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75 results about "Co occurring" patented technology
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Co-Occurring Disorders. The term co-occurring disorder refers to the condition in which an individual has a co-existing mental illness and substance use disorder. While commonly used to refer to the combination of substance use and mental disorders, the term also refers to other combinations of disorders, such a mental disorder...
Predictive modeling of consumer financial behavior using supervised segmentation and nearest-neighbor matching
InactiveUS6839682B1Specific accurate targetingIncrease valueDiscounts/incentivesDigital computer detailsPredictive modellingAlgorithm
Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Consumer vectors are developed within the vector space, to represent interests of particular consumers by virtue of relative vector positions of consumer and merchant vectors. Various techniques, including clustering, supervised segmentation, and nearest-neighbor analysis, are applied separately or in combination to generate improved predictions of consumer behavior.
Owner:CALLAHAN CELLULAR L L C
Predictive modeling of consumer financial behavior using supervised segmentation and nearest-neighbor matching
InactiveUS20050159996A1Improve efficiencyDiscounts/incentivesSpecial data processing applicationsPredictive modellingCo-occurrence
Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Supervised segmentation is applied to merchant vectors to form the merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments. The consumer profiles include consumer vectors derived as summary vectors of selected merchants patronized by the consumer. Predictions of consumer behavior are made by applying nearest-neighbor analysis to consumer vectors, thus facilitating the targeting of promotional offers to consumers most likely to respond positively.
Owner:CALLAHAN CELLULAR L L C
Consistency modeling of healthcare claims to detect fraud and abuse
InactiveUS20080249820A1Accurate pictureEasy to detectComplete banking machinesMedical data miningData dredgingPredictive modelling
Transaction-based behavioral profiling, whereby the entity to be profiled is represented by a stream of transactions, is required in a variety of data mining and predictive modeling applications. An approach is described for assessing inconsistency in the activity of an entity, as a way of detecting fraud and abuse, using service-code information available on each transaction. Inconsistency is based on the concept that certain service-codes naturally co-occur more than do others. An assessment is made of activity consistency looking at the overall activity of an individual entity, as well as looking at the interaction of entities. Several approaches for measuring consistency are provided, including one inspired by latent semantic analysis as used in text analysis. While the description is in the context of fraud detection in healthcare, the techniques are relevant to application in other industries and for purposes other than fraud detection.
Owner:FAIR ISAAC & CO INC
Apparatus for generating a statistical sequence model called class bi-multigram model with bigram dependencies assumed between adjacent sequences
InactiveUS6314399B1High speed machiningRecombinant DNA-technologySpeech recognitionSequence modelProbit
An apparatus generates a statistical class sequence model called A class bi-multigram model from input training strings of discrete-valued units, where bigram dependencies are assumed between adjacent variable length sequences of maximum length N units, and where class labels are assigned to the sequences. The number of times all sequences of units occur are counted, as well as the number of times all pairs of sequences of units co-occur in the input training strings. An initial bigram probability distribution of all the pairs of sequences is computed as the number of times the two sequences co-occur, divided by the number of times the first sequence occurs in the input training string. Then, the input sequences are classified into a pre-specified desired number of classes. Further, an estimate of the bigram probability distribution of the sequences is calculated by using an EM algorithm to maximize the likelihood of the input training string computed with the input probability distributions. The above processes are then iteratively performed to generate statistical class sequence model.
Owner:DENSO CORP
Mining of user-generated playlists for data regarding relationships between digital works
A computer-implemented service recommends works to a user based on works currently or previously played or downloaded by the user on a player device or based on playlists stored on the player device. The works may be, for example, music files, video files, electronic books, or other digital content for playing by users. A user may thus obtain personalized recommendations that are based on works obtained from sources (web sites, physical CDs, etc.) that are independent of the recommendations system. In one embodiment, the service identifies pairs of works that are related to each other by virtue of the relatively high frequency with which they co-occur on playlists or within play histories of users. The resulting mappings of works to related works are in-turn used to select works to recommend to users.
