Patents Assigned to Ancestry.com Operations Inc.
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Publication number: 20220253604Abstract: Described herein are systems, methods, and other techniques for extracting one or more keyphrases from an input text. The input text may include a plurality of words. A plurality of token-level attention matrices may be generated using a transformer-based machine learning model. The plurality of token-level attention matrices may be converted into a plurality of word-level attention matrices. A set of candidate phrases may be identified from the plurality of words based on the plurality of word-level attention matrices. The one or more keyphrases may be selected from the set of candidate phrases.Type: ApplicationFiled: February 8, 2022Publication date: August 11, 2022Applicant: Ancestry.com Operations Inc.Inventors: Yingrui Yang, Yen-Yun Yu
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Publication number: 20220253484Abstract: Methods and systems for creating a cluster view person for genealogical studies. Methods may include obtaining a plurality of genealogical trees. Each of the genealogical trees may include a plurality of interconnected nodes representing individuals that are related to each other. Methods may also include identifying one or more of the genealogical trees that contain a similar individual. Whether two individuals are grouped may depend on similarity and/or quality thresholds. Methods may include creating an aggregate individual including each of the similar individuals in each of the identified genealogical trees. The aggregate individual may combine information from each of the similar individuals.Type: ApplicationFiled: April 27, 2022Publication date: August 11, 2022Applicant: Ancestry.com Operations Inc.Inventor: JEFF PHILLIPS
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Publication number: 20220229855Abstract: Systems and methods for determining whether two tree persons in a genealogical database correspond to the same real-life individual. Embodiments include obtaining, from a tree database, a first tree person from a first genealogical tree and a second tree person from a second genealogical tree. Embodiments also include identifying a plurality of familial categories. Embodiments further include, for each familial category of the plurality of familial categories, extracting a first quantity of features for each of the tree persons in the familial category, generating a first similarity score for each possible pairing of tree persons, identifying a representative pairing based on a maximum first similarity score, and extracting a second quantity of features for each of the tree persons in the representative pairing. Embodiments may also include generating a second similarity score based on the second quantity of features.Type: ApplicationFiled: April 7, 2022Publication date: July 21, 2022Applicant: Ancestry.com Operations Inc.Inventors: TYLER FOLKMAN, Rey Furner
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Publication number: 20220189188Abstract: A simplified handwriting recognition approach includes a first network comprising convolutional neural network comprising one or more convolutional layers and one or more max-pooling layers. The first network receives an input image of handwriting and outputs an embedding based thereon. A second network comprises a network of cascaded convolutional layers including one or more subnetworks configured to receive an embedding of a handwriting image and output one or more character predictions. The subnetworks are configured to downsample and flatten the embedding to a feature map and then a vector before passing the vector to a dense neural network for character prediction. Certain subnetworks are configured to concatenate an input embedding with an upsampled version of the feature map.Type: ApplicationFiled: December 9, 2021Publication date: June 16, 2022Applicant: Ancestry.com Operations Inc.Inventors: Raunak Dey, Gopalkrishna Balkrishna Veni, Masaki Stanley Fujimoto, Yen-Yun Yu, Jinsol Lee
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Patent number: 11347798Abstract: Methods and systems for creating a cluster view person for genealogical studies. Methods may include obtaining a plurality of genealogical trees. Each of the genealogical trees may include a plurality of interconnected nodes representing individuals that are related to each other. Methods may also include identifying one or more of the genealogical trees that contain a similar individual. Whether two individuals are grouped may depend on similarity and/or quality thresholds. Methods may include creating an aggregate individual including each of the similar individuals in each of the identified genealogical trees. The aggregate individual may combine information from each of the similar individuals.Type: GrantFiled: December 29, 2016Date of Patent: May 31, 2022Assignee: Ancestry.com Operations Inc.Inventor: Jeff Phillips
