Abstract: This application describes a hardware accelerator, a computer system, and a method for accelerating Graph Neural Network (GNN) node attribute fetching. The hardware accelerator comprises a GNN attribute processor; and a first memory, wherein the GNN attribute processor is configured to: receive a graph node identifier; determine a target memory address within the first memory based on the graph node identifier; determine, based on the received graph node identifier, whether attribute data corresponding to the received graph node identifier is cached in the first memory at the target memory address; and in response to determining that the attribute data is not cached in the first memory: fetch the attribute data from a second memory, and write the fetched attribute data into the first memory at the target memory address.

Abstract: Systems and methods for assisting a user in discovering nearby medical services are disclosed. A method includes identifying a user based on matching of at least one unique identity or biometric details of the user with data stored in a database. Details of an event data may be received from the user. A current geographical location of the user may be determined. Relevant support network data may be identified based on the event data and the current geographical location of the user. The support network data may include data related to pharmacies, doctors, hospitals, clinics, third parties, insurance, and payment agents. Thereafter, the relevant support network data may be presented to the user in form of an event map. The event map may include details related to the event data and the user preferences.

Abstract: A method for classifying multi-granularity breast cancer genes based on a double self-adaptive neighborhood radius includes large-scale gene locus data are read and normalized, and a data analysis is performed on the large-scale gene loci. An optimum value K is selected by adopting a combination of contour coefficients and a PCA dimensionality reduction visualization, and a model of information granulation is adjusted. A heuristic reduction algorithm is used to implement a multi-granularity attribute reduction of a self-adaptive neighborhood radius based on a cluster center distance and a multi-granularity attribute reduction of a neighborhood radius based on an attribute inclusion degree, and big data for breast cancer genes are classified and predicted by adopting a machine learning classification algorithm based on a SVM support vector machine.

Abstract: A system for tracking and representing data science model runs includes a hub including a first computing device communicatively coupled with a data store. A runner including a second computing device having a cache is communicatively coupled with the hub through a telecommunications network. An end user computing device includes a display and is communicatively coupled with the runner and the hub. User interfaces displayed on the display include: a unique identifier identifying a data science model run performed by the runner; a list of input files used by the runner to perform the run; a list of output files output by the runner as a result of the run; and a diagram diagramming a process flow including a visual representation of the input files, a visual representation of the run, and a visual representation of the output files.

Abstract: Systems and methods for cloud object storage and versioning are provided. In an example, a cloud object storage and versioning system (COSVS) coordinates insertion of metadata into a database and data into an object store in a compute infrastructure, the compute infrastructure including the database, the object store, a data source, and a client application interacting with the data source. The COSVS has an architecture comprising a client API layer confined to provide an interface to the client application to facilitate storing or restoring of items originally obtained from the data source, and query different versions of item content originally obtained from the data source; a deduplication layer to deduplicate item content and store items originally obtained from the data source devoid of external item metadata or semantic relations among items; and a packing layer confined to store and retrieve bytes of item or object content.

Abstract: Example embodiments relate to integrated circuits with 3D partitioning. One embodiment includes an integrated circuit. The integrated circuit includes a first integrated circuit layer that includes processing cores. The integrated circuit also includes a second integrated circuit layer that includes memory arrays associated with processing cores. Additionally, the integrated circuit includes an intermediate integrated circuit layer interconnected with the first and second integrated circuit layers and including memory control logic and interface circuitries for managing data exchange between the processing cores and the memory arrays.

Abstract: Automated assistant responses may be assembled and/or evaluated to address privacy concerns. In various implementations, a free-form natural language input may be received from a first user and may include a request for information pertaining to a second user. Multiple data sources may be identified that are accessible by an automated assistant to retrieve data associated with the second user. The multiple data sources may collectively include sufficient data to formulate a natural language response to the request. Respective privacy scores associated with the multiple data sources may be used to determine an aggregate privacy score associated with responding to the request. The natural language response may then be output at a client device operated by the first user in response to a determination that the aggregate privacy score associated with the natural language response satisfies a privacy criterion established for the second user with respect to the first user.

Abstract: Methods, systems and computer-program products are directed to a Privacy Engine for evaluating initial electronic documents to identify document content categories for portions of content within the electronic documents, with respect to extracted document structures and document positions, that may include privacy information for possible redaction via visual modification. The Privacy Engine builds a content profile based on detecting information at respective portions of electronic document content that indicate one or more pre-defined categories and/or sub-categories. For each respective portion of electronic document content, the Privacy Engine applies a machine learning model that corresponds with the indicated category (or categories and sub-categories) to determine a probability value of whether the respective portion of content includes data considered likely to be privacy information.

Abstract: The technology disclosed herein involves tracking contention and using the tracked contention to manage processor cache. The technology can be implemented in a processor's cache controlling logic and can enable the processor to track which locations in main memory are contentious. The technology can use the contentiousness of locations to determine where to store the data in cache and how to allocate and evict cache lines in the cache. In one example, the technology can store the data in a shared cache when the location is contentious and can bypass the shared cache and store the data in the private cache when the location is uncontentious. This may be advantageous because storing the data in shared cache can reduce or avoid having multiple copies in different private caches and can reduce the cache coherency overhead involved to keep copies in the private caches in sync.

