Abstract: Method, system, and computer program product for automatic generation of a word-cloud for a content item are provided. The method includes: extracting terms from a content item using statistical selection criteria; weighting a term by a probability that the term is used as a tag; and generating a visual representation of terms with enhanced representation of terms according to the weighting. Weighting a term by a probability that the term is used as a tag may include determining the relative frequency of the term in a folksonomy of tag terms for a domain.

Abstract: A computer-implemented method of training a neural network includes training a first neural network of a self organizing map type with a first set of first text documents each containing one or more keywords in a semantic context to map each document to a point in the self organizing map y semantic clustering; determining, for each keyword in the first set, all points in the self organizing map to which first documents containing said keyword are mapped, as a pattern and storing said pattern for said keyword in a pattern dictionary; forming at least one sequence of keywords from a second set of second text documents each containing one or more keywords in a semantic context; translating said at least one sequence of keywords into at least one sequence of patterns using the pattern dictionary; and training a second neural network with the at least one sequence of patterns.

Abstract: Embodiments of a system and method for an artificial cognitive neural framework are generally described herein.

Abstract: Embodiments of the invention provide systems and methods for managing updates to a financial transaction monitoring system, wherein the financial transaction monitoring system is configured to specially handle any financial transactions involving an entity identified in a list of entities. In one embodiment, the system includes a communication interface configured to receive an update to the list of entities, the update including one or more new keywords. The system may further include a memory device having information about a plurality of transactions.

Abstract: Systems and methods for classifying electronic information or documents into a number of classes and subclasses are provided through an active learning algorithm. In certain embodiments, seed sets may be eliminated by merging relevance feedback and machine learning phases. Such document classification systems are easily scalable for large document collections, require less manpower and can be employed on a single computer, thus requiring fewer resources. Furthermore, the classification systems and methods described can be used for any pattern recognition or classification effort in a wide variety of fields, including electronic discovery in legal proceedings.

Abstract: Peer-to-peer media item recommendations are provided by presenting a selected list of media items to a first user to consider for recommendation to a friend, receiving an indication from the first user that one or more of the presented media items are to be recommended to the friend, and presenting the one or more indicated media items to the friend. The presented list comprises media items the friend hasn't rated, and is selected using a media recommendation engine.

Abstract: Described is a system for searching a continuous data stream for exact matches with a priori stored data sequences. The system includes a neural network with an input and an output layer. The input layer has one neuron for each possible character or number in the data stream, and the output layer has one neuron for each stored pattern. Importantly, the delays of the connections from input to output layer are engineered to match the temporal occurrence of an input character within a stored sequence. Thus, if an input sequence has the proper time gaps between characters, matching a stored pattern, then the delayed neural signals result in a simultaneous activation at the receiving neuron, which indicates a detected pattern. For storing a pattern, only one connection for each pair of input character and output neuron has to be specified resulting in sparse coding and quick storage.

Abstract: A method includes receiving data for an object at a computing device. The method includes sending a representation of the object from the computing device to a display device coupled to the computing device. The object includes a first display element in a featured position and a second display element. The method includes selecting advertising content with a processor of the computing device based on first information retrieved from the data that is associated with the first display element, based on second information retrieved from the data that is associated with the second display element, and based on a first location in the representation of the first display element relative to a second location in the representation of the second display element. The method also includes sending the advertising content from the computing device to the display device for display in an advertising window.

Abstract: Arrangements described relate to associating a meeting room with a meeting. A meeting invitation being accessed by a first recipient can be identified, wherein the meeting invitation is sent to a plurality of recipients. A location associated with the first recipient of the meeting invitation can be identified, and whether the location associated with the first recipient is similar to a location associated with a sender of the meeting invitation can be determined. Responsive to determining that the location associated with the first recipient is not similar to the location associated with a sender of the meeting invitation, the first recipient can be prompted to reserve a meeting room at the location associated with the first recipient. Responsive to receiving from the first recipient an indication of the meeting room being reserved, an association between the meeting and the meeting room can be created.

