67 results about "Real world data" patented technology

A method for strategy independent optimization of a multi-objective function of a portfolio containing at least one investment is disclosed. The method involves the use of genetic algorithms to arrive at function optimization. A suite of strategies is provided enabling the user to select a strategy and optimize a function. Real world data is drawn from exchanges and is utilized for replication. The invention also discloses a novel combination of apparatus for carrying out the method of invention, typically, using parallel processing.

A method and server computer for generating map images and providing the map images to users through the Internet are described. Web sites are automatically and recursively visited and downloaded through hyperlinks. Content items containing address and establishment information are retrieved from the information as downloaded from the visited web sites. The content retrieved items are indexed to associate the address information items contained therein with the establishment information items contained therein about establishments which are located in the addresses associated therewith respectively. A visual indication indicative of the establishment corresponding to an establishment information item is superimposed on a map image in a position corresponding to the address of this establishment with reference to the indexed content items. The map image is transmitted to a user through the Internet in response to a request message from the user.

In one aspect, a method, systems, and apparatuses provide for online gaming that integrates sensory data and/or gameplay data from a real-world environment, and in particular, interactive online gaming within an environment incorporating playback of a recorded instance of an original, live card game played in a real-world environment, wherein the online game may be provided in a delayed manner or in real-time. In one aspect, sensory data and/or gameplay data from a live card game in a real-world environment are recorded for delayed playback or streamed live in real-time, and a remote player is able to access the game online and participate in the game as if the remote player had been present at the original, live card game in the real-world environment. In one aspect, the remote player may play in the online game at the position/seat occupied by one or more of the original, real-world players in the original, real-world game. In one aspect, in games where a player is dealt his or her own hand of cards, the remote player will receive cards as they were dealt to the original, real-world player that occupied the same position/seat in the original, real-world game. In one aspect, the remote player may able to make strategic decisions during gameplay that differ from those of the original, real-world player, wherein such strategic decisions may affect the outcome of the game for that player. In one aspect, the real-world environment is a gaming area at a casino.

In many areas, recent developments have generated very large datasets from which it is desired to extract meaningful relationships between the dataset elements. However, to date, the finding of such relationships using prior art methods has proved extremely difficult especially in the biomedical arts. Methods for local causal learning and Markov blanket discovery are important recent developments in pattern recognition and applied statistics, primarily because they offer a principled solution to the variable/feature selection problem and give insight about local causal structure. The present invention provides a generative method for learning local causal structure around target variables of interest in the form of direct causes/effects and Markov blankets applicable to very large datasets and relatively small samples. The method is readily applicable to real-world data, and the selected feature sets can be used for causal discovery and classification. The generative method GLL-PC can be instantiated in many ways, giving rise to novel method variants. In general, the inventive method transforms a dataset with many variables into either a minimal reduced dataset where all variables are needed for optimal prediction of the response variable or a dataset where all variables are direct causes and direct effects of the response variable. The power of the invention and significant advantages over the prior art were empirically demonstrated with datasets from a diversity of application domains (biology, medicine, economics, ecology, digit recognition, text categorization, and computational biology) and data generated by Bayesian networks.

A principled, probabilistic approach to meta-learning acts as a go-between for a ‘black-box’ image annotation system and its users. Inspired by inductive transfer, the approach harnesses available information, including the black-box model's performance, the image representations, and a semantic lexicon ontology. Being computationally ‘lightweight.’ the meta-learner efficiently re-trains over time, to improve and/or adapt to changes. The black-box annotation model is not required to be re-trained, allowing computationally intensive algorithms to be used. Both batch and online annotation settings are accommodated. A “tagging over time” approach produces progressively better annotation, significantly outperforming the black-box as well as the static form of the meta-learner, on real-world data.

A method and apparatus for leveraging the inherent massiveness of real-world data sets to solve the problems typically associated with graphing the data is provided. Three particular areas of concern are as follows: a high likelihood of containing instances of bad or corrupted data that could distort the graph; little or no documentation about the type of each variable; and the presence of arbitrarily encoded missing or special values. One embodiment of the invention provides a methodology for automatically selecting a graphing range with minimal scale distortion. Another embodiment of the invention provides a methodology for automatically choosing an appropriate graphing style. Another embodiment of the invention provides a methodology for automatically detecting and filtering special values in data.

Real-world data may not be sparse in a fixed basis, and current high-performance recovery algorithms are slow to converge, which limits compressive sensing (CS) to either non-real-time applications or scenarios where massive back-end computing is available. Presented herein are embodiments for improving CS by developing a new signal recovery framework that uses a deep convolutional neural network (CNN) to learn the inverse transformation from measurement signals. When trained on a set of representative images, the network learns both a representation for the signals and an inverse map approximating a greedy or convex recovery algorithm. Implementations on real data indicate that some embodiments closely approximate the solution produced by state-of-the-art CS recovery algorithms, yet are hundreds of times faster in run time.

