3772 results about "Search algorithm" patented technology

Methods and systems that record the location of a user and transmit targeted content to a user based upon their current and past location information. A network is configured to include a server programmed with a database of targeted content, a database of location information, a database of user information, a database searching algorithm, and a wireless communication system capable of communicating with the user's mobile device. The location of the mobile device is ascertained and recorded. The location information is analyzed to determine the routes taken by the user, businesses visited by the user, and other behaviors of the user. Targeted content is sent to the mobile device of the user and whether the user visits the physical locations associated with the targeted content is monitored. Payment systems, phone exchange systems, and other features may also be integrated to provide detailed conversion tracking to producers of targeted content and business owners.

A system and method of interactive and live computerized matching in which a first user is provided with a personal data device including a wireless communication system. A secure network is configured to include a server programmed with a personal characteristic database and a database searching algorithm, and a wireless communication system at a specific geographic location that is capable of communicating with the user's personal data device. The first user is allowed to log on through the wireless communication system to the secure network using his or her personal data device, and communicates to and stores in the database personal data defining his or her characteristics and those for his or her ideal match. Either the secure network automatically identifies the first users precise geographic location, or the user himself otherwise indicates and stores in the database of the network an identifying address that indicates his current specific geographic location. The user then instructs the database searching algorithm to search for and identify other users similarly logged on to the network at the same specific geographic location. The user is able to initiate a search of the database for possible matches within the pool of other users also logged on to the network at the same specific geographic location. The secure network then indicates to the first user the results of the search.

The present invention provides a data-structure to store a search database and provides techniques to build this datastructure given a list of prefixes (P) and to search this database efficiently for a best matching prefix for an address D. The data-structure can be stored in standard memory (14), where values are stored associated with memory address locations. The data structure includes representations of addressable linked tables (FIG. 3b). The representations are related to a binary search trie (FIG. 1) and each linked table (T) has at least one entry. Entries in a table span more than one level of the binary search trie. The spanning feature relates to compression of a binary search trie into a finite number of levels (and hence tables). The finite number is less than the number of levels in the binary search trie. Hence the search algorithm is restricted to a finite, and predetermined number of search accesses to the tables to obtain a best-match result.

In general, the invention is directed to a technique for selection of parameter configurations for a neurostimulator using genetic algorithms. The technique may be employed by a programming device to allow a clinician to select parameter configurations, and then program an implantable neurostimulator to deliver therapy using the selected parameter configurations. In operation, the programming device executes an electrode configuration search algorithm to guide the clinician in the selection of electrode configurations. The search algorithm relies on a genetic algorithms to identify potential optimum electrode configurations within an electrode set. The genetic algorithms provide guidance in the electrode configuration selections process, interactively guiding the clinician by suggesting the configurations that are most likely to be efficacious given the results of tests already performed during an evaluation session.

Input text data undergoes language analysis to generate prosody, and a speech database is searched for a synthesis unit on the basis of the prosody. A modification distortion of the found synthesis unit, and concatenation distortions upon connecting that synthesis unit to those in the preceding phoneme are computed, and a distortion determination unit weights the modification and concatenation distortions to determine the total distortion. An Nbest determination unit obtains N best paths that can minimize the distortion using the A* search algorithm, and a registration unit determination unit selects a synthesis unit to be registered in a synthesis unit inventory on the basis of the N best paths in the order of frequencies of occurrence, and registers it in the synthesis unit inventory.

A method includes receiving a text description of a system capability request, and converting the text description into a normalized description of the system capability request. A repository is then queried, based on the normalized description and using a search algorithm, to identify multiple candidate application software units (ASUs). The candidate ASUs are displayed to a user for selection. The user-selected ASU is then deployed, either locally or to at least one remote compute device, in response to receiving the user selection. Deployment can include the user-selected candidate ASU being integrated into a local or remote software package, thus defining a modified software package that is configured to provide the system capability.

A process for refining the results of a query to an internet search engine database by the use of user feedback is disclosed. It is a method to allow a user to rate the relevancy of URLs returned for a specific query. The relevancy ratings for a specific query are combined by the internet search engine with data from a user profile of personal information defined by the user. The internet search engine can determine which items of data in the profile are common between users who have rated a query result highly. The search engine can then modify the search algorithm to return those URLs rated highly by users with common profile attributes. The benefit to the internet is more efficient searching and retrieval of information for users.