Owner:AMAZON TECH INC
Consistency modeling of healthcare claims to detect fraud and abuse
InactiveUS7813937B1Accurate pictureEasy to detectMedical data miningFinanceData dredgingPredictive modelling
Transaction-based behavioral profiling, whereby the entity to be profiled is represented by a stream of transactions, is required in a variety of data mining and predictive modeling applications. An approach is described for assessing inconsistency in the activity of an entity, as a way of detecting fraud and abuse, using service-code information available on each transaction. Inconsistency is based on the concept that certain service-codes naturally co-occur more than do others. An assessment is made of activity consistency looking at the overall activity of an individual entity, as well as looking at the interaction of entities. Several approaches for measuring consistency are provided, including one inspired by latent semantic analysis as used in text analysis. While the description is in the context of fraud detection in healthcare, the techniques are relevant to application in other industries and for purposes other than fraud detection.
Owner:FAIR ISAAC & CO INC
System and methods for screening, treating, and monitoring psychological conditions
A system for and method of remote monitoring, screening, assessment and treatment of patients having a mental health illness such as post-traumatic stress disorders or other traumatic stress injury and co-occurring symptomatology. Patients in constant communication with one or more healthcare professionals through a wireless network, complete executable programs on their patient handheld electronic devices and transmit the results of the executable programs to their supervising mental health professional. The mental health professionals review and analyze the collected patient data to make clinical assessments of the patients' mental health status.
Owner:DHUMNE ABHIJIT +1
Keyword Extracting Device
InactiveUS20080195595A1Accurate representationAccurate featuresDigital data information retrievalSpecial data processing applicationsFrequency levelCo-occurrence
A keyword extracting device includes high-frequency term extracting means (30) for extracting high-frequency terms which are index terms having a great weight among the index terms in a document group (E) including a plurality of documents (D), the weight including evaluation on the level of an appearance frequency of each index term, clustering means (50) for clustering the high-frequency terms on the basis of a co-occurrence degree C. which is based on the presence / absence of the co-occurrence of each document with the index terms (w) in the document group (E) in each document, score calculating means (70) for calculating a score key(w) of each index term (w) such that a high score is given to the index term among the index terms (w) that co-occurs with the high-frequency term belonging to more clusters (g) and that co-occurs with the high-frequency term in more documents (D), and keyword extracting means (90) for extracting keywords on the basis of the scores. Accordingly, the keywords indicating a feature of a document group including a plurality of documents can be automatically extracted.
Owner:INTPROP BANK CORP (JP)
Phrase-based document clustering with automatic phrase extraction
InactiveUS20110191098A1Reduce data management burdenReduce administrative burdenNatural language data processingSpecial data processing applicationsRecognition algorithmMutual information
Meaningful phrases are distinguished from chance word sequences statistically, by analyzing a large number of documents and using a statistical metric such as a mutual information metric to distinguish meaningful phrases from groups of words that co-occur by chance. In some embodiments, multiple lists of candidate phrases are maintained to optimize the storage requirement of the phrase-identification algorithm. After phrase identification, a combination of words and meaningful phrases can be used to construct clusters of documents.
Owner:MICRO FOCUS LLC
Granular knowledge based search engine
InactiveUS20090119281A1Maximizing capabilitySpecial data processing applicationsData selectionDocument analysisAssociation rule learning
The application borrows terminology from data mining, association rule learning and topology. A geometric structure represents a collection of concepts in a document set. The geometric structure has a high-frequency keyword set that co-occurs closely which represents a concept in a document set. Document analysis seeks to automate the understanding of knowledge representing the author's idea. Granular computing theory deals with rough sets and fuzzy sets. One of the key insights of rough set research is that selection of different sets of features or variables will yield different concept granulations. Here, as in elementary rough set theory, by “concept” we mean a set of entities that are indistinguishable or indiscernible to the observer (i.e., a simple concept), or a set of entities that is composed from such simple concepts (i.e., a complex concept).
