Abstract: 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.

Abstract: Described embodiments enable identification of family networks using combinations of DNA analysis and genealogical information. Genealogical data is provided by users of a genealogical research service or collected from other sources and used to create family trees for each user. DNA samples are also received from the users. By analyzing the DNA samples, potential genetic relationships can be identified between some users. Once these DNA-suggested relationships have been identified, common ancestors can be sought in the respective trees of the potentially related users. Where these common ancestors exist, an inference is drawn that the DNA-suggested relationship accurately represents a familial overlap between the individuals in question. People descended from the same common ancestor are each members of a family network. Members of a family network not in a user's tree may be identified for the user, enabling the user to discover additional ancestors that might otherwise have remained unknown.

Abstract: A data record management system develops person match scores for data records that may relate to the same person or subject. In a genealogical system where the data records are represented as nodes in a family tree, and where multiple data records may relate the same person in question, the data record management system evaluates not only two data records to determine if they relate to the same person, but also individually evaluate various data records pertaining to people that are related to the person in question. Person match scores are calculated by combining sub-scores based on the comparison of corresponding nodes. Sub-scores for nodes pertaining to related people may be adjusted higher even if those notes do not match, to reflect circumstances such as remarriage.

Abstract: Described are techniques for determining population structure from identity-by-descent (IBD) of individuals. The techniques may be used to predict that an individual belongs to zero, one or more of a number of communities identified within an IBD network. Additional data may be used to annotate the communities with birth location, surname, and ethnicity information. In turn, these data may be used to provide to an individual a prediction of membership to zero, one or more communities, accompanied by a summary of the information annotated to those communities.

Abstract: A data record management system develops person match scores for data records that may relate to the same person or subject. In a genealogical system where the data records are represented as nodes in a family tree, and where multiple data records may relate the same person in question, the data record management system evaluates not only two data records to determine if they relate to the same person, but also individually evaluate various data records pertaining to people that are related to the person in question. Person match scores are calculated by combining sub-scores based on the comparison of corresponding nodes. Sub-scores for nodes pertaining to related people may be adjusted higher even if those notes do not match, to reflect circumstances such as remarriage.

Abstract: Identification of inheritance-by-descent haplotype matches between individuals is described. A set of tables including word match, haplotypes and segment match tables are populated. DNA samples are received and stored. A word identification module extracts haplotype values from each sample. The word match table is indexed according to the unique combination of position and haplotype. Each column represents a different sample, and each cell indicates whether that sample includes that haplotype at that position. The haplotypes table includes the raw haplotype data for each sample. The segment match table is indexed by sample identifier, and columns represent other samples. Each cell is populated to indicate for each identified sample pair which position range(s) include matching haplotypes for both samples. The tables are persistently stored in databases of the matching system. As new sample data is received, each table is updated to include the newly received samples, and additional matching takes place.

Abstract: 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.

Abstract: Systems and methods for retrieving a set of ordered items from a distributed database. A plurality of ordered items may be stored at a cache. The plurality of ordered items may have a length of N+B at a first instant in time. A first instruction to delete a first item of the plurality of ordered items may be received. A second instruction to add a second item to the plurality of ordered items may be received. The first instruction and the second instruction may be stored in a change log. A request for the first N items of the plurality of ordered items may be received. The first instruction may be executed by deleting the first item from the plurality of ordered items. The second instruction may be executed by adding the second item to the plurality of ordered items. The first N items of the plurality of ordered items may be sent in response to the request.

Abstract: Systems and methods for registering documents. A two-dimensional document image and one or more form images may be obtained. The document image may be projected onto a horizontal axis and a vertical axis to create a horizontal document projection and a vertical document projection. The form images may be projected onto the horizontal axis and the vertical axis to create a horizontal form projection and a vertical form projection. The horizontal document projection may be correlated with the horizontal form projection of the form images and the vertical document projection may be correlated with the vertical form projection of the form images. Correlation scores may be calculated based on the correlations.

Abstract: 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.

Abstract: A tree building system that accesses data from a social networking site and, in some embodiments, other data sites having information that may pertain to the relationships between users of the social networking site. A rules engine within the system implements logic for analyzing the data from the social networking site. The system provides a candidate list of possible relatives for selection by a user and solicits information from the user through the use of guided questions.

Abstract: Described are techniques for determining population structure from identity-by-descent (IBD) of individuals. The techniques may be used to predict that an individual belongs to zero, one or more of a number of communities identified within an IBD network. Additional data may be used to annotate the communities with birth location, surname, and ethnicity information. In turn, these data may be used to provide to an individual a prediction of membership to zero, one or more communities, accompanied by a summary of the information annotated to those communities.

Abstract: A handwriting recognition system converts word images on documents, such as document images of historical records, into computer searchable text. Word images (snippets) on the document are located, and have multiple word features identified. For each word image, a word feature vector is created representing multiple word features. Based on the similarity of word features (e.g., the distance between feature vectors), similar words are grouped together in clusters, and a centroid that has features most representative of words in the cluster is selected. A digitized text word is selected for each cluster based on review of a centroid in the cluster, and is assigned to all words in that cluster and is used as computer searchable text for those word images where they appear in documents. An analyst may review clusters to permit refinement of the parameters used for grouping words in clusters, including the adjustment of weights and other factors used for determining the distance between feature vectors.

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: A handwriting recognition system converts word images on documents, such as document images of historical records, into computer searchable text. Word images (snippets) on the document are located, and have multiple word features identified. For each word image, a word feature vector is created representing multiple word features. Based on the similarity of word features (e.g., the distance between feature vectors), similar words are grouped together in clusters, and a centroid that has features most representative of words in the cluster is selected. A digitized text word is selected for each cluster based on review of a centroid in the cluster, and is assigned to all words in that cluster and is used as computer searchable text for those word images where they appear in documents. An analyst may review clusters to permit refinement of the parameters used for grouping words in clusters, including the adjustment of weights and other factors used for determining the distance between feature vectors.

Abstract: A graph database system is used to determine relationships between persons. The graph database system manages relationship data records having a compact data structure stored at a relationship database and accessed to find links or common relationships. For determining relationships between two people, the relationship records in the relationship paths for those two people are alternatively accessed and compared it to each other. Relationship records may include an identifier for a person having a relationship to a given individual, a relationship type, and a weight reflecting the confidence level or quality of the relationship.

Abstract: A handwriting recognition system converts word images on documents, such as document images of historical records, into computer searchable text. Word images (snippets) on the document are located, and have multiple word features identified. For each word image, a word feature vector is created representing multiple word features. Based on the similarity of word features (e.g., the distance between feature vectors), similar words are grouped together in clusters, and a centroid that has features most representative of words in the cluster is selected. A digitized text word is selected for each cluster based on review of a centroid in the cluster, and is assigned to all words in that cluster and is used as computer searchable text for those word images where they appear in documents. An analyst may review clusters to permit refinement of the parameters used for grouping words in clusters, including the adjustment of weights and other factors used for determining the distance between feature vectors.

Abstract: A sample collection device having a sample tube, funnel, and cap having a capsule and a piercing insert, the capsule having a stabilization solution. After depositing the sample into the tube via the funnel, the cap is screwed onto the tube, piercing the capsule and releasing the stabilization fluid into the tube. The device can be used at home without clinicial supervision for collecting a saliva sample and transporting the sample to an analysis location for DNA analysis.