Abstract: A reliable automated malware classification approach with substantially low false positive rates is provided. Graph-based local and/or global file relationships are used to improve malware classification along with a feature selection algorithm. File relationships such as containing, creating, copying, downloading, modifying, etc. are used to assign malware probabilities and simultaneously reduce the false positive and false negative rates on executable files.

Abstract: Interactive database viewing is provided. A server associated with a database accesses a stored result set from a database query. The server presents a portion of the result set in a list view to a client device remote from the server and the cache memory, where the portion presented is based on filter selection based on fields of the data. In response to changes to the filter selection, the server can dynamically alter the list view without having to again access the database. If a change to the filter selection requests data outside the cached result set, the server accesses the database and updates the cached result set. Inline editing of the data in the list view can be applied back to the database by the server.

Abstract: To facilitate the estimation of relatedness between nodes of a graph, implementations estimate relatedness between nodes in a graph by pre-computing for a subset of sample nodes (e.g., center nodes) a plurality of transition probabilities between each sample node and each of the other nodes in the graph, and then later when queried the implementations calculate in real-time the resultant estimated transition probability between the first node and the second node through the at least one sample node based on the pre-computed transition probabilities.

Abstract: A method and a system are disclosed for querying a document collection based on the layout of only a fragment of the content of a document, specified as a query zone. The method includes providing an index for a collection of documents. In the index, content of a document page in the collection that has been decomposed into layout blocks is indexed according to representations of the blocks and one or more geometric relations between the blocks. A query is generated which is based on representations of blocks determined to be within the query zone and geometric relations between them. This is used to query the index to retrieve pages of documents in the collection which can each be expected to include a layout zone somewhere in the page that is similar in layout to the query zone.

Abstract: Techniques are described for determining and using information related to domains of interest, such as by automatically analyzing documents and other information related to a domain in order to automatically determine relationships between particular terms within the domain. Such automatically determined information may then be used to assist users in obtaining information from the domain that is of interest (e.g., documents with contents that are relevant to user-specified terms and/or to other terms that are determined to be sufficiently related to the user-specified terms). For example, recommendations may be automatically generated for a user by using information about specified preferences or other interests of the user with respect to one or more terms and identifying other particular terms that are sufficiently probable to be of interest to that user, such as based on a generated probabilistic representation of relationships between particular terms for the domain.

Abstract: Methods and apparatus consistent with the invention provide the ability to organize and build understandings of machine data generated by a variety of information-processing environments. Machine data is a product of information-processing systems (e.g., activity logs, configuration files, messages, database records) and represents the evidence of particular events that have taken place and been recorded in raw data format. In one embodiment, machine data is turned into a machine data web by organizing machine data into events and then linking events together.

Abstract: According to one embodiment, generating a domain corpus includes accessing a knowledge base. The knowledge base comprises a set of articles. Each article corresponds to a particular topic and comprises one or more terms that link to other articles corresponding to other topics. A first set of first articles is selected from the knowledge base for a domain corpus. A second set of second articles related to the first set of first articles is identified. The second set of second articles is selected from the knowledge base for the domain corpus. The domain corpus is made available to access.

Abstract: A computer-implemented method of training a neural network includes training a first neural network of a self organizing map type with a first set of first text documents each containing one or more keywords in a semantic context to map each document to a point in the self organizing map y semantic clustering; determining, for each keyword in the first set, all points in the self organizing map to which first documents containing said keyword are mapped, as a pattern and storing said pattern for said keyword in a pattern dictionary; forming at least one sequence of keywords from a second set of second text documents each containing one or more keywords in a semantic context; translating said at least one sequence of keywords into at least one sequence of patterns using the pattern dictionary; and training a second neural network with the at least one sequence of patterns.

Abstract: Aggregate scoring is used to help classify digital content such as content uploaded to multi-user websites (e.g., social networking websites). In one embodiment, specific categories are used that relate to a social implication of content. For example, text, images, audio or other data formats can provide communication perceived to fall into categories such as violent, abusive, rights management, pornographic or other types of communication. The categories are used to provide a raw score to items in various groupings of a site's content. Where items are related to other items such as by organizational, social, legal, data-driven, design methods, or by other principles or definitions, the related items' raw scores are aggregated to achieve a score for a particular grouping of items that reflects, at least in part, scores from two or more of the related items.

