plan. Each of the dose calculation algorithms may be iterated a plurality of times, and different cutoff criteria can be used to limit the number of iterations in a given pass. A treatment planning system of the invention uses software for implementing the complete and incremental dose calculation algorithms. The method and system are especially useful for IMRT and arc therapy where treatment plan optimization is particularly challenging.

The present invention relates to communication field, wherein an embodiment of the invention discloses an ECMP path soft recovery method in a MPLS-TP packet transfer network. The embodiment of the invention comprises the following steps: realizing functions of congestion discovering, congestion positioning, etc. by the expanded OAM information; transmitting TDM grouping dynamic clock by MPLS-TP for adjusting operation; path cracking of the bypass heavy routing; when congestion occurs, firstly adjusting TDM service data grouping length through a source end for improving the delay characteristic; adopting a local service for shunting to the service with overhigh speed for steering clear of the congestion routing; if local link resource is insufficient, informing the source end for adjusting the bandwidth allocation, allocating higher bandwidth resource on the other N-1 paths; if no enough resources can be allocated or the allocated resources are not adjusted under the principle of simplifying the operation, informing the routing module by the source end, and completing the calculation of the other routing through the mode of incremental computation according to the bandwidth request amount. The method of the invention reduces the time for recovering network congestion. The network flexibility can be enhanced through the mode of self-adapting grouping variable-length transmission, and the using efficiency of the protected resource is increased. The quick performance recovery of the service is realized through the mode of bypass heavy routing cracking. The quick combining operation at the branching point is completed with a special numbering and a signaling process.

The invention discloses a construction method and system of a human society person portfolio database on the basis of big data. The construction system comprises a human society business database, a business data synchronization module, an archive information initialization module and an incremental message storage module, wherein the human society business database provides an original data source for the initialization of the human society person portfolio database, and provides message flow LCRs (Logical Change Records) for data increment; the business data synchronization module is used for finishing data initialization from business data to human society process data, so as to realize increment synchronization from the human society business database to a human society business process database; the archive information initialization module is used for defining, scheduling and executing an archive information initialization task, finishing the extraction, the conversion, the cleaning and the integration of human society business process data and storing results to the human society person portfolio database; the incremental message storage module receives an incremental message of an incremental synchronization module, and provides an incremental message flow for triggering flow calculation for an archive information incremental calculation module. According to the construction system, the human society business data is taken as the data source, and a big-data processing technology and a distributed storage technology are used for constructing an accurate and real-time person portfolio.

The invention relates to an arithmetic decoder based on context self-adaptive binary, wherein said decoder comprises an arithmetic decoder controller, a data interface, a mark subscript, a context subscript increment counter, a context manager, a decode engine and a mark detector; the controller is used to command external modules, the communication between nearby information and grammar element value, to simplify the interfaces of whole decoder; the data interface is used to communicate code flow with outer space, to reduce the communication times between decoder and external code flow; the mark subscript and the context subscript increment counter can quickly calculate out the mark subscript and context subscript increment; and the decode engine can realize the decode at several modes, to save the hardware consumption and accelerate the decode.

The invention relates to a real-time large data processing system and method based on distributed internal memory calculation. The real-time large data processing method comprises the following steps: a resource pool is formed by respective internal memory resources of multiple distributed internal memory nodes; when a user originates a task, a client transfers the task and incremental data related to the task within a fixed time interval to a resource scheduler of the resource pool to be applied for execution; the resource scheduler can be used for carrying out deployment in the resource pool according to the internal memory resources needed by the task, corresponding internal memory nodes in the resource pool are appointed for carrying out calculation on the incremental data related to the task, obtained local results of respective calculation are stored in the resource pool; and local results, obtained by virtue of calculation of the appointed internal memory nodes, are calculated in a combination mode to obtain a global calculation result, and the global calculation result is sent to the user. The real-time large data processing system and method is capable of achieving centralized use of distributed internal memories, restoring data in the process of the internal memory calculation and achieving real-time data incremental calculation, is high in data access speed and can be used for providing a real-time analysis result for the user.

