Patent application number | Description | Published |
20110153664 | Selective Storing of Mining Models for Enabling Interactive Data Mining - Computerized methods, data processing systems, and computer program products for storing of data mining models (DMMs) are provided. A new DMM is created having at least one of the following characteristics: quality and complexity. The new DMM is handled as a candidate for storing in a storage device if a predefined criterion for the characteristics is met. The sum of the sizes of the new DMM and already stored DMMs is determined In response to the sum falling below a storage limit, the new DMM is stored in the storage device. In response to the sum exceeding the storage limit, a decision is taken based on priorities of the DMMs which DMMs to store in the storage device. The priorities depend at least on access frequencies of the DMMs. Upon a data mining request, a corresponding DMM is determined and a user is requested to confirm that data mining is to proceed if quality of the determined DMM does not fulfill a further predefined criterion. | 06-23-2011 |
20120084251 | PROBABILISTIC DATA MINING MODEL COMPARISON - A first data mining model and a second data mining model are compared. A first data mining model M | 04-05-2012 |
20120155290 | CARRYING OUT PREDICTIVE ANALYSIS RELATING TO NODES OF A COMMUNICATION NETWORK - The invention relates to a method for carrying out predictive analysis relating to nodes of a communication network. The method comprises the steps of providing communication event information for a first set of nodes and a second set of nodes of the communication network, providing a set of attributes for the nodes of the first set, using said attributes and said communication event information for determining a set of groups among the first set of nodes, assigning each node of the second set to at least one group of the set of groups based at least on the communication event information available for the second group, the assigning resulting in membership information of the nodes of the second set as well as deriving or applying a prediction model for the second set of nodes based on the communication event information for the second set and the membership information. | 06-21-2012 |
20120158624 | PREDICTIVE MODELING - A predictive analysis generates a predictive model (Padj(Y|X)) based on two separate pieces of information,
| 06-21-2012 |
20120290608 | DATA MANAGEMENT IN RELATIONAL DATABASES - At least one user table in a relational database management system (RDBMS) using a first operator within a structured query language (SQL) command is identified. The first operator within the SQL command is utilized to transfer one or more data items from the at least one user table to a data array within the RDBMS. The data array is processed within the RDBMS, and one or more output values are generated based on the processing. | 11-15-2012 |
20120310874 | Determination of Rules by Providing Data Records in Columnar Data Structures - A method includes providing a columnar database comprising a plurality of columnar data structures associated with one column attribute; providing first data records having a plurality of first attribute-value pairs comprising counting information indicative of a number of first data records having the respective first attribute-value pair; providing mask data structures comprising one or more second attribute-value pairs; selecting second data records by intersecting the columnar data structures and the mask data structures; selecting one of the column attributes and one value contained in the column data structure associated with said selected column attribute as the destination attribute-value pair; creating one second rule for each first attribute-value pair; calculating, for each second rule, a co-occurrence-count between its respective source attribute-value pair and its destination attribute-value pair; and specifically selecting one or more of said second rules as the first rules in dependence on the calculated co-occurrence-count. | 12-06-2012 |
20130018917 | Selective Storing of Mining Models for Enabling Interactive Data Mining - A new data mining model (DMM) is created having at least one of the following characteristics: quality and complexity. The new DMM is handled as a candidate for storing in a storage device if a predefined criterion for the characteristics is met. The sum of the sizes of the new DMM and already stored DMMs is determined. In response to the sum falling below a storage limit, the new DMM is stored in the storage device. In response to the sum exceeding the storage limit, a decision is taken based on priorities of the DMMs which DMMs to store in the storage device. | 01-17-2013 |
20140180973 | Iterative Active Feature Extraction - Techniques for iterative feature extraction using domain knowledge are provided. In one aspect, a method for feature extraction is provided. The method includes the following steps. At least one query to predict at least one future value of a given value series based on a statistical model is received. At least two predictions of the future value are produced fulfilling at least the properties of 1) each being as probable as possible given the statistical model and 2) being mutually divert (in terms of numerical distance measure). A user is queried to select one of the predictions. The user may be queried for textual annotations for the predictions. The annotations may be used to identify additional covariates to create an extended set of covariates. The extended set of covariates may be used to improve the accuracy of the statistical model. | 06-26-2014 |