Methods and apparatus for performing content inspection across packet boundaries using stateful packet content matching mechanisms. Pattern data structures are employed to facilitate string search algorithm machines. Incoming packets are classified to flows, and stored in corresponding flow queues. Flow table entries are used to identify the pattern data structure for a given flow. During content inspection, the algorithm machine updates state information to identify partial or full matches. When a partial match is detected towards the end of an earlier packet state information in the flow table is updated to reflect the state such that content inspection of a following packet begins at that state. As a result, content inspection across packet boundaries is supported. The techniques may further be employed in a packet processing context pipeline stage.

A radar system is described for use in vehicular applications. The radar system is particularly suited to backup warning systems and lane-change warning systems. The radar minimizes many of the problems found in the prior art by providing programmable delays and programmable gain. The radar uses a range search algorithm to detect and sort targets at various ranges within the field of view of the radar. Each target range corresponds to a particular delay and gain setting. The radar searches for targets at the various ranges by running a target search algorithm. For each target range, the search algorithm causes the proper time delay and gain setting. Targets within the selected range are detected and catalogued. Speed of the targets is obtained through Doppler processing. A display is used to warn the driver of the vehicle of the presence of targets at the various ranges. The warning may be visual and/or audible. When used in a lane-change system, issuance of an audible warning is based on the speed of the vehicle.

A playlist of multimedia content is generated based on the results of a search algorithm operating on a metadata database connected to a network. The search algorithm utilizes a search vector that is generated using demographic data and consumer profile data, and/or based on a consumer search request. The playlist, which can list heterogeneous titles of multimedia content, may be accessed anywhere on the network by any suitable authorized device.

A system, method, and apparatus for signal characterization, estimation, and prediction comprising an integrated search algorithm that cooperatively optimizes several data mining sub-tasks, the integrated search algorithm including a machine learning model, and the method comprising processing the data for data embedding, data embedding the processed data for searching for patterns, extracting time and frequency patterns, and training the model to represent learned patterns for signal characterization, estimation, and prediction.

A “URLIT” identifier is assigned to a URL and embedded in an HTML document located at the URL. The URLIT and other data are described using a Universal Advertisement Markup Language such that high-precision searching of the World Wide Web is possible. URLIT-enabled transactions are conducted through a Universal Toolbar Utility. A search method allows user-definition of search algorithms and includes a ranking method that assigns relevancy scores to documents by polling users. Transaction reliability is enhanced by user participation in a Universal Terms of Use system and a Universal Arbitration system.

A computer process, called VGRAM, improves the performance of these string search algorithms in computers by using a carefully chosen dictionary of variable-length grams based on their frequencies in the string collection. A dynamic programming algorithm for computing a tight lower bound on the number of common grams shared by two similar strings in order to improve query performance is disclosed. A method for automatically computing a dictionary of high-quality grams for a workload of queries. Improvement on query performance is achieved by these techniques by a cost-based quantitative approach to deciding good grams for approximate string queries. An approach for answering approximate queries efficiently based on discarding gram lists, and another is based on combining correlated lists. An indexing structure is reduced to a given amount of space, while retaining efficient query processing by using algorithms in a computer based on discarding gram lists and combining correlated lists.

A method for tracking one or multiple objects from an input video sequence allows a user to select one or more regions that contain the object(s) of interest in the first and the last frame of their choice. An initialization component selects the current and the search frame and divides the selected region into equal sized macroblocks. An edge detection component computes the gradient of the current frame for each macroblock and a threshold component decides then which of the macroblocks contain sufficient information for tracking the desired object. A motion estimation component computes for each macroblock in the current frame its position in the search frame. The motion estimation component utilizes a search component that executes a novel search algorithm to find the best match. The mean absolute difference between two macroblocks is used as the matching criterion. The motion estimation component returns the estimated displacement vector for each block. An output component collects the motion vectors of all the predicted blocks and calculates the new position of the object in the next frame.

