Abstract: Embodiments relate to a system, program product, and method for use with an intelligent computer platform to create and apply textual data in vector format, and more specifically to apply context to the vector representation. Both context and document vectors are generated and assessed, with a calculated distance between the vectors corresponding to a weight. Word vectors are generated with associated word pairs and frequencies. A word vector generation model is trained. Utilization of the trained model generates one or more context sensitive word vector representations. A summarized sentence document is created and returned through application of the context sensitive word vectors.

Abstract: In one example, the present disclosure describes a device, computer-readable medium, and method for sentiment analysis tuning. In one example, the method, includes acquiring a first sentiment analysis-generated score for a first string of text, wherein the first string of text includes a first plurality of words, and wherein the first sentiment analysis-generated score is calculated using a set of first values associated with the first plurality of words, calculating a second value for at least one word of the first plurality of words, based on a non-sentiment-analysis generated score associated with the first string of text, acquiring a second string of text, wherein the second string of text includes a second plurality of words, and wherein the second plurality of words includes the at least one word, and calculating a sentiment analysis-generated score for the second string of text, using the second value for the at least one word.

Abstract: Techniques for predicting sentiment from textual data are described herein. In some examples, the described techniques utilize a sentiment prediction model having bidirectional long short-term memory (LSTM) networks with one or more convolution-and-pooling stages. The bidirectional LSTM networks process vector representations of words in a textual word sequence to determine forward and backward word-level context feature vectors. Forward and backward phrase-level feature vectors are determined based on the forward and backward word-level context feature vectors. The one or more convolution-and-pooling stages pool the forward and backward phrase-level feature vectors to determine pooled phrase-level feature vectors. A sentiment representing the textual word sequence is determined based on the pooled phrase-level feature vectors.

Abstract: Systems and methods for analyzing a large number of textual passages are described. A computing device receives the textual passages as input and generates a Raw Pair Distance (RPD) table. The device then determines a Node table and an Node-Node Distance (NND) matrix from the RPD table. An energy reduction process is used to generate an NSPACE matrix from the NND matrix. Finally, a 3D visualizer displays aspects of the Nodes table and the NSPACE matrix to a user. The systems and methods may enable a user to quickly search and understand the text relationships within the large number of textual passages.

Abstract: Presented herein are embodiments of a prefix-to-prefix framework for simultaneous translation that implicitly learns to anticipates in a single translation. Within these frameworks are effective “wait-k” policy model embodiments that may be trained to generate a target sentence concurrently with a source sentence but lag behind by a predefined number of words. Embodiments of the prefix-to-prefix framework achieve low latency and better quality when compared to full-sentence translation in four directions: Chinese?English and German?English. Also presented herein is a novel latency metric that addresses deficiencies of previous latency metrics.

Abstract: The present disclosure provides a translation processing method, a translation processing device, and a device. The first speech signal of the first language is obtained, and the speech feature vector of the first speech signal is extracted based on the preset algorithm. Further, the speech feature vector is input into the pre-trained end-to-end translation model for conversion from the first language speech to the second language text for processing, and the text information of the second language corresponding to the first speech signal is obtained. Moreover, speech synthesis is performed on the text information of the second language, and the corresponding second speech signal is obtained and played.

Abstract: The present invention relates to a braille editing method using an error output function, a recording medium storing program for executing the same, and a computer program stored in a recoding medium for executing the same. More particularly, the present invention relates to a braille editing method using an error output function, a recording medium storing program for executing the same, and a computer program stored in a recoding medium for executing the same, that are capable of finding a location where a braille translation error has occurred by utilizing index information when detecting the error and thus facilitating correction.

Abstract: There is provided an electronic device including a display, a designation device configured to designate any range of a character string displayed on the display by a user, and a processor. The processor is configured to target as a processing target at least one character included in the range designated by the designation device, determine to which of a plurality of predetermined combinations a combination of a character type of the at least one character and a position of the at least one character in the range corresponds, and execute a process on characters included in the designated range based on the determined combination.

Abstract: Embodiments include systems and methods for performing data migration using source database classification. Information about source databases can be received from a source system, including source hardware types and processor information for the source databases. Each of the source databases can be classified to one of a plurality of predetermined database sizes based on the received information. The source system can be interrogated to derive information about the source databases, such as a processor utilization per database. Characteristics of the classified database sizes can be adjusted based on the derived information and resource requirements at a target system for the classified source databases can be determined. A shape for the target databases can be generated based on the resource requirements, the shape including target databases of predetermined database sizes implemented by target hardware, where the target databases are configured to receive migration data from the source databases.

Abstract: Embodiments include systems and methods for performing data migration using database consolidation. Information and parameters about a plurality of source databases from a source system can be stored, the parameters including a location, a security zone, and processor information for the source databases. Each of the plurality of source databases can be classified to one of a plurality of predetermined database sizes based on the stored information and parameters, wherein the classifying is at least based on the processor information. The classified source databases can be mapped to target database hardware based on the classified sizes and the stored parameters, wherein the target database hardware is segmented into containers that are defined by one or more of the parameters. Data from the source databases can be migrated to the target database hardware based on the mappings.