20140180992 | Iterative Active Feature Extraction - Techniques for iterative feature extraction using domain knowledge are provided. In one aspect, a method for feature extraction is provided. The method includes the following steps. At least one query to predict at least one future value of a given value series based on a statistical model is received. At least two predictions of the future value are produced fulfilling at least the properties of 1) each being as probable as possible given the statistical model and 2) being mutually divert (in terms of numerical distance measure). A user is queried to select one of the predictions. The user may be queried for textual annotations for the predictions. The annotations may be used to identify additional covariates to create an extended set of covariates. The extended set of covariates may be used to improve the accuracy of the statistical model. | 06-26-2014 |
20140188563 | CUSTOMER DEMOGRAPHIC DATA CHANGE DETECTION BASED ON MONITORED UTILITY CONSUMPTION - In general, the present disclosure describes techniques for detecting changes in demographic data of a customer based on energy consumption data of the customer. For example, a customer data management system receives energy consumption data of a customer and detects, based at least in part on the received energy consumption data of the customer, a change in demographic data associated with the customer. The customer data management system then outputs, based at least in part on the detecting, at least one demographic change report associated with the demographic data. | 07-03-2014 |
20140188565 | CUSTOMER DEMOGRAPHIC DATA CHANGE DETECTION BASED ON MONITORED UTILITY CONSUMPTION - In general, the present disclosure describes techniques for detecting changes in demographic data of a customer based on energy consumption data of the customer. For example, a customer data management system receives energy consumption data of a customer and detects, based at least in part on the received energy consumption data of the customer, a change in demographic data associated with the customer. The customer data management system then outputs, based at least in part on the detecting, at least one demographic change report associated with the demographic data. | 07-03-2014 |
20150134306 | CREATING UNDERSTANDABLE MODELS FOR NUMEROUS MODELING TASKS - A computer program product for creating models comprises a computer readable storage medium having stored thereon first program instructions executable by a processor to cause the processor to receive the modeling tasks each having a target variable and at least one covariate, the target variable and the at least one covariate being the same for all of the modeling tasks, a relationship between the target variable and the at least one covariate being different for all of the modeling tasks, and second program instructions executable by the processor to cause the processor to generate, for each of the modeling tasks, a model including a transfer function for approximating the relationship between the target value and the at least one covariate of the modeling task in a manner that at least two of the models share an identical transfer function and the models satisfy an accuracy condition. | 05-14-2015 |
20150134307 | CREATING UNDERSTANDABLE MODELS FOR NUMEROUS MODELING TASKS - A method for generating models for a plurality of modeling tasks is disclosed. The method comprises receiving, with a processing device, the modeling tasks each having a target variable and at least one covariate. The target variable and at least one covariate are the same for all of the modeling tasks. A relationship between the target variable and at least one covariate is different for all of the modeling tasks. For each of the modeling tasks, generating a model including a transfer function for approximating the relationship between the target value and at least one covariate of the modeling task in a manner that at least two of the models share at least one identical transfer function and the models satisfy an accuracy condition. | 05-14-2015 |
20150134650 | MINING PATTERNS IN A DATASET - Accessing data in a database includes receiving, from a first user, a first query for a dataset stored in a database. A first set of patterns is provided in the dataset. For each pattern in the first set of patterns, a significance value is provided in response to the received first query. A set of tags is provided for flagging a pattern of the first set of patterns, the set of tags indicating at least two data categories describing the pattern. Input information received from the first user indicates tags of at least a first subset of patterns of the first set of patterns, wherein each tag of the tags is selected from the set of tags. The significance values of the first subset of patterns are adjusted based on the tags. | 05-14-2015 |
20150142511 | RECOMMENDING AND PRICING DATASETS - A computer processor provides a set of datasets, including at least a first dataset, with each dataset of the set of datasets respectively being configured to allow the dataset to be presented according to multiple variations, with each variation being defined by a selection of at least one transformation. The computer processor receives customer feedback information relating to at least a first variation of the first dataset. The computer processor trains a first machine learning algorithm, based, at least in part, upon the customer feedback information. The computer processor performs, by the first machine learning algorithm, a marketing act. The marketing act includes at least one of the following: (i) defining a new variation of the first dataset, (ii) defining a new transformation for defining variations of the first dataset, (iii) recommending a predefined variation of the first dataset, and (iv) pricing a predefined variation of the first dataset. | 05-21-2015 |