Abstract: A method of displaying web pages, capable of using the same settings for all web pages, is provided. The method includes receiving a user request for opening a web page; selecting, from among a plurality of views, a view in which the web page is to be opened, based on metadata corresponding to the web page, wherein each view of the plurality of views has a corresponding set of viewing properties; and displaying the web page in a browser window based on the corresponding set of viewing properties of the selected view.

Abstract: A digital communications or content platform is provided on a desktop and mobile platform that is configured to provide a useful tool for generating visualizations or other user content that is operable to create a layer or skin that acts as a pane of glass over original web content. The digital communications or content platform is configured to maintain, in a data structure, a set of data linkages representative of a set of visual components whose visual locations and website locations are dynamically maintained despite changes to the underlying webpage. The digital communications or content platform is configured to cause a display to render a hybrid webpage including both the underlying webpage and the overlay.

Abstract: A storage system receives data to be stored in its memory. A controller in the storage system allocates a primary block of the memory to store the data and determines the health of the allocated block. If the controller determines that the allocated block is not healthy enough to reliably store the data, the controller allocates a secondary block to redundantly store the data.

Abstract: A user interface (UI) enhancement system modifies a computer user interface based on user interactions recorded over time. The UI enhancement system records user interactions and develops a corresponding heat map. The heat map represents frequencies of user actions such as links clicked, scrolling actions, buttons selected, jumps within a page, etc. Based on the heat map, the UI enhancement system modifies a user interface configuration file which in turn influences the appearance and/or behavior of elements within the user interface to improve the user experience. Some embodiments give greater prominence to a UI element associated with greater “heat” and less prominence to an element with less “heat”.

Abstract: Systems and techniques may be used for providing website change detection. An example technique may include processing snapshots of a website, for example on a first day and a second day to produce a set of features of the website. The technique may include comparing at least one of the set of features from the first day to at least one of the set of features from the second day, for example using a distance function. A change score may be determined, the change score corresponding to at least one of a deleted feature, an added feature, or an unchanged feature of the website from the first day to the second day. The technique may include outputting the change score (e.g., for display).

Abstract: Users of a database management engine may generate fillable digital documents by mapping interface elements onto form documents. When a user maps interface elements onto a form document, the user may accidentally overlap two or more interface elements. To rectify this, the database management engine may modify the position of one of interface elements based on a set of positioning rules. In addition, the database management engine may identify and suggest mappings to users based on similar documents that have been previously mapped. The database management engine identifies similar documents using information about the document, the user, and the mapping itself. The mapping associated with the most similar document may be provided to the user as a suggested mapping. The database management engine converts the form document and finalized mapping into a fillable digital document. The fillable digital document is sent to recipients, who complete the fillable digital document.

Abstract: Provided is a process, including: obtaining a first training dataset, training a first machine-learning model on the first training dataset, obtaining a set of candidate question sequences, forming virtual subject-entity records, forming a second training dataset, training a second machine-learning model, and storing the adjusted parameters of the second machine-learning model in memory.

Abstract: Methods, systems, and computer-readable media for generating a personalized action recommendation are provided. The method acquires a request for a service that is associated with a user and the user's condition. The method then identifies one or more features of the user based on stored user information. The method next assigns the user to a segment based on the identified one or more features, generates a set of one or more recommended actions for the user based on the segment, and determines an expected value of each of the one or more recommended actions. The method determines a rank of the one or more recommended actions based on the expected value of each of the one or more recommended actions, and outputs a recommended action with a highest expected value for the user in response to the request for the service.

Abstract: A system and method are provided for automatically proofing the patent specification of a granted patent issued on a patent application. The method comprises the steps of scanning amendments made to the patent application during prosecution; assembling the most recent claims, based on the scanned amendments, to create a test claim set of the claims; comparing the test claim set to the claims of the issued patent as published; and identifying any differences between the compared sets of claims and communicating the differences to a user.

Abstract: A system enables tracking machine learning (“ML”) model data provenance. In particular, a computing device is configured to accept ML model code that, when executed, instantiates and trains an ML model, to parse the ML model code into a workflow intermediate representation (WIR), to semantically annotate the WIR to provide an annotated WIR, and to identify, based on the annotated WIR and ML API corresponding to the ML model code, data from at least one data source that is relied upon by the ML model code when training the ML model. A WIR may be generated from an abstract syntax tree (AST) based on the ML model code, generating provenance relationships (PRs) based at least in part on relationships between nodes of the AST, wherein a PR comprises one or more input variables, an operation, a caller, and one or more output variables.

Abstract: Systems and methods for conducting automated synthetic interactions with a user, such as a patient at home following a medical procedure. A digital coach having a processor and memory initiates a session with a user's interactive device, and presents pre-recorded scripts as video and/or audio through the interactive device. The user's responses are received by the digital coach through the interactive device. Peripheral devices, such as medical devices, may be used by the user or controlled by the digital coach to obtain data measurements regarding the physiological condition of the user. The processor of the digital coach analyzes the data from the user responses and devices, and semantically interprets the responses and data to determine the next action and script to present the user in the session. The digital coach provides a conversational, dynamic, adaptive session with a user based on semantically expanded interpretations of data by the processor.