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Publication number: 20220138453Abstract: Systems and methods for handwriting recognition using language modeling facilitate improved results by using a trained language model to improve results from a handwriting recognition machine learning model. The language model may be a character-based language model trained on a dataset pertinent to field values on which the handwriting recognition model is to be used. A loss prediction module may be trained with the handwriting recognition model and/or the language model and used to determine whether a prediction from the handwriting recognition model should be refined by passing the prediction through the trained language model.Type: ApplicationFiled: October 28, 2021Publication date: May 5, 2022Applicant: Ancestry.com Operations Inc.Inventors: Jinsol Lee, Gopalkrishna Balkrishna Veni, Masaki Stanley Fujimoto, Yen-Yun Yu
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Patent number: 11321361Abstract: Systems and methods for determining whether two tree persons in a genealogical database correspond to the same real-life individual. Embodiments include obtaining, from a tree database, a first tree person from a first genealogical tree and a second tree person from a second genealogical tree. Embodiments also include identifying a plurality of familial categories. Embodiments further include, for each familial category of the plurality of familial categories, extracting a first quantity of features for each of the tree persons in the familial category, generating a first similarity score for each possible pairing of tree persons, identifying a representative pairing based on a maximum first similarity score, and extracting a second quantity of features for each of the tree persons in the representative pairing. Embodiments may also include generating a second similarity score based on the second quantity of features.Type: GrantFiled: October 19, 2018Date of Patent: May 3, 2022Assignee: ANCESTRY.COM OPERATIONS INC.Inventors: Tyler Folkman, Rey Furner
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Publication number: 20220067438Abstract: Techniques for training a machine-learning (ML) model for captioning images are disclosed. A plurality of feature vectors and a plurality of visual attention maps are generated by a visual model of the ML model based on an input image. Each of the plurality of feature vectors correspond to different regions of the input image. A plurality of caption attention maps are generated by an attention model of the ML model based on the plurality of feature vectors. An attention penalty is calculcated based on a comparison between the caption attention maps and the visual attention maps. A loss function is calculcated based on the attention penalty. One or both of the visual model and the attention model are trained using the loss function.Type: ApplicationFiled: October 14, 2021Publication date: March 3, 2022Applicant: Ancestry.com Operations Inc.Inventors: Jiayun Li, Mohammad K. Ebrahimpour, Azadeh Moghtaderi, Yen-Yun Yu
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Publication number: 20210390704Abstract: Systems and methods for identifying and segmenting objects from images include a preprocessing module configured to adjust a size of a source image; a region-proposal module configured to propose one or more regions of interest in the size-adjusted source image; and a prediction module configured to predict a classification, bounding box coordinates, and mask. Such systems and methods may utilize end-to-end training of the modules using adversarial loss, facilitating the use of a small training set, and can be configured to process historical documents, such as large images comprising text. The preprocessing module within said systems and methods can utilize a conventional image scaler in tandem with a custom image scaler to provide a resized image suitable for GPU processing, and the region-proposal module can utilize a region-proposal network from a single-stage detection model in tandem with a two-stage detection model paradigm to capture substantially all particles in an image.Type: ApplicationFiled: June 9, 2021Publication date: December 16, 2021Applicant: Ancestry.com Operations Inc.Inventors: Masaki Stanley Fujimoto, Yen-Yun Yu
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Publication number: 20210365803Abstract: Systems and methods for determining whether two tree persons in a genealogical database correspond to the same real-life individual. Embodiments include identifying two tree persons in a genealogical database and extracting a plurality of features from both tree persons to generate two vectors. Embodiments also include calculating a plurality of metrics between the two vectors to generate a metric function. Embodiments further include generating feature weights using a recursive process based on training data input by external users, and generating a score by calculating a weighted sum of the metric function being weighted by the feature weights. The generated score may then be compared to a threshold value.Type: ApplicationFiled: August 3, 2021Publication date: November 25, 2021Applicant: Ancestry.com Operations Inc.Inventors: Atanu Roy, Jianlong Qi, Peng Jiang, Aaron Ling, Rey Furner, Lei Wu, Eugene Greenwood, Ian Stiles