Abstract: A temporal pooler for a Hierarchical Temporal Memory network is provided. The temporal pooler is capable of storing information about sequences of co-occurrences in a higher-order Markov chain by splitting a co-occurrence into a plurality of sub-occurrences. Each split sub-occurrence may be part of a distinct sequence of co-occurrences. The temporal pooler receives the probability of spatial co-occurrences in training patterns and tallies counts or frequency of transitions from one sub-occurrence to another sub-occurrence in a connectivity matrix. The connectivity matrix is then processed to generate temporal statistics data. The temporal statistics data is provided to an inference engine to perform inference or prediction on input patterns. By storing information related to a higher-order Markov model, the temporal statistics data more accurately reflects long temporal sequences of co-occurrences in the training patterns.

Abstract: Certain aspects of the present disclosure support a technique for neural temporal coding, learning and recognition. A method of neural coding of large or long spatial-temporal patterns is also proposed. Further, generalized neural coding and learning with temporal and rate coding is disclosed in the present disclosure.

Abstract: A method, system and computer program product is disclosed for intelligent data mining. The method comprises receiving an event from an application, assigning property weights to properties of the event, and building a query from these properties based on the property weights. The method further comprises assigning search engine weights to a group of search engines, selecting at least some of the search engines based on the search engine weights, and sending the built query to the selected search engines. Results from the selected search engines are stored in a knowledge repository and used to adjust the property weights and the search engine weights. The invention may be used to provide an analysis with information about a problem, and to manage a solutions database which can be used for problem determination. The invention provides a low cost solution for collecting relevant information from online sources.

Abstract: A system and method for processing information in unstructured or structured form, comprising a computer running in a distributed network with one or more data agents. Associations of natural language artifacts may be learned from natural language artifacts in unstructured data sources, and semantic and syntactic relationships may be learned in structured data sources, using grouping based on a criteria of shared features that are dynamically determined without the use of a priori classifications, by employing conditional probability constraints.

Abstract: Systems and methods for performing predictive analytics in an electrical grid network are disclosed. In one example of the disclosed technology, a method comprises aggregating a plurality of events from an electrical grid network, analyzing the plurality of events to recognize at least one event pattern, serializing at least one of the event patterns in a database, and predicting a future event pattern based on a correlation of the plurality of event patterns.

Abstract: Real-time condition-based analysis is performed on a machine for providing diagnostic and prognostic outputs indicative of machine status includes a signal processor for receiving signals from sensors adapted for measuring machine performance parameters. The signal processor conditions and shapes at least some of the received signals into an input form for a neural network. A fuzzy adaptive resonance theory neural network receives at least some of the conditioned and shaped signals, and detects and classifies a state of the machine based upon the received conditioned and shaped signals, and upon a predetermined ontology of machine states, diagnostics, and prognostics. The neural network can also determine from the machine state a health status thereof, which can comprise an anomaly, and output a signal representative of the determined health status. A Bayesian intelligence network receives the machine state from the neural network and determines a fault probability at a future time.

Abstract: In various embodiments, a method for compressed transmission of data packet header fields in a packet-oriented data stream may comprise: estimating in advance a data packet header field in a packet-oriented data stream from at least one preceding data packet header field; forming a piece of comparison information which indicates the difference between the data packet header field and the data packet header field estimated in advance using the transmitter neural network; transmitting the comparison information as a compressed data packet header field from the transmitter to a receiver; estimating in advance the data packet header field from at least one already transmitted data packet header field in the packet-oriented data stream using the receiver neural network; and generating the data packet header field from the data packet header field estimated in advance using the neural network of the receiver and from the transmitted piece of comparison information.