Owner:WANG ANDREW CHIEN CHUNG +2
Extracting information about references to entities ROM a plurality of electronic documents
InactiveUS20070016580A1Special data processing applicationsDocument management systemsElectronic documentDocument quality
The present invention provides a method and system of extracting information about references to entities from a plurality of electronic documents. In an exemplary embodiment, the method and system include (1) applying at least one document quality measure to each of the plurality of electronic documents, (2) recognizing the references to entities in the plurality of electronic documents, (3) using at least one reference quality measure for each of the references to entities, (4) computing at least one topical category associated with each of the references to entities, (5) finding at least one co-occurring term associated with each of the references to entities, and (6) characterizing each of the references to entities by at least one characteristic category.
Owner:IBM CORP
Topic-influenced document relationship graphs
Owner:QUID LLC
Adjustment of document relationship graphs
ActiveUS9645999B1Semantic analysisSpecial data processing applicationsDocument preparationData mining
Provided is a process of modifying semantic similarity graphs representative of pair-wise similarity between documents in a corpus, the method comprising obtaining a semantic similarity graph that comprises more than 500 nodes and more than 1000 weighted edges, each node representing a document of a corpus, and each edge weight indicating an amount of similarity between a pair of documents corresponding to the respective nodes connected by the respective edge; obtaining an n-gram indicating that edge weights affected by the n-gram are to be increased or decreased; expanding the n-gram to produce a set of expansion n-grams; adjusting edge weights of edges between pairs of documents in which members of the expanded n-gram set co-occur.
Owner:QUID LLC
Inferring User Interests Using Social Network Correlation and Attribute Correlation
InactiveUS20120311030A1Digital data information retrievalMultiple digital computer combinationsSocial correlationMultiple attribute
Methods and apparatus are provided for inferring user interests from both direct and indirect social neighbors. User interests are inferred from social neighbors by exploiting the correlation among multiple attributes of a user, in addition to the social correlation of an attribute among a group of users. Attributes of a user are inferred by obtaining an inferred set of attributes comprised of one or more attributes of social neighbors of the user. Thereafter, the inferred set is modified using a user attribute correlation model describing a probability that the attributes in the inferred set co-occur on the user and one or more of the social neighbors. An inference quality of the obtained attributes can optionally be obtained based on social network properties of the social neighbors. Interactions with the user and / or the social neighbors can be employed to solicit feedback to improve the one or more inferred attributes.
Owner:IBM CORP
System for analyzing occurrences of logical concepts in text documents
InactiveUS7162465B2Improve information retrievalEnhanced informationData processing applicationsNatural language data processingCo-occurrenceDocumentation
A method for indexing, extracting, analyzing, and utilizing co-occurrences of logical concepts in text documents is disclosed. References to logical concepts are detected by a text processing procedure by detection of descriptors, e.g., names, also including abbreviations, from a hierarchical dictionary with names and synonyms for said logical concepts, or database identifiers. Co-occurring concepts are indexed and stored in a database as a list or a table. Analysis of co-occurrences detects expressed and implied relationships between co-occurring concepts based on statistical and lexical text analysis. The method includes a procedure to create domain-specific hierarchical dictionaries for logical concepts in a given domain.
Owner:JENSSEN TOR KRISTIAN +1
Searching Using Patterns of Usage
InactiveUS20090313227A1Improve recommendationsImprove search resultMetadata video data retrievalSpecial data processing applicationsObject basedCo occurring
In various embodiments, the present invention relates disparate objects based on user behavior, thus enabling search engines to provide more comprehensive and accurate results. According to various embodiments of the present invention, multiple kinds of interactions by users with multiple classes of objects can be analyzed. The result is that disparate classes of objects can be related. Derived relations between text and objects can be used to implement search-like functionality or to extend a conventional text retrieval system.In one embodiment, the present invention is used to improve search results and / or recommendations by employing a filtered co-occurrence matrix that provides a representation as to which queries tend to co-occur with the originally submitted query. By supplementing or replacing the original query with co-occurring queries, the system of the present invention is able to generate results that are more likely to be of interest.