20150142519 | RECOMMENDING AND PRICING DATASETS - A computer processor provides a set of datasets, including at least a first dataset, with each dataset of the set of datasets respectively being configured to allow the dataset to be presented according to multiple variations, with each variation being defined by a selection of at least one transformation. The computer processor receives customer feedback information relating to at least a first variation of the first dataset. The computer processor trains a first machine learning algorithm, based, at least in part, upon the customer feedback information. The computer processor performs, by the first machine learning algorithm, a marketing act. The marketing act includes at least one of the following: (i) defining a new variation of the first dataset, (ii) defining a new transformation for defining variations of the first dataset, (iii) recommending a predefined variation of the first dataset, and (iv) pricing a predefined variation of the first dataset. | 05-21-2015 |
Patent application number | Description | Published |
20140132627 | Automatic Tuning of Value-Series Analysis Tasks Based on Visual Feedback - A method for selecting an analysis procedure for a value series, including displaying a value series on a computer display monitor, receiving one or more sequences of user provided annotations, where the annotations overlay at least a sub-interval of the value series on the computer display monitor, using the sequences of user provided annotations to select an optimal value series analysis method from a set of value series analysis methods, where selecting an optimal value series analysis method includes determining parameter values for the optimal value series analysis method, and presenting the selected optimal value series analysis method and parameters, and the optimal reconstruction of the annotation sequences to the user. | 05-15-2014 |
20140136563 | Accelerating Time Series Data Base Queries Using Dictionary Based Representations - A method for accelerating time series data base queries includes segmenting an original time series of signal values into non-overlapping chunks, where a time-scale for each of the chunks is much less than the time scale of the entire time series, representing time series signal values in each chunk as a weighted superposition of atoms that are members of a shape dictionary to create a compressed time series, storing the original time series and the compressed time series into a database, determining whether a query is answerable using the compressed time series or the original time series, and whether answering the query using the compressed time series is faster. If answering the query is faster using the compressed representation, the query is executed on weight coefficients of the compressed time series to produce a query result, and the query result is translated back into an uncompressed representation. | 05-15-2014 |
20140146078 | Automatic Tuning of Value-Series Analysis Tasks Based on Visual Feedback - A method for selecting an analysis procedure for a value series, including displaying a value series on a computer display monitor, receiving one or more sequences of user provided annotations, where the annotations overlay at least a sub-interval of the value series on the computer display monitor, using the sequences of user provided annotations to select an optimal value series analysis method from a set of value series analysis methods, where selecting an optimal value series analysis method includes determining parameter values for the optimal value series analysis method, and presenting the selected optimal value series analysis method and parameters, and the optimal reconstruction of the annotation sequences to the user. | 05-29-2014 |
20140149444 | Accelerating Time Series Data Base Queries Using Dictionary Based Representations - A method for accelerating time series data base queries includes segmenting an original time series of signal values into non-overlapping chunks, where a time-scale for each of the chunks is much less than the time scale of the entire time series, representing time series signal values in each chunk as a weighted superposition of atoms that are members of a shape dictionary to create a compressed time series, storing the original time series and the compressed time series into a database, determining whether a query is answerable using the compressed time series or the original time series, and whether answering the query using the compressed time series is faster. If answering the query is faster using the compressed representation, the query is executed on weight coefficients of the compressed time series to produce a query result, and the query result is translated back into an uncompressed representation. | 05-29-2014 |
Patent application number | Description | Published |