Visual tracking of multiple objects in a crowded scene is critical for many applications include surveillance, video conference and human computer interaction. Complex interactions between objects result in partial or significant occlusions, making tracking a highly challenging problem. Presented is a novel efficient approach to tracking a varying number of objects through occlusion. The object tracking during occlusion is posed as a track-based segmentation problem in the joint-object space. Appearance models are used to interpret the foreground into multiple layer probabilistic masks in a Bayesian framework. The search for optimal segmentation solution is achieved by a greedy searching algorithm and integral image for real-time computing. Promising results on several challenging video surveillance sequences have been demonstrated.

The present invention discloses a visual target detection and labeling method. The method includes: an image inputting step, to input an image to be detected; a candidate region extracting step, to extract a candidate window as the candidate region from the image to be detected using selectively search algorithm; a feature description extracting step, to perform feature description on the candidate region using a pre-trained large-scale convolutional neural network and output the feature description of the candidate region; a visual target predicting step, to predict the candidate region based on the feature description of the candidate region using a pre-trained object detection module, to estimate regions having the visual target; and a position labeling step, to labeling the position of the visual target according to the estimated result. Experiments show that, compared with the mainstream week supervision visual target detection and labeling method, the present invention has a stronger ability to excavate positive samples and a more general application prospect, and is suitable for visual target detection and automatic labeling tasks on the large-scale data set.

An automated system (100) and method for analyzing, modeling and valuing elements of a business enterprise on a specified valuation date. The performance of the elements are analyzed using search algorithms and induction algorithms to determine the value drivers associated with each element. The induction algorithms are also used to create composite variables that relate element performance to enterprise revenue, expenses and changes in capital. Predictive models are then used to determine the correlation between the value drivers and the enterprise revenue, expenses and changes in capital. The correlation percentages for each value driver are then multiplied by capitalized value of future revenue, expenses and changes in capital, the resulting numbers for each value driver associated with each element are then added together to calculate a value for each element.

Methods and systems are disclosed for learning a regression decision graph model using a Bayesian model selection approach. In a disclosed aspect, the model structure and/or model parameters can be learned using a greedy search algorithm applied to grow the model so long as the model improves. This approach enables construction of a decision graph having a model structure that includes a plurality of leaves, at least one of which includes a non-trivial linear regression. The resulting model thus can be employed for forecasting, such as for time series data, which can include single or multi-step forecasting.

The present invention is an adaptable pre-matched tuner system and calibration method for measuring reflection factors above Gamma=0.85 for a DUT. The system includes a first and second large-band microwave tuners connected in series, the first and second large-band tuners being mechanically and electronically integrated; and a controller for controlling the two large-band tuners. The first tuner is adapted to act as a pre-matching tuner and the second tuner is adapted to investigate an area of a Smith Chart that is difficult to characterise with a single tuner, so that the combination of the first and second large-band tuners permits the measurement of reflection factors above Gamma=0.85. The pre-matched tuner system allows the generation of a very high reflection factor at any point of the reflection factor plane (Smith Chart). The pre-matched tuner must be properly calibrated, such as to be able to concentrate the search for optimum performance of the DUT in the exact location of the reflection factor plane where the DUT performs best, using a pre-search algorithm.

A method of Digital Image Stabilization (DIS) including a feature point sorting algorithm for selecting optimal feature points, and a computationally efficient tile-vector based search algorithm for deriving motion vectors of the selected feature points, and a feature point motion vector grouping/comparison process for grouping pairs of the selected feature points based on their vector magnitude ratio and their angular difference.

A Digital Image Stabilization method including selecting a Principal transform representing a stationary/background object in the scene of a video frame, based on scoring each of a plurality of transforms of tile motion vector (Tile MV) groups and of feature point motion vector (FP MV) groups, and excluding large moving objects based on the history of the stationary (background) group and the history of each of the plurality motion vector groups.

An automated system (100) and method for analyzing, modeling and valuing elements of a business enterprise on a specified valuation date. The performance of the elements are analyzed using search algorithms and induction algorithms to determine the value drivers associated with each element. The induction algorithms are also used to create composite variables that relate element performance to enterprise revenue, expenses and changes in capital. Predictive models are then used to determine the correlation between the value drivers and the enterprise revenue, expenses and changes in capital. The correlation percentages for each value driver are then multiplied by capitalized value of future revenue, expenses and changes in capital, the resulting numbers for each value driver associated with each element are then added together to calculate a value for each element.