Owner:CORP ONE
Search query processing to identify search string corrections that reflect past search query submissions of users
A search engine process predicts the correct spellings of search terms within multiple-term search queries. In one embodiment, when a user submits a multiple-term search query that includes a non-matching term and at least one matching term, a table is accessed to look up a set of terms that are “related” to the matching term or terms. A spelling comparison function is then used to determine whether any of these related terms is sufficiently similar in spelling to the non-matching term to be deemed a candidate correctly-spelled replacement. A candidate replacement term may automatically be substituted for the non-matching term, or may be suggested to the user as a replacement. The invention also includes a process for identifying terms that are related to each other based on the relatively high frequencies with which they co-occur within search queries of users, database records, and / or specific database fields.
Owner:A9 COM INC
Topic-influenced document relationship graphs
Owner:QUID LLC
Audio signal semantic concept classification method
ActiveUS20140056432A1Reliable methodPerforms betterElectrical apparatusSpeech analysisNatural language processingClassification methods
A method for determining a semantic concept associated with an audio signal captured using an audio sensor. A data processor is used to automatically analyze the audio signal using a plurality of semantic concept detectors to determine corresponding preliminary semantic concept detection values, each semantic concept detector being adapted to detect a particular semantic concept. The preliminary semantic concept detection values are analyzed using a joint likelihood model based on predetermined pair-wise likelihoods that particular pairs of semantic concepts co-occur to determine updated semantic concept detection values. One or more semantic concepts are determined based on the updated semantic concept detection values. The semantic concept detectors and the joint likelihood model are trained together with a joint training process using training audio signals, at least some of which are known to be associated with a plurality of semantic concepts.
Owner:KODAK ALARIS INC
Anomaly data priority assessment device and anomaly data priority assessment method
InactiveUS20190310979A1Improve accuracyDigital data information retrievalElectric testing/monitoringCo-occurrencePriority setting
Provided are: a data related information generating unit for generating data related information DL including detection data and air conditioner information of air conditioners; a class classifying unit for creating a plurality of classes on the basis of the air conditioner information related to alarm data extracted by an alarm data extracting unit among the air conditioner information and for classifying the data related information DL into the plurality of classes; a priority setting unit for setting priority to each of a plurality of types of alarm data and the plurality of classes; and a priority calculating unit for assessing co-occurrence of anomaly data extracted by an anomaly data extracting unit and the alarm data, assessing co-occurrence of the alarm data and the plurality of classes, assigning priority about the alarm data and the plurality of classes to the co-occurred anomaly data, and calculating priority of anomaly data.
Owner:MITSUBISHI ELECTRIC CORP
Method and system of clustering for multi-dimensional data streams
InactiveUS20100106723A1Improve performanceExtended processing timeDigital data processing detailsCharacter and pattern recognitionMultidimensional dataData element
A method for clustering multi-dimensional data streams includes: when data elements are input, determining 1-D subclusters and assigning identifiers to the determined 1-D subclusters; (b) generating a matching set that is a set of identifiers of the 1-D subclusters where each dimensional value of the data elements belongs to the range of the 1-D subclusters of the corresponding dimensions; and (c) determining subclusters by finding a set of frequently co-occurring 1-D subclusters among a set of 1-D subclusters that belong to the generated matching set. With the present invention, the processing time required to find the subclusters can be improved and the performance of the memory is further improved.
Owner:IND ACADEMIC CORP FOUND YONSEI UNIV
System and method for playlist generation based on similarity data
ActiveUS20100076958A1Easy to calculateProcessed quickly and efficientlyMetadata audio data retrievalRecording carrier detailsClient-sideData system
System, method and computer program that encompasses one or more client devices cooperating with a program host's on-line data processing center for making purchase recommendations of media items to a program participant. Accordingly, there is a transmission from a program host to a program participant of identification of at least one recommended-for-purchase media item selected based on the recommended-for-purchase media item being rated as similar to a designated media item presently contained in an inventory of a media library of the program participant. The rating of the recommended-for-purchase media item as being similar to the designated media item presently contained in the inventory of the media library of the program participant is representative of a frequency at which the recommended-for-purchase media item co-occurs with the designated media item in media libraries of others.
