| No. | Publication Number | Title | Publication/Patent Number Publication/Patent Number |
Publication Date
Publication Date
|
Application Number Application Number |
Filing Date
Filing Date
|
Inventor Inventor | Assignee Assignee |
IPC
IPC
|
|||||
|
1 | US2021004672A1 |
UNARY RELATION EXTRACTION USING DISTANT SUPERVISION
|
Publication/Patent Number: US2021004672A1 | Publication Date: 2021-01-07 | Application Number: 16/502,625 | Filing Date: 2019-07-03 | Inventor： Glass, Michael Robert Gliozzo, Alfio Massimiliano | Assignee: International Business Machines Corporation | IPC: G06N3/08 | Abstract: Methods and systems are described for populating knowledge graphs. A processor can identify a set of data in a knowledge graph. The processor can identify a plurality of portions of an unannotated corpus, where a portion includes at least one entity. The processor can cluster the plurality of portions into at least one data set based on the at least one entity of the plurality of portions. The processor can train a model using the at least one data set and the set of data identified from the knowledge graph. The processor can apply the model to a set of entities in the unannotated corpus to predict unary relations associated with the set of entities. The processor can convert the predicted unary relations into a set of binary relations associated with the set of entities. The processor can add the set of binary relations to the knowledge graph. | |||
|
|
2 | US2021004311A1 |
AUTOMATED FEEDBACK-BASED APPLICATION OPTIMIZATION
|
Publication/Patent Number: US2021004311A1 | Publication Date: 2021-01-07 | Application Number: 16/460,182 | Filing Date: 2019-07-02 | Inventor： Bhide, Manish Anand Ananthapur, Bache Vijay Kumar Chebolu, Srinivas Bera, Jhilam | Assignee: International Business Machines Corporation | IPC: G06F11/36 | Abstract: Approaches presented herein enable optimization of a developing application to a user base. More specifically, application-centric data is gathered during a cultivation phase of the developing application. Substantially concurrently with the cultivation phase of the developing application, the application-centric data is analyzed according to static code of the developing application, a testing of the developing application, or a user experience (UX) design of the developing application. A machine learning model is applied to the analyzed application-centric data. This machine learning model is trained on historic application feedback data from applications available to the user base. Based on the machine learning model, a recommended change to optimize the developing application to the user base is generated. | |||
|
|
3 | US2021004160A1 |
PREFETCHING DATA BLOCKS FROM A PRIMARY STORAGE TO A SECONDARY STORAGE SYSTEM WHILE DATA IS BEING SYNCHRONIZED BETWEEN THE PRIMARY STORAGE AND SECONDARY STORAGE
|
Publication/Patent Number: US2021004160A1 | Publication Date: 2021-01-07 | Application Number: 16/460,960 | Filing Date: 2019-07-02 | Inventor： Shasha, Osnat Amit, Jonathan Mayraz, Matosevich Rivka | Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION | IPC: G06F3/06 | Abstract: Provided are a computer program product, system, and method for prefetching data blocks from a primary storage to a secondary storage system while data is being synchronized between the primary storage and secondary storage. A determination is made of data blocks to prefetch from the primary storage to the secondary controller not yet synchronized from the primary storage to the secondary storage in anticipation of future access requests for the data blocks to the secondary controller while data blocks are being synchronized between the primary storage and the secondary storage over the network. A prefetch command is sent to prefetch the determined data blocks to copy from the primary storage to the secondary controller to make available to future access requests received at the secondary controller for the determined data blocks. | |||
|
|
4 | US10884886B2 |
Copy-on-read process in disaster recovery
|
Publication/Patent Number: US10884886B2 | Publication Date: 2021-01-05 | Application Number: 16/169,905 | Filing Date: 2018-10-24 | Inventor： Wilkinson, John P. | Assignee: International Business Machines Corporation | IPC: G06F11/20 | Abstract: Inventive systems, techniques, and program products for copy-on-read, particularly in the context of disaster recovery (DR), are described. The inventive concepts include: a primary system for copy-on-read processing and disaster recovery, the primary system comprising: a primary storage volume available at a primary system, the primary storage volume storing one or more data portions; a record of regions of the primary storage volume, wherein a given region of the primary storage volume is marked when a given data portion stored on the primary storage volume is sent to a disaster recovery system; and a record monitoring component configured to determine whether one or more later writes to marked region(s) of the primary storage volume should be immediately replicated to the disaster recovery system, wherein the later writes occur after replicating the given data portion stored on the primary storage volume to the disaster recovery system. | |||
