Patents by Inventor Srujana Merugu
Srujana Merugu has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20120109637Abstract: Methods and apparatus for performing computer-implemented extraction of temporal information for business entities and events are disclosed. In one embodiment, a sequence of text is obtained. A label is assigned to one or more of a plurality of segments of the text such that each of the one or more of the plurality of segments of the text is classified as temporal data in one of a plurality of classes of temporal data. One or more rules are applied to the one or more segments of the text that have been classified as temporal data to generate a structured representation of the temporal data, where the rules include one or more schematic rules. Each of the schematic rules pertains to one or more of the plurality of classes of temporal data and indicates a structure in which temporal data in the corresponding one or more of the plurality of classes is to be stored.Type: ApplicationFiled: November 1, 2010Publication date: May 3, 2012Applicant: YAHOO! INC.Inventors: Srujana Merugu, Sathiya Keerthi Selvaraj, Vipul Agarwal, Arup Kumar Choudhury
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Patent number: 8140301Abstract: A method (and system) for causal modeling includes modeling a data set. The modeling includes estimating a reverse Bayesian forest for the data set and detecting outliers in a separate data set. Detecting the outliers includes applying the reverse Bayesian forest to the separate data set to obtain a probability value assigned to data points in the separate data set and identifying outliers in the separate data set by evaluating the probability value given by the reverse Bayesian forest.Type: GrantFiled: April 30, 2007Date of Patent: March 20, 2012Assignee: International Business Machines CorporationInventors: Naoki Abe, David L. Jensen, Srujana Merugu, Justin Wai-Chow Wong
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Publication number: 20110153542Abstract: A system is disclosed for obtaining and aggregating opinions generated by multiple sources with respect to one or more objects. The disclosed system uses observed variables associated with an opinion and a probabilistic model to estimate latent properties of that opinion. With those latent properties, the disclosed system may enable publishers to reliably and comprehensively present object information to interested users.Type: ApplicationFiled: December 23, 2009Publication date: June 23, 2011Applicant: Yahoo! Inc.Inventors: Srujana Merugu, Arun Shankar Iyer, Ashwin Kumar V. Machanavajjhala, Santhiya Keerthi Selvaraj, Philip L. Bohannon
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Patent number: 7953676Abstract: A method for predicting future responses from large sets of dyadic data includes measuring a dyadic response variable associated with a dyad from two different sets of data; measuring a vector of covariates that captures the characteristics of the dyad; determining one or more latent, unmeasured characteristics that are not determined by the vector of covariates and which induce local structures in a dyadic space defined by the two different sets of data; and modeling a predictive response of the measurements as a function of both the vector of covariates and the one or more latent characteristics, wherein modeling includes employing a combination of regression and matrix co-clustering techniques, and wherein the one or more latent characteristics provide a smoothing effect to the function that produces a more accurate and interpretable predictive model of the dyadic space that predicts future dyadic interaction based on the two different sets of data.Type: GrantFiled: August 20, 2007Date of Patent: May 31, 2011Assignee: Yahoo! Inc.Inventors: Deepak Agarwal, Srujana Merugu
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Patent number: 7895149Abstract: A system is disclosed for reconciling opinions generated by agents with respect to one or more predicates. The disclosed system may use observed variables and a probabilistic model including latent parameters to estimate a truth score associated with each of the predicates. The truth score, as well as one or more of the latent parameters of the probabilistic model, may be estimated based on the observed variables. The truth score generated by the disclosed system may enable publishers to reliably represent the truth of a predicate to interested users.Type: GrantFiled: December 17, 2007Date of Patent: February 22, 2011Assignee: Yahoo! Inc.Inventors: Srujana Merugu, Philip L. Bohannon, Ashwin Kumar V Machanavajjhala, Pedro DeRose
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Publication number: 20100274770Abstract: Disclosed are methods and apparatus for segmenting and labeling a collection of token sequences. A plurality of segments of one or more tokens in a token sequence collection are partially labeled with labels from a set of target labels using high precision domain-specific labelers so as to generate a partially labeled sequence collection having a plurality of labeled segments and a plurality of unlabeled segments. Any label conflicts in the partially labeled sequence collection are resolved. One or more of the labeled segments of the partially labeled sequence collection are expanded so as to cover one or more additional tokens of the partially labeled sequence collection. A statistical model, for labeling segments using local token and segment features of the sequence collection, is trained based on the partially labeled sequence collection. This trained model is then used to label the unlabeled segments and the labeled segments of the sequence collection so as to generate a labeled sequence collection.Type: ApplicationFiled: April 24, 2009Publication date: October 28, 2010Applicant: Yahoo! Inc.Inventors: Rahul Gupta, Sathiya Keerthi Selvaraj, Daniel Kifer, Srujana Merugu
