Abstract: Information about media objects within media streams is inferred based on repeat instances of the media objects within the media streams. A system and methods enable the monitoring of one or more media streams and the identification of repeat instances of media objects (e.g., audio and/or video objects) within the media streams. The monitoring and object repeat identification is performed by one or more server computers on a network. Information about a media object can be inferred based on repeat instances of the media object and based on repeat instances of related media objects. The information is transferred from a server to a client in response to a user query entered at the client through an interactive user interface.

Abstract: A collection of web pages is modeled as a directed graph, in which the nodes of the graph are the web pages and directed edges are hyperlinks. Web pages can also be represented by content, or by other features, to obtain a similarity graph over the web pages, where nodes again denote the web pages and the links or edges between each pair of nodes is weighted by a corresponding similarity between those two nodes. A random walk is defined for each graph, and a mixture of the random walks is obtained for the set of graphs. The collection of web pages is then analyzed based on the mixture to obtain a web page analysis result. The web page analysis result can be, for example, clustering of the web pages to discover web communities, classifying or categorizing the web pages, or spam detection indicating whether a given web page is spam or content.

Abstract: Described herein is a system that includes a receiver component that receives first scores for training points and second scores for the training points, wherein the first scores are individually assigned to the training points by a first ranker component and the second scores are individually assigned to the training points by a second ranker component. The apparatus further includes a determiner component in communication with the receiver component that automatically outputs a value for a parameter ? based at least in part upon the first scores and the second scores, wherein ? is used to linearly combine the first ranker component and the second ranker component.

Abstract: A system described herein includes analyzer component that analyzes queries submitted by users and corresponding URLs selected by the users, wherein the queries include a first query and a second query, and wherein the analyzer component determines that the first query and the second query are substantially similar queries. The system additionally includes a correlator component that, responsive to the analyzer component determining that the first query and the second query are substantially similar, generates correlation data that indicates that the first and second queries are substantially similar.

Abstract: A machine learning system to rank data within sets is disclosed. The system comprises a ranking module that has differentiable parameters. The system further comprises a cost calculation module that uses a cost function that depends on pairs of examples and which describes an output of the ranking module. Methods of using the disclosed system are also provided.

Abstract: The present invention relates to a system and methodology to facilitate database processing in accordance with a plurality of various applications. In one aspect, a large database of objects is processed, wherein the objects can be represented as points in a vector space, and two or more objects are deemed ‘close’ if a Euclidean distance between the points is small. This can apply for substantially any type of object, provided a suitable distance measure can be defined. In another aspect, a ‘test’ object having a vector x, is processed to determine if there exists an object y in the database such that the distance between x and y falls below a threshold t. If several objects in the database satisfy this criteria, a list of objects can be returned, together with their corresponding distances. If no objects were to satisfy the criterion, an indication of this condition can also be provided, but in addition, the condition or information relating to the condition can be provided.

Abstract: The present invention provides systems and methods for signal detection and enhancement. The systems and methods utilize one or more discriminative classifiers (e.g., a logistic regression model and a convolutional neural network) to estimate a posterior probability that indicates whether a desired signal is present in a received signal. The discriminative estimators generate the estimated probability based on one or more signal-to-noise ratio (SNRs) (e.g., a normalized logarithmic posterior SNR (nlpSNR) and a mel-transformed nlpSNR (mel-nlpSNR)) and an estimated noise model. Depending on the resolution desired, the estimated SNR can be generated at a frame level or at an atom level, wherein the atom level estimates are utilized to generate the frame level estimate. The novel systems and methods can be utilized to facilitate speech detection, speech recognition, speech coding, noise adaptation, speech enhancement, microphone arrays and echo-cancellation.

Abstract: Aspects of the subject matter described herein relate to predicting and using search engine switching behavior. In aspects, switching components receive a representation of user interactions with at least one browser. The switching components derive information from the representation that is useful in predicting whether a user will switch search engines. The derived information and information about a user's current interaction with a browser is then used by a switch predictor to predict whether the user will switch search engines. This prediction may be used in a variety of ways examples of which are given herein.

Abstract: A system described herein includes a trainer component that receives an estimated gradient of cost that corresponds to a first ranker component with respect to at least one training point and at least one query. The trainer component builds a second ranker component based at least in part upon the received estimated gradient. The system further includes a combiner component that linearly combines the first ranker component and the second ranker component.

Abstract: Described herein is a system that includes a receiver component that receives first scores for training points and second scores for the training points, wherein the first scores are individually assigned to the training points by a first ranker component and the second scores are individually assigned to the training points by a second ranker component. The apparatus further includes a determiner component in communication with the receiver component that automatically outputs a value for a parameter ? based at least in part upon the first scores and the second scores, wherein ? is used to linearly combine the first ranker component and the second ranker component.