|
|
5 | US10884899B2 |
Optimized trampoline design for fast software tracing
|
Publication/Patent Number: US10884899B2 | Publication Date: 2021-01-05 | Application Number: 16/148,126 | Filing Date: 2018-10-01 | Inventor： Rao, Naveen N. Mavinakayanahalli, Ananth N. | Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION | IPC: G06F11/36 | Abstract: Tracing computer software program execution includes copying a software instruction at an instrumentation point within an original instruction stream, and replacing the software instruction with a jump instruction. The jump instruction branches to a multi-level trampoline that includes at least a first-level trampoline specific to an associated software tracing probe, and a second-level trampoline generic to plural software tracing probes. The first-level trampoline preserves partial CPU state and branches to the second-level trampoline, passing it software tracing probe identifying information. The second-level trampoline preserves a remainder of the CPU state, implements software tracing operations in accordance with the software tracing probe, restores the CPU state that it previously preserved, and returns program control to the first-level trampoline. Either the first-level or second-level trampoline may execute or emulate the original instruction. The first-level trampoline restores the CPU state that it previously preserved, and returns program control to the original instruction stream. | |||
|
|
6 | US10884864B2 |
Autonomous self-healing stateless microservice nodes
|
Publication/Patent Number: US10884864B2 | Publication Date: 2021-01-05 | Application Number: 16/204,609 | Filing Date: 2018-11-29 | Inventor： Treadway, Michael | Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION | IPC: G06F11/14 | Abstract: A computer-implemented method includes: randomly generating, by a process running on a computer device, a reset time for the process; broadcasting a message to other processes in a cluster, the message including the reset time; entering a running state; receiving another message from one of the processes, the other message including another reset time; comparing the other reset time to the reset time; and in response to the comparing, the process performs one of: continuing in the running state based on the other reset time being different than the reset time; and randomly generating a new reset time for the process based on the other reset time coinciding with the reset time. | |||
|
|
7 | US10887378B2 |
Software-defined networking single-source enterprise workload manager
|
Publication/Patent Number: US10887378B2 | Publication Date: 2021-01-05 | Application Number: 16/559,848 | Filing Date: 2019-09-04 | Inventor： Decusatis, Casimer M. Krishnamurthy, Rajaram B. | Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION | IPC: H04L29/08 | Abstract: Embodiments relate to a software-defined networking (SDN) single-source enterprise workload manager. An aspect includes analyzing, by an enterprise server executing a workload compiler, a plurality of source code files of a workload during a workload compilation and build process to determine enterprise network connections between a plurality of subprograms of the workload as a plurality of compile-time information of the workload. The workload compiler generates a network flow graph as interactions between the subprograms of the workload in the enterprise network responsive to the compile-time information of the workload. The network flow graph is provided to an SDN controller to make network resource allocations for the workload based on the network flow graph. A workload manager of the enterprise server adjusts an allocation of compute resources based on a notification of a reallocation of network resources made by the SDN controller. | |||
|
|
8 | US10887293B2 |
Key identifiers in an obliviousness pseudorandom function (OPRF)-based key management service (KMS)
|