Abstract: Methods, systems, and apparatus, including computer programs encoded on one or more computer storage devices, for training and retraining predictive models. A series of training data sets for predictive modeling can be received, e.g., over a network from a client computing system. The training data included in the training data sets is different from initial training data that was used with multiple training functions to train multiple trained predictive models stored in a predictive model repository. The series of training data sets are used with multiple trained updateable predictive models obtained from the predictive model repository and multiple training functions to generate multiple retrained predictive models. An effectiveness score is generated for each of the retrained predictive models. A first trained predictive model is selected from among the trained predictive models included in the predictive model repository and the retrained predictive models based on their respective effectiveness scores.

Abstract: Providing for automated generation of tags (e.g., metadata descriptors) for items of e-mail or syndication formatted communication is described herein. By way of example, a system can include a filtering component that can generate one or more tags based on information relevant to content of the communication, a sender, or recipient, or combinations thereof. In addition, such tags can be automatically attached to a received item, or a presentation component can furnish the tags to a recipient (e.g., by way of a communication device user interface) for selection, whereby selected tags are associated with the item of communication. Accordingly, the subject innovation provides for improved classification and description of items of communication by automatic generation of descriptive and/or representative tags associated therewith.

Abstract: A self adapting cognitive-neural method and system for image analysis is disclosed. The method comprises detecting a set of potential items of interest in an image using a cognitive algorithm, refining the set of potential items of interest using a neural analysis, and adapting the cognitive algorithm based on information gained from the results of the neural analysis. The method may further comprise fusing the results of the cognitive and neural algorithms with a fusion classifier. The neural analysis can include eye tracked EEG, RSVP, or presentation to an operator for visual inspection.

Abstract: This disclosure provide a bottom sediment determining device, which is inputted with an echo signal corresponding to an ultrasonic wave outputted underwater, and determines water bottom sediment using a neural network. The device includes a memory for storing two or more parameters to be used in the neural network so as to be associated with positional information, a receiver for receiving the positional information, an acquisition module for acquiring the parameters corresponding to the positional information, and a setting module for setting the parameters to the neural network.

Abstract: In some embodiments, a streaming message classification method dynamically allocates a stream of messages to a variable number of clusters (e.g. message categories), each containing messages which share a set of similar features. Incoming messages are compared to a collection of known spam clusters. New spam types are identified, and new clusters are created automatically and dynamically in order to accommodate the new spam types. Message clustering is performed in a hyperspace of message feature vectors using a modified k-means algorithm. Triangle inequality distance comparisons may be used to accelerate hyperspace distance calculations.

Abstract: An artificial intelligence system and method for interpreting input from a user and generating a response to the user. The input is converted into an array of concepts which are compared to a database of interrelated concepts. A response is generated based on the concepts in the database and their relationship to the concepts in the input array. The system and method may be implemented in a number of electronic or computer devices to interact with humans or computer systems.

Abstract: The present invention provides a method of real-time crystal peak tracking for avalanche-photodiode (APD) detectors on positron emission tomography (PET) scanners that satisfies the need to compensate for the significant gain drifting due to thermal variations in APD detectors on PET scanners.

Abstract: A simulated consciousness method (10) for an improved human/computer interface. A computer system (12) is programmed to have a Digital Life Form (32) possessing a plurality of attributes (65). A plurality of actions (64) taken relative to objects (60) in the environment (30) contribute to simulated feelings (76) which ultimately control the viability of the Digital Life Form (32). When there are not sufficient energy packets (66) to sustain the Digital Life Form (32) then simulated death 52 results. Therefore, only actions (64) which contribute to the viability of the Digital Life Form (32) are repeated in the long-run. Some of those actions (64) include perception of reality, concept formation, and natural language processing.

Abstract: A system for clustering data objects includes a module for calculating an importance value of at least one member in a first data object represented as a variable length vector of 0 to N members and a clustering module for dynamically forming a plurality of clusters containing one or more data objects. The clustering module is configured to associate the first data object with at least one of the plurality of clusters in dependence upon the at least one member's similarity value in comparison to members in other data objects. The clustering module may be configured to cluster the first data object into a plurality of clusters if it has at least two members and each member belongs to a different cluster.