Abstract: The concept of variability pertains to whether users exhibit consistent search interaction patterns, for example, in terms of interaction flow or information targeted. Methods are provided for analyzing variability, and then adapting search-related functionality (e.g., processes and/or interfaces) to account for variability characteristics, for example, to account for predictable search interaction behavior.

Abstract: Systems and methods are disclosed that facilitate producing probabilistic outputs also referred to as posterior probabilities. The probabilistic outputs include an estimate of classification strength. The present invention intercepts non-probabilistic classifier output and applies a set of kernel models based on a softmax function to derive the desired probabilistic outputs. Such probabilistic outputs can be employed with handwriting recognition where the probability of a handwriting sample classification is combined with language models to make better classification decisions.

Abstract: A collection of web pages is modeled as a directed graph, in which the nodes of the graph are the web pages and directed edges are hyperlinks. Web pages can also be represented by content, or by other features, to obtain a similarity graph over the web pages, where nodes again denote the web pages and the links or edges between each pair of nodes is weighted by a corresponding similarity between those two nodes. A random walk is defined for each graph, and a mixture of the random walks is obtained for the set of graphs. The collection of web pages is then analyzed based on the mixture to obtain a web page analysis result. The web page analysis result can be, for example, clustering of the web pages to discover web communities, classifying or categorizing the web pages, or spam detection indicating whether a given web page is spam or content.

Abstract: Prior to searching a multidimensional feature space populated with data objects, each dimension in the feature space is divided into a number of intervals. When a query is received, a single interval that is overlapped by the query is selected from each dimension. A reduced set of data objects is then selected that includes only those data objects that overlap the selected intervals. This reduced set of data objects, rather than the entire set of data objects in the feature space, is then used to determine matches for the query.

Abstract: The present invention relates to a system and methodology to facilitate automatic management and pruning of audio files residing in a database. Audio fingerprinting is a powerful tool for identifying streaming or file-based audio, using a database of fingerprints. Duplicate detection identifies duplicate audio clips in a set, even if the clips differ in compression quality or duration. The present invention can be provided as a self-contained application that it does not require an external database of fingerprints. Also, a user interface provides various options for managing and pruning the audio files.

Abstract: A dependency structure is used to divide samples corresponding to items to be ranked into leaf nodes, based on the rank of the items. The dependency structure is trained by splitting or merging training data received at given nodes based on selected features and selected thresholds for those features. A metric is then calculated which is indicative of performance of the node, in splitting the data. The trained structure is then used during runtime to rank items.

Abstract: A model-based system and method for global optimization that utilizes quantum mechanics in order to approximate the global minimum of a given problem (e.g., mathematical function). A quantum mechanical particle with a sufficiently large mass has a ground state solution to the Schrödinger Equation which is localized to the global minimum of the energy field, or potential, it experiences. A given function is modeled as a potential, and a quantum mechanical particle with a sufficiently large mass is placed in the potential. The ground state of the particle is determined, and the probability density function of the ground state of the particle is calculated. The peak of the probability density function is localized to the global minimum of the potential.

Abstract: The present invention relates to a system and methodology to facilitate automatic generation of mnemonic audio portions or segments referred to as audio thumbnails. A system is provided for summarizing audio information. The system includes an analysis component to determine common features in an audio file and a mnemonic detector to extract fingerprint portions of the audio file based in part on the common features in order to generate a thumbnail of the audio file. The generated thumbnails can then be employed to facilitate browsing or searching audio files in order to mitigate listening to longer portions or segments of such files.

Abstract: Prior to searching a multidimensional feature space populated with data objects, each dimension in the feature space is divided into a number of intervals. When a query is received, a single interval that is overlapped by the query is selected from each dimension. A reduced set of data objects is then selected that includes only those data objects that overlap the selected intervals. This reduced set of data objects, rather than the entire set of data objects in the feature space, is then used to determine matches for the query.

Abstract: The present invention relates to a system and methodology to facilitate database processing in accordance with a plurality of various applications. In one aspect, a large database of objects is processed, wherein the objects can be represented as points in a vector space, and two or more objects are deemed ‘close’ if a Euclidean distance between the points is small. This can apply for substantially any type of object, provided a suitable distance measure can be defined. In another aspect, a ‘test’ object having a vector x, is processed to determine if there exists an object y in the database such that the distance between x and y falls below a threshold t. If several objects in the database satisfy this criteria, a list of objects can be returned, together with their corresponding distances. If no objects were to satisfy the criterion, an indication of this condition can also be provided, but in addition, the condition or information relating to the condition can be provided.