Publication/Patent Number: US10887293B2 | Publication Date: 2021-01-05 | Application Number: 15/926,883 | Filing Date: 2018-03-20 | Inventor： Resch, Jason K. Krawczyk, Hugo M. Seaborn, Mark D. Nagaratnam, Nataraj Lo, Erlander | Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION | IPC: H04L29/00 | Abstract: A computing device includes an interface configured to interface and communicate with a communication system, a memory that stores operational instructions, and processing circuitry operably coupled to the interface and to the memory that is configured to execute the operational instructions to perform various operations. The computing device generates a sub-key identifier based on a data ID, which is based on unique ID value(s) associated with an encrypted data object, and a requester secret. The computing device processes the sub-key identifier in accordance with an Oblivious Pseudorandom Function (OPRF) blinding operation to generate a blinded input and an Oblivious Key Access Request (OKAR). The computing device transmits the OKAR to another computing device (e.g., Key Management System (KMS) service) and receives a blinded sub-key therefrom. The computing device processes the blinded sub-key in accordance with an OPRF unblinding operation to generate the key and accesses secure data thereby. | |||
|
|
9 | US10884998B2 |
Method for migrating data records from a source database to a target database
|
Publication/Patent Number: US10884998B2 | Publication Date: 2021-01-05 | Application Number: 16/131,101 | Filing Date: 2018-09-14 | Inventor： Gruszecki, Artur M. Sekman, Tomasz Kazalski, Tomasz Wrobel, Andrzej J. | Assignee: International Business Machines Corporation | IPC: G06F16/27 | Abstract: The present disclosure relates to a method using a database engine for migrating data records from a source database to a target database, where said data records are arranged in a sorted source table of the source database in accordance with a clustered-base-table order following the Hilbert-Filling-Curve algorithm. The method comprises configuring the database engine for storing the CBT order of each data record of the source table in a reference table to said source table or a in a column of said source table. A reading step may be performed to read said data records from said source table, wherein in said reading step said stored CBT order is used. The read data and the stored CBT order may be transferred to the target database in accordance with the stored CBT order. The transferred data may be written at the target database in accordance with the CBT order. | |||
|
|
10 | US10884709B2 |
Generating an application programming interface by analyzing source code metadata
|
Publication/Patent Number: US10884709B2 | Publication Date: 2021-01-05 | Application Number: 16/025,061 | Filing Date: 2018-07-02 | Inventor： Hogan, Seana | Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION | IPC: G06F8/30 | Abstract: A computer-implemented method for generating an application programming interface (API) includes receiving metadata describing one or more source files of a program. The source files define a plurality of modules, and a first module is selected from among the plurality of modules. A chain of modules is traversed beginning at the first module, based on the metadata, where the chain of modules represents nested module calls described in the metadata. The traversing includes maintaining a set of common include files that are common to each module visited in the traversal of the chain of modules. Each include file in the set of common include files is placed into at least one of a request file list and a response file list. An API is generated for the module by submitting the set of common include files, the request file list, and the response file list to an API generator. | |||
|
|
11 | US2021005749A1 |
TRANSISTOR GATE HAVING TAPERED SEGMENTS POSITIONED ABOVE THE FIN CHANNEL
|
Publication/Patent Number: US2021005749A1 | Publication Date: 2021-01-07 | Application Number: 16/458,708 | Filing Date: 2019-07-01 | Inventor： Miller, Eric Karve, Gauri Bergendahl, Marc A. Lie, Fee Li Cheng, Kangguo Teehan, Sean | Assignee: International Business Machines Corporation | IPC: H01L29/78 | Abstract: Embodiments of the invention are directed to a method that includes forming a fin over a major surface of a substrate. The fin includes an active fin region having a top fin surface and a fin sidewall. The top fin surface is substantially parallel with respect to the major surface, and the fin sidewall is substantially perpendicular with respect to the major surface. A gate is formed over and around a central portion of the fin, the gate having a bottom gate region and a top gate region. The bottom gate region is substantially below the top fin surface and includes a bottom gate region sidewall that is substantially parallel with respect to the fin sidewall. The top gate region is substantially above the top fin surface and includes a top gate region sidewall that is at an angle with respect to the major surface. | |||
|
|
12 | US2021005328A1 |
Expectedness Cognitive Service for Pharmacovigilence
|