Abstract: Methods and systems for Web-scale entity relationship extraction are usable to build large-scale entity relationship graphs from any data corpora stored on a computer-readable medium or accessible through a network. Such entity relationship graphs may be used to navigate previously undiscoverable relationships among entities within data corpora. Additionally, the entity relationship extraction may be configured to utilize discriminative models to jointly model correlated data found within the selected corpora.

Abstract: Methods, systems and computer-readable media for finding similarities between visual objects by evaluating user interactions with a collection of visual objects are provided. Using a neural network, human interactions with a collection of visual objects are evaluated to ascertain relationships or connections between visual objects. The relationship between visual objects indicates that the visual objects are similar. Once relationships between visual objects are identified, a user may select one or more visual objects and receive suggested visual objects that are similar to the one or more visual objects selected by the user.

Abstract: The method and circuits of the present invention aim to associate a complex component operator (CC_op) to each component of an input pattern presented to an input space mapping algorithm based artificial neural network (ANN) during the distance evaluation process. A complex operator consists in the description of a function and a set of parameters attached thereto. The function is a mathematical entity (either a logic operator e.g. match(Ai,Bi), abs(Ai?Bi), . . . or an arithmetic operator, e.g. >, <, . . . ) or a set of software instructions possibly with a condition. In a first embodiment, the ANN is provided with a global memory, common for all the neurons of the ANN, that stores all the CC_ops. In another embodiment, the set of CC_ops is stored in the prototype memory of the neuron, so that the global memory is no longer physically necessary. According to the present invention, a component of a stored prototype may now designate objects of different nature.

Abstract: A system and method for processing information in unstructured or structured form, comprising a computer running in a distributed network with one or more data agents. Associations of natural language artifacts may be learned from natural language artifacts in unstructured data sources, and semantic and syntactic relationships may be learned in structured data sources, using grouping based on a criteria of shared features that are dynamically determined without the use of a priori classifications, by employing conditional probability constraints.

Abstract: A system, method and program product for providing biometric security using neuroplastic fidelity. A method is disclosed that includes: receiving biometric data; analyzing the biometric data with a probabilistic neural network and outputting a chromosome containing a binary string; mapping the binary string to a selected extractor and a selected matcher; apply the selected extractor to the biometric data to generate a template; using the selected matcher to compare the template to a set of stored templates to identify a match; and outputting a result.

Abstract: The invention provides molecular markers that are associated with the progression of chronic myeloid leukemia (CML), and methods and computer systems for monitoring the progression of CML in a patient based on measurements of these molecular markers. The present invention also provides CML target genes, and methods and compositions for treating CML patients by modulating the expression or activity of these CML target genes and/or their encoded proteins. The invention also provides genes that are associated with resistance to imatinib mesylate (Gleevec™) treatment in CML patients, and methods and compositions for determining the responsiveness of a CML patient to imatinib mesylate treatment based on measurements of these genes and/or their encoded proteins. The invention also provides methods and compositions for enhancing the effect of Gleevec™ by modulating the expression or activity of these genes and/or their encoded proteins.

Abstract: The claimed subject matter provides a system and/or a method that facilitates reducing spam in search results. An interface can obtain web graph information that represents a web of pages. A spam detection component can determines one or more features based at least in part on the web graph information. The one or more features can provide indications that a particular page of the web graph is spam. In addition, a robust rank component is provided that limits amount of contribution a single page can provide to the target page.

Abstract: Designs for cognitive memory systems storing input data, images, or patterns, and retrieving it without knowledge of where stored when cognitive memory is prompted by query pattern that is related to sought stored pattern. Retrieval system of cognitive memory uses autoassociative neural networks and techniques for pre-processing query pattern to establish relationship between query pattern and sought stored pattern, to locate sought pattern, and to retrieve it and ancillary data.