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Patent number: 11170257Abstract: Techniques for training a machine-learning (ML) model for captioning images are disclosed. A plurality of feature vectors and a plurality of visual attention maps are generated by a visual model of the ML model based on an input image. Each of the plurality of feature vectors correspond to different regions of the input image. A plurality of caption attention maps are generated by an attention model of the ML model based on the plurality of feature vectors. An attention penalty is calculated based on a comparison between the caption attention maps and the visual attention maps. A loss function is calculated based on the attention penalty. One or both of the visual model and the attention model are trained using the loss function.Type: GrantFiled: October 8, 2019Date of Patent: November 9, 2021Assignee: ANCESTRY.COM OPERATIONS INC.Inventors: Jiayun Li, Mohammad K. Ebrahimpour, Azadeh Moghtaderi, Yen-Yun Yu
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Publication number: 20210319003Abstract: Systems, methods, and other techniques for genealogical entity resolution. In some embodiments, first tree data and second tree data are obtained, the first tree data corresponding to a first tree person and the second tree data corresponding to a second tree person. A set of features is extracted from the first tree data and the second tree data. An individual-level similarity score for each possible pairing of tree persons is generated based on the set of features. A set of most-similar tree persons is identified based on the individual-level similarity score for each possible pairing. A plurality of individual-level similarity scores for the set of most-similar tree persons are provided as input to a family-level ML model to determine that the first tree person and the second tree person correspond to a same individual.Type: ApplicationFiled: July 22, 2019Publication date: October 14, 2021Applicant: Ancestry.com Operations Inc.Inventors: TYLER FOLKMAN, Rey Furner, Drew Pearson
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Publication number: 20210319216Abstract: Described herein are systems, methods, and other techniques for segmenting an input text. A set of tokens are extracted from the input text. Token representations are computed for the set of tokens. The token representations are provided to a machine learning model that generates a set of label predictions corresponding to the set of tokens. The machine learning model was previously trained to generate label predictions in response to being provided input token representations. Each of the set of label predictions indicates a position of a particular token of the set of tokens with respect to a particular segment. One or more segments within the input text are determined based on the set of label predictions.Type: ApplicationFiled: April 12, 2021Publication date: October 14, 2021Applicant: Ancestry.com Operations Inc.Inventor: Carol Myrick Anderson
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Patent number: 11113609Abstract: Systems and methods for determining whether two tree persons in a genealogical database correspond to the same real-life individual. Embodiments include identifying two tree persons in a genealogical database and extracting a plurality of features from both tree persons to generate two vectors. Embodiments also include calculating a plurality of metrics between the two vectors to generate a metric function. Embodiments further include generating feature weights using a recursive process based on training data input by external users, and generating a score by calculating a weighted sum of the metric function being weighted by the feature weights. The generated score may then be compared to a threshold value.Type: GrantFiled: April 5, 2017Date of Patent: September 7, 2021Assignee: ANCESTRY.COM OPERATIONS INC.Inventors: Atanu Roy, Jianlong Qi, Peng Jiang, Aaron Ling, Rey Furner, Lei Wu, Eugene Greenwood, Ian Stiles
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Patent number: 11093746Abstract: Augmented reality is used to display graphical elements overlaid on a continually updating image of an area around an augmented reality device (e.g., a mobile device). The graphical element may contain geographical location information about a grave of an ancestor and/or biographical information about the ancestor. The continually updating image is captured by a camera of the augmented reality device and updates in response to time and motion of the augmented reality device. Based on orientation data and geographical location data collected by the augmented reality device, the graphical element is updated and displayed on the mobile device.Type: GrantFiled: January 30, 2019Date of Patent: August 17, 2021Assignee: Ancestry.com Operations Inc.Inventors: Gary Lee Mangum, James Bart Whiteley, David Layne Boothe, Byron Hundley, Russell Adrian Ochoa, Kendall Jay Jefferson