Publication/Patent Number: US2021005328A1 | Publication Date: 2021-01-07 | Application Number: 16/458,450 | Filing Date: 2019-07-01 | Inventor： Kelgere, Ramesh Abhinandan Routray, Ramani Abu-assal, Claire Bao, Sheng Hua | Assignee: International Business Machines Corporation | IPC: G16H70/40 | Abstract: A mechanism is provided in a data processing system comprising a processor and a memory, the memory comprising instructions that are executed by the processor to specifically configure the processor to implement an expectedness cognitive service for identifying seriousness of a patient case. The expectedness cognitive service receives a patient case and identifies a suspect drug, an adverse event, and context features based on the patient case. An expectedness binary classifier within the expectedness cognitive service determines a plurality of expectedness classifications for the adverse event with respect to a plurality of drug labeling service repositories. The expectedness cognitive service generates and outputs an expectedness classification output comprising the plurality of expectedness classifications. | |||
|
|
13 | US10884946B2 |
Memory state indicator check operations
|
Publication/Patent Number: US10884946B2 | Publication Date: 2021-01-05 | Application Number: 14/854,240 | Filing Date: 2015-09-15 | Inventor： Mak, Pak-kin Slegel, Timothy J. Walters, Craig R. Webb, Charles F. | Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION | IPC: G06F12/1009 | Abstract: Aspects include a computer-implemented method that includes receiving an instruction at a processor to perform an operation on a memory block having an address and accessing a state indicator by the processor without altering a value of the state indicator. The state indicator is stored in a memory location independent of the memory block, and accessing includes sending a request to an operator to return the value of the state indicator to the processor. The method also includes determining based on the value of the state indicator whether the memory block is in a pre-defined state. | |||
|
|
14 | US2021004421A1 |
PERSONALIZED RECOMMENDER WITH LIMITED DATA AVAILABILITY
|
Publication/Patent Number: US2021004421A1 | Publication Date: 2021-01-07 | Application Number: 16/502,048 | Filing Date: 2019-07-03 | Inventor： Zadorojniy, Alexander Voldman, Sergey Mashkif, Nir | Assignee: International Business Machines Corporation | IPC: G06F16/9535 | Abstract: In some examples, a system for generating personalized recommendation includes a processor that can perform an initial training for a deep reinforcement learning (DRL) model using domain knowledge, available users data, and an items list. The processor also inputs users data and an items list to the trained DRL model to generate an initial list of recommended items. The processor also inputs the initial list of recommended items and a user profile to a content-based filter to generate a final list of recommendations for a target user. | |||
|
|
15 | US10886364B2 |
Vertical memory cell with mechanical structural reinforcement
|
Publication/Patent Number: US10886364B2 | Publication Date: 2021-01-05 | Application Number: 15/889,514 | Filing Date: 2018-02-06 | Inventor： Yang, Adam Lee, Choong Ho Mataev, Elnatan Fry, Jonathan Lin, Cheng-yi Biyani, Bharat Sim, Jang | Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION | IPC: H01L29/06 | Abstract: A reinforced vertical-NAND structure is provided. The reinforced vertical-NAND structure includes a first set of interleaved oxide and nitride layers formed into first and second vertical structures. The first vertical structure rises from a first section of a substrate and the second vertical structure rises from a second section of the substrate. The reinforced vertical-NAND structure also includes a reinforcing layer and a second set of interleaved oxide and nitride layers formed into third and fourth vertical structures. The reinforcing layer includes sheets, which are distinct and laid across respective tops of the first and second vertical structures, and bridges connecting the sheets. The third vertical structure rises from the sheet corresponding to the first vertical structure and the fourth vertical structure rises from the sheet corresponding to the second vertical structure. | |||
|
|
16 | US10886254B2 |
Flip-chip electronic device with carrier having heat dissipation elements free of solder mask
|
Publication/Patent Number: US10886254B2 | Publication Date: 2021-01-05 | Application Number: 16/145,321 | Filing Date: 2018-09-28 | Inventor： Oggioni, Stefano Brunschwiler, Thomas Schlottig, Gerd | Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION | IPC: H01L25/065 | Abstract: A solution relating to electronic devices of flip-chip type is provided, which includes at least one chip carrier having a carrier surface, the carrier(s) including one or more contact elements of electrically conductive material on the carrier surface, at least one integrated circuit chip having a chip surface, the chip(s) including one or more terminals of electrically conductive material on the chip surface each one facing a corresponding contact element, solder material soldering each terminal to the corresponding contact element, and a restrain structure around the contact elements for restraining the solder material during a soldering of the terminals to the contact elements. The carrier includes one or more heat dissipation elements of thermally conductive material on the carrier surface facing the chip surface displaced from the terminals, the dissipation elements being free of any solder mask. | |||