Abstract: A system for information searching includes a first layer and a second layer. The first layer includes a first plurality of neurons each associated with a word and with a first set of dynamic connections to at least some of the first plurality of neurons. The second layer include a second plurality of neurons each associated with a document and with a second set of dynamic connections to at least some of the first plurality of neurons. The first set of dynamic connections and the second set of dynamic connections can be configured such that a query of at least one neuron of the first plurality of neurons excites at least one neuron of the second plurality of neurons. The excited at least one neuron of the second plurality of neurons can be contextually related to the queried at least one neuron of the first plurality of neurons.

Abstract: Data for a first time period in a primary data sequence is compared with data for a second time period in each of a set of secondary data sequences. The durations of the first and second time periods are correlated, and the first time period is different from the second time period. A ranking is assigned to each secondary data sequence based on the corresponding data for the second time period. The ranking for each of the set of secondary data sequences is written to a computer useable medium. The primary data sequence and the set of secondary data sequences are adjusted based on a request to change the primary data sequence to one of the set of secondary data sequences. The comparing, assigning, and writing are repeated for the adjusted primary data sequence and set of secondary data sequences.

Abstract: A computer-based method and a system for indexing, querying, and ranking documents based on layout are provided. The method includes providing a plurality of documents to computer memory, extracting layout blocks from the provided documents, clustering the layout blocks into a plurality of layout block clusters, computing a representative block for each of the layout block clusters, generating a document index for each provided document based on the layout blocks of the document and the computed representatives blocks, clustering the created document indexes into a plurality of document index clusters, and generating a representative cluster index for each of the document index clusters. The indexes generated, together with the representative blocks and document index clusters, can be stored and used for retrieval of documents responsive to a layout query.

Abstract: Embodiments are configured to provide one or more candidates based in part on an input. In an embodiment, a system includes a prediction engine which can be configured to provide one or more ranked candidates using one or more configurable data sources and/or candidate providers. Each data source can be configured to include a candidate provider to predict and return predicted candidates. The prediction engine can use a predicted candidate to rank and return a ranked candidate to a user interface, process, or other application. In one embodiment, a computing device can include and use a prediction engine which can use a customized ranking component to rank and return ranked candidates based in part on a query type. The customized ranking component can use predicted candidates provided by one or more data sources and/or candidate providers when making a ranking determination.

Abstract: A mirror system includes an image sensor coupled to a mirror, and gathers consumer shopping preferences for merchandise items. During operation, the system gathers one or more sequential images, from the image sensor, of a consumer wearing a first wearable merchandise item in front of the image sensor. Next, the system identifies in the one or more sequential images a first merchandise item being worn by the consumer. Then, the system determines a demographic group associated with the consumer, and detects behavior patterns for the consumer, wherein the behavior pattern indicates an interest level of the consumer for the identified merchandise item. The system then determines a mapping between the identified consumer demographic group and an interest level for the identified merchandise item, and produces a model which encodes the mapping.

Abstract: Described are techniques for using statistical analysis to reduce the number of samples required in accordance with statistical analysis confidence intervals to verify correctness of a component. These techniques may be used in verification of a neural network or other hardware or software component.

Abstract: Context-based user behavior data is collected from a search mechanism. This data includes, for a given query, user feedback (implicit and explicit) on the query and context information on the query. A predictive pattern is applied to the context-based user behavior data in order to produce predicted user satisfaction data. Data mining techniques may be used to create and improve one or more predictive patterns. Predicted user satisfaction data can be used to monitor or improve search mechanism performance, via a display reporting the performance or identification of any queries with a shared characteristic and sub-par user satisfaction. A dynamically-improving search mechanism uses the predicted user satisfaction data to improve the performance of the search mechanism.

Abstract: A simulated consciousness method (10) for an improved human/computer interface. A computer system (12) is programmed to have a Digital Life Form (32) possessing a plurality of attributes (65). A plurality of actions (64) taken relative to objects (60) in the environment (30) contribute to simulated feelings (76) which ultimately control the viability of the Digital Life Form (32). When there are not sufficient energy packets (66) to sustain the Digital Life Form (32) then simulated death 52 results. Therefore, only actions (64) which contribute to the viability of the Digital Life Form (32) are repeated in the long-run. Some of those actions (64) include perception of reality, concept formation, and natural language processing.