1407 results about "Categorization" patented technology

A method for computerized interactive search and retrieval of content items, in which contributed content items are separated into discrete classifications, provided to users, evaluated by certain users, and assigned a quality rating based on weightings of the evaluations.

The present invention relates to systems and methods that determine intent for received data (e.g., email, voice, graphics . . . ) and respond to the data based on the intent. The systems and methods employ various combinations of features based on shallow and deep linguistic analysis (e.g., semantic and syntactic) to yield very high accuracy. The systems and methods analyze and categorize received data to locate data that can include intent. This data can be further refined by extracting features related to the intent. The features can be utilized by a classifier to determine the intent. If the intent warrants a response, the data are further scrutinized and reformulated to generate a description that is indicative of the intent. The reformulation can include representing the features in a logical form, transforming the form and generating a description of the intent that can be presented to a user visually and / or audibly.

A technique for vehicle classification and identification from images successively narrows the classification of a vehicle down to vehicle make, model, and other specific characteristics. This process uses location, size, color, shape, and other image characteristics that help differentiate vehicles from other kinds of objects in an image. A broad categorization of the target vehicle is performed by classifying the vehicle according to a predetermined set of general vehicle types. A short list is then created of potential matching vehicle makes and models within the broad category that have the best chance of matching the target vehicle. Specific visible points on the target vehicle are identified and then a wire-frame matching with pre-recorded wire-frame models of the short listed vehicles is performed to produce a set of selected vehicle makes and models.

An apparatus for classifying an input audio signal into audio contents of a first and second class, comprising an audio segmentation module adapted to segment said input audio signal into segments of a predetermined length; a feature computation module adapted to calculate for the segments features characterizing said audio input signal; a threshold comparison module adapted to generate a feature vector for each of said one or more segments based on a plurality of predetermined thresholds, the thresholds including for each of the audio contents of the first class and of the second class a substantially near certainty threshold, a substantially high certainty threshold, and a substantially low certainty threshold; and a classification module adapted to analyze the feature vector and classify each one of said one or more segments as audio contents of the first class, of the second class, or as non-decisive audio contents.

The present invention relates generally to the classification of items into categories, and more generally, to the automatic selection of different classifiers at different places within a hierarchy of categories. An exemplary hierarchical categorization method uses a hybrid of different classification technologies, with training-data based machine-learning classifiers preferably being used in those portions of the hierarchy above a dynamically defined boundary in which adequate training data is available, and with a-priori classification rules not requiring any such training-data being used below that boundary, thereby providing a novel hybrid categorization technology that is capable of leveraging the strengths of its components. In particular, it enables the use of human-authored rules in those finely divided portions towards the bottom of the hierarchy involving relatively close decisions for which it is not practical to create in advance sufficient training data to ensure accurate classification by known machine-learning algorithms, while still facilitating eventual change-over within the hierarchy to machine learning algorithms as sufficient training data becomes available to ensure acceptable performance in a particular sub-portion of the hierarchy.

A useful object-oriented knowledge base system is provided, which comprises an 'object-oriented knowledge base', an inference mechanism, and an ideal dictionary, etc. Sentences used as a 'rule' and / or as a 'fact' in the 'object-oriented knowledge base' are described according to a simple English grammar. Hierarchical structure of nouns-system in an 'ideal thesaurus' is constructed, on the basis of special kind of 'object-oriented-lexical-definition of nouns' recorded in the ideal dictionary. Lexical meaning of a verb whose meaning is specific are derived from that of a verb whose meaning is general and universal, by using 'dichotomy' on the basis of C-language-like way of description of English sentences in the lexicon. The hierarchical structure of verbs-system in an 'ideal classification table' is constructed on the basis of them. The Inference mechanism processes not only mathematically well defined equations but, also simple English sentences, by making full use of the 'ideal thesaurus' and the 'ideal classification table', on the basis of specially contrived 'sentence based object-oriented categorical syllogism'.