The invention discloses an incremental correction method for a tidal atlas of an electric network. The incremental correction method comprises the following steps of: firstly performing structure hierarchical reorganization on an electric network model, defining a voltage class range of the electric network model, then performing incremental calculation on the model, further calculating a graphic increment according to calculation result of the incremental calculation of the model, and finally correcting the graphic increment of the electric network model according to the calculation result of the graphic increment. According to the incremental correction method disclosed by the invention, incremental updating of the tidal atlas of the electric network within a full voltage class range or a single voltage class range of the electric network in the jurisdiction scope of a certain control center of an electric power system can be realized, namely on the basis of realizing full graphic updating, the parts which are not changed during every correction can be prevented from being deleted and re-generated; and simultaneously, according to the incremental correction method disclosed by the invention, the graphic increment is in one-to-one correspondence with a model increment based on an IEC (International Electrotechnical Commission) 1970/CIM (common information model) model standard, so that the changes in tidal flow of the electric network is very easy to identify, and the working difficulty of dispatching staff and operation staff of the electric network can be greatly reduced.

The invention provides a tunneling method and system for automatic surveying, mapping and positioning. The tunneling method comprise the steps that a well lane model given by a design system is dispersed into a bottom plate middle axis multi-section line and a well lane section contour polygon; a machine body coordinate system of a heading machine is set with the right side direction of the heading machine as the X axis, the head direction of the heading machine as the Y axis, and perpendicular to the XOY plane and the overall upward direction as the Z axis; the relative position coordinate increment from the laser target ball position to the turning center of the heading machine is calibrated according to the coordinate axis increment of the machine body coordinate system; the position coordinates of a laser target ball of the heading machine are positioned by using a positioning robot and a north pointing device; according to the position coordinate of the laser target ball and the relative position coordinate increment of the laser target ball position in the machine body coordinate system, the motion base point coordinates of a cantilever of the heading machine is calculated; the heading machine is controlled to cut the radial section according to the multi-section line of the bottom middle axis, the well lane section contour polygon, and the motion base point coordinates of the cantilever of the heading machine. According to the tunneling method and system, the heading machine can be accurately positioned, and the operation is unmanned.

The invention discloses a graph structure matching-based social network analysis method, and relates to the fields of a graph structure matching technique, an incremental calculation technique and the like. The graph structure matching-based social network analysis method mainly comprises the steps as follows: (a) a graphic interface helps a user manage graph data, and constructs a mode pattern and a visual query result; and (b) a query engine invokes a distributed algorithm to carry out structure matching calculation; meanwhile, the matching results are evaluated; and top-K results are selected and are visualized on the graphic interface; and (c) incremental calculation is carried out on the existing matching results by an incremental algorithm, so as to ensure the accuracy and the integrity of the results. Aiming at ''large data'' in a social network, efficient and convenient data analysis and maintenance are achieved through distributed, visual and incremental calculation techniques, so that a key technical support is provided for hotspot applications such as expert recommendation, social circle identification and social position analysis.

A method of selecting a motion vector for use in a motion estimation system in which the motion vector defines movement of a block of pixels between a search window and a reference frame. The method includes the steps of scanning a search window in a fixed order for a suitable match with an area of the reference frame such that each search position within a current row or column of the window is one pixel away from a previous search position, defining a preferred point in the search window, calculating a primary norm function with reference to the preferred point for a given position in each row or column, calculating a norm function for each search position based on a linear increment of the primary norm function for the respective row or column, calculating an Absolute Error (AE) for each search position, based on a difference between a given property of the search position and a position in the reference window, and selecting a motion vector, the displacement of the motion vector defined in terms of the search position having the smallest AE and the smallest norm function. An apparatus for performing the method is also disclosed.