Abstract: Embodiments include systems and methods for performing rules based scheduling and migration of databases based on complexity and weight. Information about source databases from a source system can be stored, the stored information including storage capacity information and downtime information for the source databases. Each of the source databases can be classified to one of a plurality of predetermined migration complexities based on the storage capacity information and downtime information. Scheduling weights can be assigned to each class of complexity. A migration schedule can be generated that defines periods of time for migrating data from the source databases, where a rules based scheduling engine generates the migration schedule based on the classified source databases and the assigned scheduling weights, the rules defining a weight criteria for the periods of time. Data can be migrated from the source databases to target databases according to the migration schedule.

Abstract: Systems and methods are described for providing an implementation of the MapReduce programming model utilizing tasks executing on an on-demand code execution system, utilizing a stream data processing system as an intermediary between map and reduce function. A map task implementing a map function can process portions of a data set, to generate outputs associated with different values for a measured attribute of the data set. Executions of the map task can publish outputs to a data stream on the stream data processing system, which stream is configured to utilize the measured attribute as a partition key for the stream. Based on the partition key, the stream data processing system can divide the stream into sub-streams, each containing a relevant subset of the outputs. The on-demand code execution system can execute a reduce task to apply the reduce function to the outputs of each sub-stream, thereby completing the MapReduce process.

Abstract: A method and system for tagging database columns are presented. The method includes receiving an input column name of at least one column in a database; performing signature matching of the input column name to contents of a seed table; determining a first confidence score for the signature matching; and tagging a matching value in the seed table as a tag for the input column name, when a first confidence score exceeds a first threshold value.

Abstract: A bias compensation method, system, and computer program product include modifying a behavior of a first analytic engine service with a second analytic engine service, where the first service accepts user submitted data and communicates an assessment of the data in a form of a label associated with the corresponding submitted data, where the second service accepts an input and communicates an assessment in a form of a label associated with the corresponding input, and where a behavior model of the first service and the second service includes a discrepancy between the output labels by each service with respect to true labels of data accepted, further including composing a new analytic engine service from the first service and the second service to optimize a service bias in terms of a test dataset based on the behavior model and the known true assessments.

Abstract: An event system comprises an admin application, a producer application, a micro-site, an embedded version of the micro-site, a database, and a portal. Templates are used to generate a micro-site for an event. The event is promoting a product on the micro-site according to a schedule. The micro-site is accessible via another website during the scheduled time. The admin application is configured to receive an order for the product. A portal configured to receive information about the order for the product and transmit the information for fulfilment. The database is configured to store the schedule and the information about the order. The producer application is configured to receive, from the admin application, micro-site and embedded version views, stock allocations and sales data of the product being promoted while the event is running.

Abstract: Methods of providing data to a user including receiving a page request from the user for a database to provide a sub-set of data from a dataset. The method further including sending a publish request from the database to a publisher, publishing the dataset from the publisher to the database, preparing the sub-set of data in the page request in the database, and sending the sub-set of data in the page request to the user.

Abstract: The disclosed embodiments provide a system that uses A/B testing to safely terminate unused experiments. During operation, the system determines a first A/B test that matches one or more criteria for removal from an A/B testing platform. Next, the system initiates a first ramp-down of the first A/B test to observe an effect of a control variant on a performance metric for the first A/B test. When the effect includes a change in the performance metric, the system automatically removes code blocks that use the first A/B test on the A/B testing platform and terminates the first A/B test.

Abstract: Systems and methods for issuing continuous trim commands for a memory system, including periodically sending trim commands to an electronically erasable memory device. Each of the trim commands identifies unused blocks of a portion of a total storage capacity of the electronically erasable memory device to erase.

Abstract: According to one embodiment, a computer program product for managing contention includes a computer readable storage medium that has program instructions embodied therewith, where the computer readable storage medium is not a transitory signal per se, and where the program instructions are executable by a processor to cause the processor to perform a method including incrementing, by the processor, a counter associated with an image in response to a creation of a container instance using the image, comparing, by the processor, the counter to a threshold value, and conditionally replicating the image by the processor, based on the comparing.

Abstract: Embodiments include methods, systems and computer program products method for editing and correcting structural metadata associated a binary large object (BLOB). The computer-implemented method includes obtaining, using a processor, at least a portion of structural metadata associated with the BLOB. The processor converts one or more fields associated with the at least a portion of structural metadata and determines that the one or more fields generated one or more errors or null values. The processor provides an interface, wherein the interface is used to cause a first movement or edit the one or more fields. The processor determines that the first movement or edit of the one or more fields fixes the one or more errors or null values and provides an indication that the first movement or edit of the one or more fields has or has not fixed the one or more errors or null values.