A system and method for providing virtual fitting experience for online clothing shopping customers include receiving customer data and clothing data, processing the customer data by a customer data module, processing the clothing data by a clothing data module; generating fitting data by graphic rendering based on the customer data and clothing data with a graphic processing module, and displaying the fitting data with an output module. In addition, a a database module that stores the customer data, the clothing data and the fitting data and a communication module that sends and receives the customer data, the clothing data or the fitting data over electronic networks. A customer inputs her body dimension and face photograph, and chooses or inputs her own clothing data. The graphic processing module renders virtual fitting result for the customer's review. Templates may be used to reduce complexity of handling details of real world data.

A bivariate metric is disclosed, in which one variable measures the variability of the estimate, and the other measures the accuracy of classifying the positive and negative users. A bagged logistic regression model is used, which achieves a comparable classification accuracy as a usual logistic regression, but a much more stable estimate of individual advertising channel contributions. Embodiments of the invention also provide an intuitive and simple probabilistic model to quantify the attribution of different advertising channels directly. Both the bagged logistic model and the probabilistic model are then applied to a real world data set from a multichannel advertising campaign.

A portable sensor unit for capturing motion and/or other data may be securely mounted on objects such as a user's limb, a vehicle, or other items. The sensor unit may then collect motion and/or other data from the object to which it is affixed, and may provide this data to a data logger which stores the data. The data logger may subsequently communicate the data to a gaming system which may tailor the motion characteristics of a virtual object to resemble those of the real-world object from which the motion data was captured. Thus, a user can (for example) capture motion data from a vehicle, with this data being supplied to a video gaming unit which provides a virtual vehicle having the same acceleration/deceleration, handling, and other characteristics.

An apparatus and method for dynamically displaying data in a browser of a client computer. In one aspect, the invention is a method comprising: displaying a web page comprising a primary frame having dynamic fields in said browser, wherein said web page is created by programming language containing specialized tags containing instructional elements adapted to facilitate rendering of visual data in said dynamic fields; searching said programming language of said web page for said specialized tags and creating a companion file, said companion file comprising scripting information based upon said instructional elements and updated real world data stored in a memory source; downloading said companion file; and executing said scripting information contained within said companion file causing said rendering of visual data in said dynamic fields to correspond to said updated real world data.

The invention discloses a method for interactive influence of characters in real world and virtual world. The method comprises the following steps of: (1) acquiring various information of a user in the real world by using a sensor; (2) deducing a user behavior state by using a machine learning method according to various acquired sensor data; (3) comparing the user behavior state with a pre-established user behavior state learning library to obtain character state parameters of the user; (4) setting parameters corresponding to the same state of the user in the real world and the virtual world according to a statistical result to establish functional relation between the two parameters; (5) obtaining the character state parameter of the virtual world through the functional relation and according to the character state parameter obtained in the step 3; and (6) adjusting the state of the character in a virtual game according to the character state parameter of the virtual world.

In accordance with our invention, for two mixture-type probability distribution functions (PDF's), G, H, $G\left(x\right)=\sum _{i=1}^N{\mu }_i{g}_i\left(x\right),H\left(x\right)=\sum _{k=1}^K{\gamma }_k{h}_k\left(x\right),$

where G is a mixture of N component PDF's g_i (x), H is a mixture of K component PDF's h_k (x), μ_i and γ_k are corresponding weights that satisfy $\sum _{i=1}^N{\mu }_i=1\mathrm{and}\sum _{k=1}^K{\gamma }_k=1;$

we define their distance, D_M(G, H), as $D_M\left(G,H\right)=\underset{w=\left[{\omega }_{\mathrm{ik}}\right]}{\min }\sum _{i=1}^N\sum _{k=1}^K{\omega }_{\mathrm{ik}}d\left(g_i,h_k\right)$

where d(g_I, h_k is the element distance between component PDF's g_i and h_k and w satisfie

ω_ik≧0, 1≦i≦N, 1≦k≦K;

and $\sum _{k=1}^K{\omega }_{\mathrm{ik}}={\mu }_i,1\le i\le N,\sum _{i=1}^N{\omega }_{\mathrm{ik}}={\gamma }_k,1\le k\le K.$

The application of this definition of distance to various sets of real world data is demonstrated.

Systems and methods for integrating maps in which roads are represented as polylines. The main novelty of the invention is in using only the locations of the endpoints of the polylines rather than trying to match whole lines. Experiments on real-world data are given, showing that this approach of integration based on matching merely endpoints is efficient and accurate (that is, it provides high recall and precision).

A system for analyzing images and video that is capable of recognizing, classifying, and processing the context and meaning contained therein in a manner similar to human intuitive understanding of such context and meaning. Images and video are gathered through a crowdsourcing portal, fixed cameras, and other remote sensing devices. Real world data relevant to the images and video is gathered using a deep web extraction engine. The resulting inputs are analyzed for context and meaning using machine learning algorithms, whose outputs and reviewed and adjusted by humans through a crowdsourcing portal.