130results about How to "Quick merge" patented technology

Quantum processor based techniques minimize an objective function for example by operating the quantum processor as a sample generator providing low-energy samples from a probability distribution with high probability. The probability distribution is shaped to assign relative probabilities to samples based on their corresponding objective function values until the samples converge on a minimum for the objective function. Problems having a number of variables and / or a connectivity between variables that does not match that of the quantum processor may be solved. Interaction with the quantum processor may be via a digital computer. The digital computer stores a hierarchical stack of software modules to facilitate interacting with the quantum processor via various levels of programming environment, from a machine language level up to an end-use applications level.

A method for authentication of devices (D1, D2, D3) in a wireless network, wherein—a device (D1, D2, D3) periodically switches its mode from a read mode, in which it is able to receive authentication data from one or more other devices (D1, D2, D3), to a write mode, in which it sends out authentication data to the one or more other devices (D1, D2, D3), according to a random time slot scheme, —the device (D1, D2, D3) authenticates itself after having received authentication data from another device (D1, D2, D3) during the read mode, and—the device (D1, D2, D3) switches permanently its mode to the write mode after being authenticated.

A method, system and program storage device are provided for extending an inverted index, which comprises first and second inverted index subfiles to increase the speed of establishing and updating inverted index files. The method includes performing ordered keyword indexing operations of generating an inverted index from data sources, in which a frequency of occurrence of keywords in each of the data sources is calculated, and writing each keyword, the data sources, and the frequency of occurrence of each keyword in the corresponding data sources to the inverted index. If a number of data sources involved in the indexing operations reaches a first threshold, then writing contents of the inverted index as a smallest grid into the first inverted index subfile. If a number of smallest grids in the first inverted index subfile reaches a second threshold, then merging the smallest grids into a merged grid and writing the merged grid into the second inverted index subfile. If the number of merged grids in the second inverted index subfile reaches a third threshold, then further merging the merged grids into a larger merged grid, and writing the larger merged grid back into the first inverted index subfile.

An apparatus for automating a prioritization of an incoming message, including a batch learning module that generates a global classifier based on training data that is input to the batch learning module. A feedback learning module that generates a user-specific classifier based on a plurality of feedback instances. A feature extraction module that receives the incoming message and a topic-based user model, infers a topic of the incoming message based on the topic-based user model, and computes a plurality of contextual features of the incoming message. A classification module that dynamically determines a priority classification strategy for assigning a priority level to the incoming message based on the plurality of contextual features of the incoming message and a weighted combination of the global classifier and the user-specific classifier, and classifies the incoming message based on the priority classification strategy.

A method of automating incoming message prioritization. The method including training a global classifier of a computer system using training data. Dynamically training a user-specific classifier of the computer system based on a plurality of feedback instances. Inferring a topic of the incoming message received by the computer system based on a topic-based user model. Computing a plurality of contextual features of the incoming message. Determining a priority classification strategy for assigning a priority level to the incoming message based on the computed contextual features of the incoming message and a weighted combination of the global classifier and the user specific classifier. Classifying the incoming message based on the priority classification strategy.

A flat file data organization technique is used for storing and retrieving geospatially organized data. The invention reduces transfer time by transferring a few large files in lieu of a large number of small files. It also moves the process of locating a given data file away from the file system to a proprietary code base. Additionally, the invention simplifies database management by having quadtree packets generated on demand.