Abstract: A computing server may continuously update a set of nodes that are addable to a data tree based on past interactions of the user with one or more nodes. The computing server may track a recently interacted set of interacted nodes with which the user has interacted within a number of past interactions. The computing server may select a pool of candidate nodes based on the recently interacted set. At least one of the candidate nodes is within a domain boundary of one of the interacted nodes that is in the recently interacted set. The domain boundary may be determined by the degree of relationship. The computing server may present one or more candidate nodes in the pool as a version of the continuously updated set of nodes. The computing server may update the pool of candidate nodes as additional interactions performed by the user updates the recently interacted set.

Abstract: Systems and methods for importing documents are described. An input image is received and preprocessed. OCR and/or page segmentation and chapter detection are performed. Special-case processing is performed for lists, tables, free text, and other categories. Anaphora analysis, stemming, lemmatization, and relationship detection are performed. A genealogical tree is generated, augmented, or merged based on the extracted entities and relationships.

Abstract: A family tree interface may include a default number of family members in addition to a target node which are expandable upon selection by a user. The default tree interface is expandable by a user vertically to include more generations and laterally. The tree interface includes labels showing a relationship of a tree node to the target node. In some embodiments, one or more family members that have not been rendered may be cached to speed up the visual rendering process. A graphical user interface, in a viewing session, may display an initial view of the family tree associated with the target individual. Upon receipt of an expand request, the viewing session may add the one or more additional family members to generate an expanded view of the family tree. The expanded view may partially adjust the initial view without refreshing the viewing session.

Abstract: The disclosed system links an individual dataset to a database. The system receives a target individual dataset associated with a target individual and identifies candidate individual datasets that are potentially related to the target individual dataset. The system identifies a related individual dataset that has data bits that match some data bits in the target individual dataset. The system then identifies a parent node that is a common parent node to both the target individual dataset and the related individual dataset. The system retrieves a data tree that the parent node belongs to with the data tree containing information describing inter-relationships among datasets in the data tree. A node in the data tree is identified to assign the target individual dataset based on strings of matched data bits and number of the matched strings between the target individual dataset and the datasets in the data tree.

Abstract: Data-sharding systems and/or methods for cost- and time-efficient record search are described. Data-sharding embodiments utilize a name-sharding dimension, optionally in combination with one or more additional dimensions such as record type and year, to reduce latency and reduce search-associated costs. The data-sharding systems and methods embodiments utilize an optimization algorithm to determine a distribution of records related to names. The optimization algorithm may use a three-character prefix for surnames in records to distribute shards across documents, with specific shards relating to no-name and multi-name records allocated.

Abstract: Systems, methods, and/or computer-program products for generating a photo composite are configured to identify a facial photo, assign a community such as a genetic community to the identified facial photo, select and retrieve a subset of photos from a genetic community, determine a landmark in each photo of the subset of photos, compute and apply a similarity transform to each photo based and its landmarks, update estimates of transformed averaged landmarks, calculate a triangularization of the transformed averaged landmarks, warp images to the average image landmarks, and combine the intensities of the warped images. The communities are identified from genetic information. The facial photos are identified from a network of genealogical trees and/or a collection of historical records.

Abstract: A user may select one or more potential common ancestors with a DNA match to view the target individual's relationship with them. The process may include identifying, from a first genealogical profile of the target individual. A first individual has a first linkage that connects the target individual towards the selected potential common ancestor. The process may also include identifying, from a second genealogical profile of the DNA match, a second individual who has a second linkage that connects the DNA match towards the selected potential common ancestor. The process may further include connecting the first linkage and the second linkage with the selected potential common ancestor by adding one or more individuals whose profiles are retrieved from other searchable genealogical profiles stored in the online system. With the nodes and connections available, the process may generate a map of visual connections between the target individual and the DNA match.

Abstract: Provided herein are systems, devices, and methods for sample collection. A sample collection device may comprise a vessel, a lid, and pre-loaded liquid solutions. The sample collection device may collect a liquid sample, such as a biological sample. The liquid solutions may comprise reagents for preserving and/or stabilizing biological samples, such as saliva, collected in the vessel. A chamber comprising the liquid solutions may be located in the vessel and/or the lid. In some instances, the liquid solution may be released from the chamber upon closure of the vessel with the lid. In some instances, the liquid solution may be released from the chamber upon actuation of an implement, such as a plunger. In some instances, the liquid solution may be released upon compression of an absorbent member. The sample collecting device may be delivered to a remote location for further processing and/or analysis.

