Merck Sharp + Dohme Corp.

David B Hurry

David J Tabacco

Stephen Charles North

An indexing system indexes data entries in a database and processes queries of the database. The indexing system generates a key database storing keys that each represent a vector of a relative attribute between two data entries. For instance, a temporal distance indicates a relative time between timestamps of events represented by the two data entries. In other embodiments, relative attributes may be based on physical proximity, altitude, semantics, etc. The indexing system may also generate a key space database to enable efficient lookup of events associated with a target entity for indexing new data entries. For example, the indexing system may perform one read operation using the key space database to lookup all events associated with the target entity. Furthermore, the indexing system may determine responses for queries to retrieve events that occurred within a target temporal distance before or after a target type of event.

Database indexing and processing

A web detection system processes webpage information and performs automated feature extraction of webpages including machine processable information. In an embodiment, the web detection system determines a subset of webpages having a target characteristic by processing markup language. For a webpage of the subset, the web detection system determines that a first image overlaps at least a portion of a second image in the webpage. The web detection system generates an image of the webpage such that the portion of the second image is obscured by the first image. The web detection system determines a graphical feature of the webpage by processing the image, e.g., using optical character recognition. Responsive to determining that the graphical feature corresponds to graphical features of images of a different set of webpages associated with a target entity, the web detection system determines that the webpage is also associated with the target entity.

Image processing of webpages

A security system determines authorizations for entities to access data objects. The security system may train an adaptive model to predict the intent of a user who provides authorization for various entities or other users. In an embodiment, the adaptive model may be configured to determine latent properties of training data by identifying common parameters between entities that are, or are not, permitted to access given data object(s). The training data may include previous authorizations provided to the entities. Based on the identified common parameters, the model may generate usage expressions for determining a likelihood that the user intends to provide authorization for a given entity to access the given data object. If the likelihood is greater than a threshold value, the security system may provide a recommendation to the user to provide the authorization for the given entity.

Adaptive model for database security and processing

Large data sets (e.g., with millions of records) are represented by a heat map within a user interface (UI). Each record in the data set includes a label. The labels of the records are assigned to leaf nodes of a data structure. The leaf nodes are mapped to a grid of cells according to a layout method. Furthermore, values are determined for the cells based on data records having the labels mapped to the cells. A visual property is selected for each cell based on the corresponding value. Since the data labels are stored in leaf nodes that are connected to internal nodes, if a zoom state of the heat map results in a display of a number of data labels that exceeds the number of cells in the grid, values of the cells can be updated according to values determined from the internal nodes without losing the connections between the cells and the underlying leaf nodes.

Displaying large data sets in a heat map

An indexing system uses a cascade of hash structures to process data entries upon ingest for indexing. The indexing system may be used for enhancing database privacy, anonymization, or data compression. A hash structure, for example, a bloom filter or hash table, passes a representation of the data entries to a subsequent hash structure in the cascade responsive to determining that the hash structure previously filtered an instance of the same representation. The indexing system can generate the representations of the data entries using one or more hash functions. A terminal hash structure of the cascade may index the data entries responsive to determining that the data entries satisfy a criteria for anonymization. For instance, the indexing system determines that there exists a threshold number of data entries describing a population of subjects having the same combination of data elements.

Growing community of inventors

Mount Airy, MD, United States of America

David B Hurry