Owner:APPLE INC
Playlist-based detection of similar digital works and work creators
InactiveUS20120303713A1Digital data information retrievalDigital data processing detailsWeb sitePersonalization
Owner:AMAZON TECH INC
Method utilizing Chinese online resources for supervising extraction of character relations remotely
ActiveCN104035975AGuaranteed accuracySpecial data processing applicationsLabel propagationData mining
The invention discloses a method utilizing Chinese online resources for supervising extraction of character relations remotely. According to the method, at first, an online encyclopedia website, formed through a semi-manual mode, on a web is utilized for automatically constructing a knowledge base so as to obtain accurate relation types comprehensive as much as possible, and examples of the character relations; then co-occurring names and context features are extracted from a text corpus, and the names and the relation examples in the knowledge base are matched to obtain name pair sets of the marked relations and name pair sets of unmarked relations; finally, a label propagation algorithm is introduced to achieve relation match of unmarked name pairs, so that extraction of the character relations is achieved. According to the method, the knowledge base of the character relations can be automatically constructed, and the richer and more accurate relation types are included; based on the knowledge base, the label propagation algorithm is introduced to supervise extraction of the character relations remotely, and therefore accuracy of results of the extracted relations can be ensured.
Owner:EAST CHINA NORMAL UNIV
Methods, systems, and articles of manufacture for soft hierarchical clustering of co-occurring objects
InactiveUS7644102B2Data processing applicationsDigital data information retrievalDeterministic annealingCo-occurrence
Methods, systems, and articles of manufacture consistent with certain principles related to the present invention enable a computing system to perform hierarchical topical clustering of text data based on statistical modeling of co-occurrences of (document, word) pairs. The computing system may be configured to receive a collection of documents, each document including a plurality of words, and perform a modified deterministic annealing Expectation-Maximization (EM) process on the collection to produce a softly assigned hierarchy of nodes. The process may involve assigning documents and document fragments to multiple nodes in the hierarchy based on words included in the documents, such that a document may be assigned to any ancestor node included in the hierarchy, thus eliminating the hard assignment of documents in the hierarchy.
Owner:XEROX CORP
System and method for creation, representation, and delivery of document corpus entity co-occurrence information
To respond to queries that relate to co-occurring entities on the Web, a compact sparse matrix representing entity co-occurrences is generated and then accessed to satisfy queries. The sparse matrix has groups of sub-rows, with each group corresponding to an entity in a document corpus. The groups are sorted from most occurring entity to least occurring entity. Each sub-row within a group corresponds to an entity that co-occurs in the document corpus, within a co-occurrence criterion, with the entity represented by the group, and to facilitate query response the sub-rows within a group are sorted from most occurring co-occurrence to least occurring co-occurrence.
Owner:INT BUSINESS MASCH CORP +1
Detecting recurring themes in consumer image collections
InactiveUS8625904B2Character and pattern recognitionMetadata still image retrievalDigital imageCo occurring
A method of identifying groups of related digital images in a digital image collection, comprising: analyzing each of the digital images to generate associated feature descriptors related to image content or image capture conditions; storing the feature descriptors associated with the digital images in a metadata database; automatically analyzing the metadata database to identify a plurality of frequent itemsets, wherein each of the frequent itemsets is a co-occurring feature descriptor group that occurs in at least a predefined fraction of the digital images; determining a probability of occurrence for each the identified frequent itemsets; determining a quality score for each of the identified frequent itemsets responsive to the determined probability of occurrence; ranking the frequent itemsets based at least on the determined quality scores; and identifying one or more groups of related digital images corresponding to one or more of the top ranked frequent itemsets.
Owner:MONUMENT PEAK VENTURES LLC
Related word presentation device
InactiveCN101601038APrevent missing searchesDigital data information retrievalSpecial data processing applicationsNatural language processingSearch words
Owner:PANASONIC CORP
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