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Publication number: 20210224651Abstract: Described herein are systems, methods, and other techniques for training a machine learning (ML) model to jointly perform named entity recognition (NER) and relation extraction (RE) on an input text. A set of hyperparameters for the ML model are set to a first set of values. The ML model is trained using a training dataset and is evaluated to produce a first result. The set of hyperparameters are modified from the first set of values to a second set of values. The ML model is trained using the training dataset and is evaluated to produce a second result. Either the first set of values or the second set of values are selected and used for the set of hyperparameters for the ML model based on a comparison between the first result and the second result.Type: ApplicationFiled: January 21, 2021Publication date: July 22, 2021Applicant: Ancestry.com Operations Inc.Inventors: Philip Theodore Crone, Carol Myrick Anderson, Suraj Subraveti
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Publication number: 20210174083Abstract: Embodiments described herein relate generally to a methodology of efficient object classification within a visual medium. The methodology utilizes a first neural network to perform an attention based object localization within a visual medium to generate a visual mask. The visual mask is applied to the visual medium to generate a masked visual medium. The masked visual medium may be then fed into a second neural network to detect and classify objects within the visual medium.Type: ApplicationFiled: February 18, 2021Publication date: June 10, 2021Applicant: Ancestry.com Operations Inc.Inventors: Mohammad K. Ebrahimpour, Yen-Yun Yu, Jiayun Li, Jack Reese, Azadeh Moghtaderi
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Publication number: 20210150262Abstract: Systems and methods for classifying historical images. A feature extractor may create feature vectors corresponding to a plurality of images. A first classification of the plurality of images may be performed based on the plurality of feature vectors, which may include assigning a label to each of the plurality of images and assigning a probability for each of the assigned labels. The assigned probability for each of the assigned labels may be related to a statistical confidence that a particular assigned label is correctly assigned to a particular image. A subset of the plurality of images may be displayed to a display device. An input corresponding to replacement of an incorrect label with a corrected label for a certain image may be received from a user. A second classification of the plurality of images based on the input from the user may be performed.Type: ApplicationFiled: January 26, 2021Publication date: May 20, 2021Applicant: Ancestry.com Operations Inc.Inventors: Laryn Brown, Michael Murdock, Jack Reese, Shawn Reid
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Publication number: 20210110205Abstract: Described herein are systems, methods, and other techniques for training a generative adversarial network (GAN) to perform an image-to-image transformation for recognizing text. A pair of training images are provided to the GAN. The pair of training images include a training image containing a set of characters in handwritten form and a reference training image containing the set of characters in machine-recognizable form. The GAN includes a generator and a discriminator. The generated image is generated using the generator based on the training image. Update data is generated using the discriminator based on the generated image and the reference training image. The GAN is trained by modifying one or both of the generator and the discriminator using the update data.Type: ApplicationFiled: October 8, 2020Publication date: April 15, 2021Applicant: Ancestry.com Operations Inc.Inventors: Mostafa Karimi, Gopalkrishna Veni, Yen-Yun Yu
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Patent number: 10949666Abstract: Embodiments described herein relate generally to a methodology of efficient object classification within a visual medium. The methodology utilizes a first neural network to perform an attention based object localization within a visual medium to generate a visual mask. The visual mask is applied to the visual medium to generate a masked visual medium. The masked visual medium may be then fed into a second neural network to detect and classify objects within the visual medium.Type: GrantFiled: September 11, 2020Date of Patent: March 16, 2021Assignee: ANCESTRY.COM OPERATIONS INC.Inventors: Mohammad K. Ebrahimpour, Yen-Yun Yu, Jiayun Li, Jack Reese, Azadeh Moghtaderi