The invention provides a method and a system for realizing checksum updating of a 1588UDP (User Datagram Protocol) packet in multiple MAC (Media Access Control). The method comprises the following steps that: a message outlet processing module reads message data, edits a message header and modifies the message data, substitutes a modified 64-bit time stamp or a time modification domain value with 0, and obtains the value of the original 16-bit UDP checksum by calculation; the current 64-bit time stamp is obtained from a PTP (Precision Time Protocol) engine through a message time identification point, and the value of new 16-bit UDP checksum is obtained based on the value of the original 16-bit UDP checksum by incremental computation; and the MAC substitutes the value of the new 16-bit checksum and the 64-bit time stamp for the previous data while transmitting the message to the position on which the data are modified. In the method, the UDP checksum computing mode before the PTP message enters into an MAC end is modified, and the 64-bit original time stamp or the time modification domain value is not needed to be stored in multiple MAC, so that use of a register or a memory is reduced greatly, and design cost of chips is also reduced.

The invention discloses a log real-time monitoring and early warning method and its device. The log real-time monitoring and early warning method comprises the following steps: collecting server logs; aggregating and summarizing the collected server logs according to predetermined time and business; Incremental calculations are performed according to the aggregated server logs; and the pre-set threshold is used to determine whether to issue an early warning based on the results of incremental calculations. The present invention realizes the monitoring and early warning with high timeliness, high accuracy and low calculation cost through the continuous real-time incremental calculation mode.

The invention relates to a netuser behavior data real-time processing method based on distributed computation. The netuser behavior data real-time processing method includes a starting process and a real-time computing process which are sequentially operated. The starting process includes extracting data from a netuser behavior database, subjecting the data to distributed batching computation to acquire a statistical result initial value, and storing the statistical result initial value into a statistical result cache region and a result database. The real-time computing process includes that a data source end continues to receive event data streams generated from user visit interbehavior data and stores the same into the netuser behavior database, all current event data streams on the data source end are distributed in multiple nodes in distributed manner, incremental computation and agreement stipulation are performed on the event data streams according to the statistical result initial value, and the final result is saved in the statistical result cache region. Compared with the prior art, the netuser behavior data real-time processing method has the advantages such that distributed multi-node parallel computing is supported, incremental computational algorithm of the event stream is designed based on the actual needs, coupling degree with other functions on the network platform is low, and real-time computing is effectively guaranteed.

The invention discloses an incremental computation method on the basis of MapReduce. The incremental computation method includes creating incremental processing models used for caching different historic processing results including one caching combiner results, one caching intermediate results and one directly reusing the results; selecting the corresponding incremental processing models for processing data according to the characteristics of the input data when the input data are acquired and computing the incremental data by calling the cached historic processing results during data processing of the corresponding incremental processing models when the incremental data are present. Via the method selecting the models applicable to the data characteristics for computation, many unnecessary repeated computations can be saved and data processing efficiency is improved.

The invention discloses a link prediction method and system for a clinical temporal knowledge graph. The method comprises first obtaining the clinical temporal knowledge graph, vectorizing an entity and complex semantic relationship, adding context information, performing serialized learning, performing incremental computation on the temporal knowledge graph, extracting a feature vector from the temporal information, establishing a link prediction model for the clinical temporal knowledge graph, wherein the link prediction model includes a triplet vectorization layer, a sequence incremental learning layer, a sequence feature combination layer and an output layer; performing link prediction on the clinical temporal knowledge graph according to the link prediction model. The method, by usingan incremental LSTM model, highlights the semantic and temporal information implied in a clinical fact, mine the dependence information before and after the semantic and temporal information by usingserialized learning, compensating for the low accuracy of time-sensitive knowledge graph prediction of a traditional link prediction model, improve the accuracy of knowledge graph link prediction.

The invention discloses an increment computing method for minimal function dependencies. According to the method, increment detection is performed for judging whether original minimal function dependencies come into existence or not according to a minimal nontrivial function dependence set before the variation of a relation table, an increment data set, and a partition information set of the relation table before the variation, and the minimal nontrivial function dependency set after the variation of the relation table is determined. According to the method, corresponding increment computing for the minimal function dependencies is performed according to tuple operation types (adding, deleting or modifying). Since most minimal function dependencies in an original data set are effective, in the method provided by the invention, all the minimal function dependencies of a new data set do not need to be recalculated, only the newly-added and deleted minimal function dependencies of the original minimal function dependency set need to be calculated. Therefore, the efficiency is relatively high, the flexibility is strong and the calculation results are accurate.