20090113561 | GENE TRAP CASSETTES FOR RANDOM AND TARGETED CONDITIONAL GENE INACTIVATION - A new type of gene trap cassette, which can induce conditional mutations, relies on directional site-specific recombination systems, which can repair and re-induce gene trap mutations when activated in succession. After the gene trap cassettes are inserted into the genome of the target organism, mutations can be activated at a particular time and place in somatic cells. The gene trap cassettes also create multipurpose alleles amendable to a wide range of post-insertional modifications. Such gene trap cassettes can be used to mutationally inactivate all cellular genes temporally and/or spatially. Cells which contain the inventive gene trap cassette can be used for identification and/or isolation of genes and for the creation of transgenic organisms to study gene function at various developmental stages, including the adult, as well as for the creation of animal models of human disease useful for in vivo drug target validation. | 04-30-2009 |
20100199360 | ENHANCER-CONTAINING GENE TRAP VECTORS FOR RANDOM AND TARGETED GENE TRAPPING - The present invention relates to a novel class of gene trap vector (enhanced gene trap vectors, eGTV) for efficiently identifying silent or weakly expressed target genes in mammalian genomes, methods of their production and methods for identifying and mutating target genes by using the enhanced gene trap vectors. The gene trap vectors of the present invention can also be used for inducing the expression of silent genes and enhancing the expression of weakly expressed genes. The use of the enhanced gene trap vectors for creating transgenic organisms to identify gene function and to validate pharmaceutical compounds prior to clinical applications is a further aspect of the present invention. | 08-05-2010 |
20100242127 | METHODS TO IDENTIFY MODULATORS OF B-RAF PROTEIN KINASE AND THEIR USE FOR THE TREATMENT OF ANXIETY AND DEPRESSION - The present invention relates to a method for identifying a compound capable of modulating an anxiety or depression disorder comprising the steps of: (a) contacting a composition comprising a B-Raf protein or a B-Raf gene in expressible form or a transcript thereof with a compound under conditions that allow for an interaction of the B-Raf protein or the B-Raf gene or a transcript thereof and the compound; and (b) measuring whether said interaction, if any, results in (i) a change of B-Raf kinase activity compared to B-Raf kinase activity in the absence of said compound; (ii) a modulation of the expression of the B-Raf gene compared to B-Raf gene expression in the absence of said compound; or (iii) the formation of a complex between the compound and the B-Raf protein, wherein such a change in activity, modulation of expression or the formation of a complex is indicative of the compound being a modulator of an anxiety or depression disorder. Further, the invention relates to a method for treating an anxiety or depression disorder in an individual comprising administering to the individual an effective amount of a compound inhibiting B-Raf kinase activity or gene expression and to a use of a compound that inhibits B-Raf kinase activity or gene expression in the manufacture of a pharmaceutical composition for treating an anxiety or depression disorder. Moreover, the invention relates to a method of diagnosing a B-Raf associated anxiety or depression disorder and to a genetically engineered mouse. Finally, the invention also relates to a method of identifying another gene contributing to the pathophysiology of an anxiety or depression disorder apart from B-Raf. | 09-23-2010 |
20100299771 | MEANS AND METHODS FOR shRNA MEDIATED CONDITIONAL KNOCKDOWN OF GENES - The present invention relates to a combination of DNA segments comprising: (a) a first segment comprising in 5′ to 3′ or 3′ to 5′ order: (aa) a promoter; (ab) a first DNA sequence comprising: (i) a DNA sequence giving rise upon transcription to the sense strand of an shRNA molecule; (ii) a transcriptional stop element which is flanked by a first type of recombinase recognition sequences; and (iii) a DNA sequence giving rise upon transcription to the antisense strand of an shRNA molecule; (b) a second segment comprising in 5′ to 3′ or 3′ to 5′ order: (ba) a promoter; (bb) a second DNA sequence comprising: (i) a DNA sequence giving rise upon transcription to the sense strand of an shRNA molecule; (ii) a transcriptional stop element which is flanked by a second type of recombinase recognition sequences; and (iii) a DNA sequence giving rise upon transcription to the antisense strand of an shRNA molecule; wherein (i) said first type of recombinase recognition sequences are recognized and recombined by a recombinase but not recombined with said second type of recombinase recognition sequences; (ii) said second type of recombinase recognition sequences are recognized and recombined by the recombinase of (i) but not recombined with said first type of recombinase recognition sequences; and (iii) said DNA sequence of (ab) and (bb) is expressed under the control of said promoters of (aa) and (ba) upon removal of said transcriptional stop elements of (ab) and (bb) by the activity of a recombinase, resulting in transcription of said shRNA molecule in a cell. Further, the invention relates to a genetically engineered non-human animal and a method to produce said transgenic non-human animal. Also, the invention relates to a cell genetically engineered with the DNA molecule of the invention and a method of simultaneously knocking down two genes in a cell. Furthermore, envisaged is a method of identifying a combination of two target genes as a potential drug target and the use of the DNA molecule of the invention for the preparation of a composition for gene therapy. | 11-25-2010 |