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Publication number: 20100241639Abstract: Disclosed are methods and apparatus for extracting (or annotating) structured information from web content. Web content of interest from a particular domain is represented as one or more tree instances having a plurality of branching nodes that each correspond to a web object such that the tree instances correspond to one or more structured data instances. The particular domain is associated with domain knowledge that includes one or more presentation rulesets that each specifies a particular structure for a set of data instances, a domain-specific concept labeler, one or more specified properties of the web objects in the tree instances, and a concept schema that specifies a representation of the data to be extracted from the web content. A structured data instance that conforms to the concept schema is extracted from the one or more tree instances based on the domain knowledge for the particular domain.Type: ApplicationFiled: March 20, 2009Publication date: September 23, 2010Applicant: YAHOO! INC.Inventors: Daniel Kifer, Srujana Merugu, Ankur Jain, Sathiya Keerthi Selvaraj, Alok S. Kirpal, Philip L. Bohannon, Raghu Ramakrishnan
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Publication number: 20100169158Abstract: A method of predicting a response relationship between elements of two sets includes: specifying a dyadic response matrix; specifying covariates that measure additional dyadic relationships; specifying a number of row clusters and a number of column clusters for clustering the rows and columns of the response matrix; specifying a rank for cluster factors that model average interactions between row clusters and column clusters by products of cluster factors; and determining prediction parameters for predicting responses between elements of the first set and the second set by improving a likelihood value that relates the prediction parameters to the response matrix, the covariates, the observation weights, the row clusters and the column clusters. Determining the prediction parameters includes: updating the prediction parameters for fixed assignments of row clusters and column clusters, and updating assignments for row clusters and column clusters for fixed prediction parameters.Type: ApplicationFiled: December 30, 2008Publication date: July 1, 2010Applicant: YAHOO! INC.Inventors: Deepak K. AGARWAL, Srujana Merugu
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Publication number: 20100161652Abstract: A classifier development process seamlessly and intelligently integrates different forms of human feedback on instances and features into the data preparation, learning and evaluation stages. A query utility based active learning approach is applicable to different types of editorial feedback. A bi-clustering based technique may be used to further speed up the active learning process.Type: ApplicationFiled: December 24, 2008Publication date: June 24, 2010Applicant: YAHOO! INC.Inventors: Kedar BELLARE, Srujana MERUGU, Sathiya Keerthi SELVARAJ
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Publication number: 20090157589Abstract: A system is disclosed for reconciling opinions generated by agents with respect to one or more predicates. The disclosed system may use observed variables and a probabilistic model including latent parameters to estimate a truth score associated with each of the predicates. The truth score, as well as one or more of the latent parameters of the probabilistic model, may be estimated based on the observed variables. The truth score generated by the disclosed system may enable publishers to reliably represent the truth of a predicate to interested users.Type: ApplicationFiled: December 17, 2007Publication date: June 18, 2009Applicant: Yahoo! Inc.Inventors: Srujana Merugu, Phillip L. Bohannon, Ashwin Kumar Machanavajjhala, Pedro DeRose
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Publication number: 20090055139Abstract: A method for predicting future responses from large sets of dyadic data includes measuring a dyadic response variable associated with a dyad from two different sets of data; measuring a vector of covariates that captures the characteristics of the dyad; determining one or more latent, unmeasured characteristics that are not determined by the vector of covariates and which induce local structures in a dyadic space defined by the two different sets of data; and modeling a predictive response of the measurements as a function of both the vector of covariates and the one or more latent characteristics, wherein modeling includes employing a combination of regression and matrix co-clustering techniques, and wherein the one or more latent characteristics provide a smoothing effect to the function that produces a more accurate and interpretable predictive model of the dyadic space that predicts future dyadic interaction based on the two different sets of data.Type: ApplicationFiled: August 20, 2007Publication date: February 26, 2009Applicant: Yahoo! Inc.Inventors: Deepak Agarwal, Srujana Merugu
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Publication number: 20080270088Abstract: A method (and system) for causal modeling includes modeling a data set using a reverse Bayesian forest.Type: ApplicationFiled: April 30, 2007Publication date: October 30, 2008Applicant: International Business Machines CorporationInventors: Naoki Abe, David L. Jensen, Srujana Merugu, Justin Wai-Chow Wong
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Publication number: 20080208788Abstract: A method (and system) of predicting an unobserved target variable includes building a graphical predictive model from domain knowledge, which takes advantage of conditional independence to facilitate inference about the unobserved target variable, given observations of other variables in the graphical predictive model from a plurality of information sources.Type: ApplicationFiled: February 27, 2007Publication date: August 28, 2008Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Srujana Merugu, Claudia Perlich, Saharon Rosset