Abstract: 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 the 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.

Abstract: Disclosed herein relates to example embodiments for recognizing handwritten information in a genealogical record. A computing server may receive a genealogical record. The genealogical record may take the form of an image of a physical form having a structured layout, fields, and handwritten information. The computing server may divide the genealogical record into a plurality of areas based on the structured layout. The computing server may identify, for a particular area, a type of field that is included within the particular area. The computing server may select a handwriting recognition model for identifying the handwritten information in the particular area. The handwriting recognition model may be selected based on the type of the field. The computing server may input an image of the particular area to the handwriting recognition model to generate text of the handwritten information. The computing server may store the text of the handwritten information.

Abstract: 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.

Abstract: Search-result explanation systems, methods, and computer-program products receive a user search query, expand the search query into a plurality of sub-queries, perform a database search using the expanded user search query, and determine which sub-queries of the plurality of sub-queries matched with a particular search result. Results from the database search are re-indexed in an index generated on-the-fly and in-memory, within which the results are searched using the sub-queries to determine matching fields and match types. A score is determined based on the type of match(es) with a particular search result based on one or more predefined weights and normalized using a denominator comprising a fictitious, on-the-fly record configured to receive a perfect score according to the received user search query. A user interface showing ranked results and explanations for the ranking, including a score for the result based on the expanded user search query.

Abstract: Described are computational methods to reconstruct the chromosomes (and genomes) of ancestors given genetic data, IBD information, and full or partial pedigree information of some number of their descendants.

Abstract: 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.

Abstract: 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.

Abstract: Disclosed are systems, computer-program products, and computer-implemented methods for the automatic estimation of geographic boundaries. Implementations of the foregoing may be useful for automatedly determining the geographic boundary of a community. In some embodiments, a computing device may receive birth location data related to the community. Enriched birth locations for the community may be determined based on likelihood metrics. An estimated geographic boundary of the community may be determined. The estimated geographic boundary may correspond to a probability density of the enriched birth locations represented using the geographical coordinates. A graphical user interface may present a map and the estimated geographic boundary of the community overlaying the map.

Abstract: An input sample SNP genotype is divided into a plurality of windows, each including a sequence of SNPs. For each window, a diploid hidden Markov Model (HMM) is built and from a haplotype Markov Model (MM). The diploid HMM for a window is used to determine the probability that the window corresponds to a pair of labels (e.g., ethnicity labels). An inter-window HMM, with a set of states for each window, is built based on the diploid HMMs for each window. Labels are assigned to the input sample genotype based on the inter-window HMM.

Abstract: A storytelling interface comprising a map panel and a genealogy panel, and methods for using the same, are described. The storytelling interface facilitates dynamic and automatic scaling and relocation of the map panel based on a user's location within the genealogy panel, which facilitates a continuous scrolling operation to navigate between different sections of the genealogy panel. The storytelling interface facilitates a user receiving, viewing, and interacting with DNA and ethnic communities results determined from DNA testing, and allows a user to navigate through pertinent communities in both time and/or space.

Abstract: A computing device may receive a target data instance. The computing device may identify a plurality of matched segments that match to the target data instance for at least a threshold length. The computing device may define, based on overlapping of the matched segments, the target data instance as a plurality of data string ranges, wherein each divided data string is matched to a set of overlapping matched segments. The computing device may apply an iterative clustering algorithm to group the plurality of data string ranges based on values of a similarity metric among data string ranges that are assigned to a given group. The computing device may attribute a first set of data string ranges that are assigned to a first group to a first inheritance.

Abstract: Disclosed herein relates to a method that improves the accuracy of producing family trees. The DNA of a target individual is processed to find a matching individual. Using the known family tree of the matching individual, multiple candidate family trees are generated with multiple proposed placements for the target individual. For each candidate family tree, a genetic likelihood for a proposed relationship and the other DNA test takers in the family tree. A birth-year probability is determined by identifying a most recent common ancestor (MRCA). The birth-year probability is based on the number of years between the target individual and the matching individual and a normal distribution of ages for parent-child age differences in a population. The genetic likelihood is converted to a genetic probability so that it can be compared with or added to the birth-year probability. Based on the two probabilities, the candidate family trees are sorted.