20110061118 | VECTORS AND METHODS FOR GENERATING VECTOR-FREE INDUCED PLURIPOTENT STEM (IPS) CELLS USING SITE-SPECIFIC RECOMBINATION - The present invention relates to a DNA molecule comprising: (a) a first DNA sequence comprising: (aa) a coding sequence giving rise upon transcription to a factor that contributes to the reprogramming of a somatic cell into an induced pluripotent stem (iPS) cell; (ab) a promoter mediating the transcription of said coding sequence; and (ac) two sequence motifs that mediate excision of (aa) and/or (ab) from the DNA molecule, wherein one sequence motif is positioned 5′ and the other sequence motif is positioned 3′ of the sequence to be excised; (b) a second DNA sequence comprising a sequence motif that mediates site-specific integration of (a) into another DNA molecule. Further, the invention relates to DNA molecule comprising: (a) a first DNA sequence comprising: (aa) a coding sequence giving rise upon transcription to a factor that contributes to the reprogramming of a somatic cell into an induced pluripotent stem cell; and (ab) a promoter mediating the transcription of said coding sequence; (b) a second DNA sequence comprising: (ba) a sequence motif that mediates extrachromosomal self-replication of the DNA-molecule; and (bb) two sequence motifs that mediate excision of at least said sequence motif of (ba) from the second DNA sequence (b), wherein one sequence motif is located 5′ of (ba) and the other sequence motif 3′ of (ba). Also, the invention relates to a vector comprising the DNA molecule of the invention, a method for assembly of said vector and a somatic cell comprising said DNA molecule or said vector of the invention. Furthermore, the invention relates to methods to generate an induced pluripotent stem (iPS) cell, an induced pluripotent stem cell obtainable by said methods, to a kit comprising the DNA molecule of the invention, to a cell line or cell culture collection comprising the induced pluripotent stem cell of the invention, to the use of said cell or cell line as a research tool, to a method to generate a transgenic non-human animal and to a non-human animal generated by said method. Finally, the invention relates to a composition for gene therapy, regenerative medicine, cell therapy or drug screening. | 03-10-2011 |
20120276537 | HOMOLOGOUS RECOMBINATION IN THE OOCYTE - The present invention relates to a method of modifying a target sequence in the genome of a mammalian or avian oocyte by homologous recombination with a donor nucleic acid sequence, the method comprising the steps (a) introducing into the oocyte a zinc finger nuclease or a nucleic acid molecule encoding the zinc finger nuclease in expressible form, wherein the zinc finger nuclease specifically binds within the target sequence and introduces a double strand break within the target sequence; and (b) introducing a nucleic acid molecule into the oocyte, wherein the nucleic acid molecule comprises the donor nucleic acid sequence and regions homologous to the target sequence. The present invention further relates to a method of producing a non-human mammal or an avian carrying a modified target sequence in its genome. | 11-01-2012 |
20130212725 | FUSION PROTEINS COMPRISING A DNA-BINDING DOMAIN OF A TAL EFFECTOR PROTEIN AND A NON-SPECIFIC CLEAVAGE DOMAIN OF A RESTRICTION NUCLEASE AND THEIR USE - The present invention relates to a method of modifying a target sequence in the genome of a eukaryotic cell, the method comprising the step: (a) introducing into the cell a fusion protein comprising a DNA-binding domain of a Tal effector protein and a non-specific cleavage domain of a restriction nuclease or a nucleic acid molecule encoding the fusion protein in expressible form, wherein the fusion protein specifically binds within the target sequence and introduces a double strand break within the target sequence. The present invention further relates to the method of the invention, wherein the modification of the target sequence is by homologous recombination with a donor nucleic acid sequence further comprising the step: (b) introducing a nucleic acid molecule into the cell, wherein the nucleic acid molecule comprises the donor nucleic acid sequence and regions homologous to the target sequence. The present invention also relates to a method of producing a non-human mammal or vertebrate carrying a modified target sequence in its genome. Furthermore, the present invention relates to a fusion protein comprising a DNA-binding domain of a Tal effector protein and a non-specific cleavage domain of a restriction nuclease. | 08-15-2013 |
20140304847 | RECOMBINATION EFFICIENCY BY INHIBITION OF NHEJ DNA REPAIR - The present invention relates to a method for modifying a target sequence in the genome of a mammalian cell, the method comprising the step of introducing into a mammalian cell: a. one or more compounds that introduce double-strand breaks in said target sequence; b. one or more DNA molecules comprising a donor DNA sequence to be incorporated by homologous recombination into the genomic DNA of said mammalian cell within said target sequence, wherein said donor DNA sequence is flanked upstream by a first flanking element and downstream by a second flanking element, wherein said first and second flanking element are different and wherein each of said first and second flanking sequence are homologous to a continuous DNA sequence on either side of the double-strand break introduced by said one or more compounds of a. within said target sequence in the genome of said mammalian cell; and c. one or more compounds that decrease the activity of the non-homologous end joining (NHEJ) DNA repair complex in said mammalian cell. Further, the invention relates to a method of producing a non-human mammal carrying a modified target sequence in its genome. | 10-09-2014 |