32 results about "Probabilistic framework" patented technology

A data processing system generates recommendations for on-line shopping by scoring recommendations matching the customer's cart contents using by assessing and ranking each candidate recommendation by the expected incremental margin associated with the recommendation being issued (as compared to the expected margin associated with the recommendation not being issued) by taking into consideration historical associations, knowledge of the layout of the site, the complexity of the product being sold, the user's session behavior, the quality of the selling point messages, product life cycle, substitutability, demographics and / or other considerations relating to the customer purchase environment. In an illustrative implementation, scoring inputs for each candidate recommendation (such as relevance, exposure, clarity and / or pitch strength) are included in a probabilistic framework (such as a Bayesian network) to score the effectiveness of the candidate recommendation and / or associated selling point messages by comparing a recommendation outcome (e.g., purchase likelihood or expected margin resulting from a given recommendation) against a non-recommendation outcome (e.g., the purchase likelihood or expected margin if no recommendation is issued). In addition, a probabilistic framework may also be used to select a selling point message for inclusion with a selected candidate recommendation by assessing the relative strength of the selling point messages by factoring in a user profile match factor (e.g., the relative likelihood that the customer matches the various user case profiles).

A probabilistic framework for acoustic-phonetic automatic speech recognition organizes a set of phonetic features into a hierarchy consisting of a broad manner feature sub-hierarchy and a fine phonetic feature sub-hierarchy. Each phonetic feature of said hierarchy corresponds to a set of acoustic correlates and each broad manner feature of said broad manner feature sub-hierarchy is further associated with a corresponding set of acoustic landmarks. A pattern recognizer is trained from a knowledge base of phonetic features and corresponding acoustic correlates. Acoustic correlates are extracted from a speech signal and are presented to the pattern recognizer. Acoustic landmarks are identified and located from broad manner classes classified by the pattern recognizer. Fine phonetic features are determined by the pattern recognizer at and around the acoustic landmarks. The determination of fine phonetic features may be constrained by a pronunciation model. The most probable feature bundles corresponding to words and sentences are those that maximize the joint a posteriori probability of the fine phonetic features and corresponding acoustic landmarks. When the hierarchy is organized as a binary tree, binary classifiers such as Support Vector Machines can be used in the pattern classifier and the outputs thereof can be converted probability measures which, in turn may be used in the computation of the aforementioned joint probability of fine phonetic features and corresponding landmarks.

A micropayment system and method is presented for a payor U to establish payment to payee M for a transaction T, which typically has a very low value TV. The micropayment scheme minimizes the bank's processing costs, while at the same time eliminating the need for users and merchants to interact in order to determine whether a given micropayment should be selected for payment. In one embodiment, the micropayment scheme includes time constraints, which require that an electronic check C for the transaction T be presented to a bank B for payment within a predetermined time / date interval. In another embodiment, the micropayment scheme includes a selective deposit protocol, which guarantees that a user is never charged in excess of what he actually spends, even within a probabilistic framework. In another embodiment, the micropayment scheme includes a deferred selection protocol, which provides the bank with control and flexibility over the payment selection process.

A probabilistic framework to detect controversy on the web. The prior kNN-WC algorithm is recast into a theoretical framework and a new language model introduced. Language models are constructed that are used to calculate probabilities. The probabilities are compared to determine whether or not a certain document is controversial.

The invention discloses a multi-source heterogeneous flight accident track data fusion method, relates to a flight accident data processing method, and belongs to the technical field of data processing. Firstly, a unified time reference correction is performed on various data sources, and then the wavelet algorithm is used. Identify and eliminate abnormal flight data, and then use the least squares algorithm and flight dynamics model data to supplement the sparse flight parameter data. Finally, based on the probability graph model method, various heterogeneous flight data are heterogeneously fused to generate the final flight accident track. Under the uniform probability framework, the present invention uses flight data of different configurations and different sources, as well as the flight dynamics model of the corresponding model, to carry out comprehensive data fusion on the flight accident track, so as to improve the estimation accuracy and update of the flight accident track. frequency.