The invention provides a specific target emotion classification method based on attention coding and a graph convolution network, and the method comprises the steps: obtaining a context and a hidden state vector corresponding to a specific target through a preset bidirectional recurrent neural network model, and carrying out the multi-head self-attention coding of the context and the hidden statevector; extracting a syntax vector in a syntax dependency tree corresponding to the context by combining a point-by-point convolution graph convolutional neural network, and performing multi-head self-attention coding on the syntax vector; then, multi-head interaction attention is used for carrying out interaction fusion on syntactic information codes, context semantic information codes, syntacticinformation codes and specific target semantic information codes; and splicing the fused result with the context semantic information code to obtain a final feature representation, and obtaining an emotion classification result of the specific target based on the feature representation. Compared with the prior art, the relation between the context and the syntax information and the relation between the specific target and the syntax information are fully considered, and the accuracy of sentiment classification is improved.

Systems, devices, and methods of the present invention detect argumentation in text. In an example, an application executing on a computing device accesses text comprising fragments. The application creates a discourse tree from the text. The discourse tree includes nodes, each nonterminal node representing a rhetorical relationship between two of the fragments and each terminal node of the nodes of the discourse tree is associated with one of the fragments. The application matches each fragment that has a verb to a verb signature, thereby creating a communicative discourse tree. The application determines whether the communicative discourse tree represents text that includes argumentation by applying a classification model trained to detect argumentation to the communicative discourse tree.

Provided is a program recommendation apparatus that recommends a program to a user that is in accordance with the user's preference, by taking into account the importance of keywords used in classifying programs' contents into correct categories. The program recommendation apparatus has a category dictionary containing words as keywords, where each of the keywords is stored in association with contribution factors assigned with respect to categories respectively, searches program information of each program in an EPG for the keywords contained in the category dictionary, for any found keywords, obtains category summations of contribution factors of the found keywords for each of the categories, calculates category evaluation values of the program according to the category summations of the contribution factors, and recommends one or more programs to the user according to a degree of similarity between the category evaluation values of the programs and user preference factors.

Systems, devices, and methods of the present invention uses noisy-robust discourse trees to determine a rhetorical relationship between one or more sentences. In an example, a rhetoric classification application creates a noisy-robust communicative discourse tree. The application accesses a document that includes a first sentence, a second sentence, a third sentence, and a fourth sentence. The application identifies that syntactic parse trees cannot be generated for the first sentence and the second sentence. The application further creates a first communicative discourse tree from the second, third, and fourth sentences and a second communicative discourse tree from the first, third, and fourth sentences. The application aligns the first communicative discourse tree and the second communicative discourse tree and removes any elementary discourse units not corresponding to a relationship that is in common between the first and second communicative discourse trees.

A method and system for automatic coronary stenosis detection in computed tomography (CT) data is disclosed. Coronary artery centerlines are obtained in an input cardiac CT volume. A trained classifier, such as a probabilistic boosting tree (PBT) classifier, is used to detect stenosis regions along the centerlines in the input cardiac CT volume. The classifier classifies each of the control points that define the coronary artery centerlines as a stenosis point or a non-stenosis point.

A useful object-oriented knowledge base system is provided, which comprises an 'object-oriented knowledge base', an inference mechanism, and an ideal dictionary, etc. Sentences used as a 'rule' and / or as a 'fact' in the 'object-oriented knowledge base' are described according to a simple English grammar. Hierarchical structure of nouns-system in an 'ideal thesaurus' is constructed, on the basis of special kind of 'object-oriented-lexical-definition of nouns' recorded in the ideal dictionary. Lexical meaning of a verb whose meaning is specific are derived from that of a verb whose meaning is general and universal, by using 'dichotomy' on the basis of C-language-like way of description of English sentences in the lexicon. The hierarchical structure of verbs-system in an 'ideal classification table' is constructed on the basis of them. The Inference mechanism processes not only mathematically well defined equations but, also simple English sentences, by making full use of the 'ideal thesaurus' and the 'ideal classification table', on the basis of specially contrived 'sentence based object-oriented categorical syllogism'.

A user's context can be captured in terms of experimental results and other locally collected data. The use of extracted links between imported scientific text, biological models or experimental data, and proprietary or public data to provide relevance ranking, filtering, and categorization of imported scientific text or biological models, based upon their linking with the local data is described.