|
|
17 | US10885065B2 |
Data convergence
|
Publication/Patent Number: US10885065B2 | Publication Date: 2021-01-05 | Application Number: 15/725,623 | Filing Date: 2017-10-05 | Inventor： Dunne, Jonathan Forde, Karen Holmes, William Penrose, Andrew | Assignee: International Business Machines Corporation | IPC: G06F16/00 | Abstract: Embodiment for identifying data convergence are presented. First and second sets of data each comprising heterogeneous data are each processed in accordance with a data clustering algorithm so as to obtain a plurality of primary and secondary data clusters, respectively, where each data cluster comprising homogeneous data. The primary and secondary data clusters are analyzed with respect to time to identify convergence of data of the first and second sets of data to first and second topics, respectively. The first and second topics are compared to determine a pattern of data convergence for the first and second data sets. | |||
|
|
18 | US10885033B2 |
Query plan management associated with a shared pool of configurable computing resources
|
Publication/Patent Number: US10885033B2 | Publication Date: 2021-01-05 | Application Number: 16/243,640 | Filing Date: 2019-01-09 | Inventor： Konik, Rafal P. Mittelstadt, Roger A. Muras, Brian R. | Assignee: International Business Machines Corporation | IPC: G06F16/00 | Abstract: Disclosed aspects relate to query plan management associated with a shared pool of configurable computing resources. A query, which relates to a set of data located on the shared pool of configurable computing resources, is detected. A virtual machine includes the set of data. With respect to the virtual machine, a set of burden values of performing a set of asset actions is determined. Based on the set of burden values, a query plan to access the set of data is established. Using at least one asset action of the set of asset actions, the query plan is processed. | |||
|
|
19 | US10885332B2 |
Data labeling for deep-learning models
|
Publication/Patent Number: US10885332B2 | Publication Date: 2021-01-05 | Application Number: 16/354,352 | Filing Date: 2019-03-15 | Inventor： Bigaj, Rafal Cmielowski, Lukasz G. Oszajec, Marek Erazmus, Maksymilian | Assignee: International Business Machines Corporation | IPC: G06K9/62 | Abstract: A first and second scoring endpoint with payload logging are deployed. At the second scoring endpoint, native data and a user-generated score for the native data are received, the native data is pre-processed into readable data for the deep-learning model, and the user-generated score and the readable data are output to the first scoring endpoint, which is associated directly with the deep-learning model. A raw payload that includes the native data is output to a payload store. At the first scoring endpoint, the readable data and the user-generated score are processed by the deep-learning model, which outputs a transformed payload and a prediction, respectively, to the payload store. The raw payload is matched with the transformed payload and the prediction to produce a comprehensive data set, which is evaluated to describe a set of transformation parameters. The deep-learning model is retrained to account for the set of transformation parameters. | |||
|
|
20 | US10885029B2 |
Parallel execution of merge operations
|
Publication/Patent Number: US10885029B2 | Publication Date: 2021-01-05 | Application Number: 16/195,903 | Filing Date: 2018-11-20 | Inventor： Li, Shuo Liang, Ping Sun, Bing Qing Wang, Xiaobo Yang, Xin Ying | Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION | IPC: G06F16/22 | Abstract: Aspects include a method that includes receiving a structured query language (SQL) database command at a processing device configured to manage a table space of a relational database, the database command including a merge statement. The method also includes identifying a group of target records from the database command, and associating each target record with one of a plurality of portions of the table space, and in response to determining that the group of target records is associated with more than one portion of the table space, sorting the target records into a plurality of sub-groups, each sub-group associated with a different portion of the table space. The method further includes generating a sub-task associated with each sub-group, the sub-task prescribing aspects of performing the merge operation using an associated sub-group respective sub-group, and performing all of the sub-tasks on the memory space in parallel. |
3.Current Quota