Abstract: Certain example embodiments involve accessing data in a database. At least one key is associated with the data. The data is indexed based on the at least one key. The index provides key-value pairs in which keys in the key-value pairs correspond to the at least one key associated with the data and values in the key-value pairs correspond to deserializable serialized blobs generated to include the data in variant data type format. The variant data type format includes different possible equivalent representations of the data such that the data stored in the blobs is of potentially different structures. Responsive to a request received from a computing device, a database transaction is performed on the data in connection with the index and based on the received request. These techniques can be used in connection with tasks as well as data “per se.” O(1) performance is achievable in some instances.

Abstract: Representative embodiments enable the management of index structures for data tables within a database. The techniques can include (1) receiving a request to perform an operation (e.g., read, write, etc.) on a row identifier (ID) associated with an index structure, (2) identifying a plurality of segments that corresponds to the index structure, where each segment stores a respective bitmap, (3) identifying, based on the row ID, a logical block ID of a logical block that encompasses the row ID, (4) utilizing the logical block ID to identify, among the plurality of segments, a subset of segments encompassed by the logical block, and (5) parsing each segment of the subset of segments to identify a respective bitmap that encompasses the row ID, and (6) in response to identifying the respective bitmap: performing an operation on a bitmap value that corresponds to the row ID.

Abstract: Provided is a method and system for transforming a GUID of a database entry into a reduced identifier. The transformation may be performed by a bijective function. In one example, the method may include one or more of receiving a database entry which includes a global unique identifier (GUID) which uniquely identifies the database entry, identifying a transformation function associated with the database entry, transforming the GUID into a reduced identifier based on the transformation function wherein the reduced identifier has a reduced size with respect to a size of the GUID, and storing the database entry based on the reduced identifier.

Abstract: In one embodiment, a computer-implemented method for namespace and content manipulation within a storage system includes: defining policy rule(s), each policy rule dictating: how namespaces within the storage system may be transformed; and/or how content stored within the storage system may be transformed; receiving a request for access to a particular data set stored within the storage system; parsing the request to determine one or more transformations requested therein and/or required thereby; determining whether the particular data set is compliant with the one or more transformations; in response to determining the particular data set is compliant with the one or more transformations, providing access to the particular data set; and in response to determining the particular data set is not compliant with the one or more transformations, performing the one or more transformations to generate a transformed data set, and providing access to the transformed data set.

Abstract: A method, computer system, and a computer program product for ensuring integrity of records in a NoSQL database including a first table and a second table is provided. The present invention may include the first table having first records representing respective first entities and the second table having second records representing respective second entities. The present invention may include using a hash table associating each second entity of the second table with the respective hash or summary hash values of first records for reading the second records of the second table.

Abstract: The present disclosure includes analyzing client instance performance trends to predict future client instance performance and adjusting thresholds used to send resource utilization alerts based on analyzing the client instance performance trends. In particular, a data center providing a platform as a service includes a database that stores performance data associated with client instances. The data center also includes alignment logic that temporally aligns the performance data, and a frequency based filter that compresses the aligned performance data based on frequency of values. The data center further includes dynamic threshold adjustment logic that adjusts thresholds associated with sending performance trend alerts based on analyzing the compressed set of performance data.

Abstract: In one embodiment, a service receives a one or more digests to verify a plurality of requests that were performed by a request handler for one or more clients. The digests summarize processing of the plurality of requests using a first contract. The information for the one or more digests is stored in a plurality of blocks in a distributed ledger. A second contract is executed to verify the processing of the plurality of requests. The second contract generates a first set that stores states for reads of values from the data store; generates a second set that stores states for values written to the data store, and verifies the processing by checking states in the first set are a subset of states in the second set.

Abstract: A method of providing data stored in a network device to a subscriber, the method including providing a central database including data stored in a table, maintaining a sorted list for the table in the publisher, and generating a modification and a modification identifier for the table with the publisher. The method further including inserting the modification into the table in the central database based on the modification identifier, receiving a command from the subscribed for the table, and providing the table to the subscriber from the central database.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for expanding user segments automatically utilizing user embedding representations generated by a trained neural network. For example, a user embeddings system expands a segment of users by identifying holistically similar users from uniform user embeddings that encode behavior and/or realized traits of the users. Further, the user embeddings system facilitates the expansion of user segments in a particular direction and focus to improve the accuracy of user segments.

Abstract: The disclosed embodiments provide a system for performing A/B testing of service-level metrics. During operation, the system obtains service-level metrics for service calls made during an A/B test, wherein the service-level metrics are aggregated by user identifiers of multiple users. Next, the system matches the service-level metrics to treatment assignments of the users to a treatment group and a control group in the A/B test. The system then applies the A/B test to a first grouping of the service-level metrics for the treatment group and a second grouping of the service-level metrics for the control group. Finally, the system outputs a result of the A/B test for use in assessing an effect of a treatment variant in the A/B test on the service-level metrics.

Abstract: Methods for automatic selection of degrees of parallelism for efficient execution of queries in a database system are performed by systems and devices. An incoming query associated with a query system is received and features of the incoming query are determined. A system state of the query system and a set of executing queries are also determined, along with a query state of each executing query in the set. At runtime of the incoming query, allocation of a degree of parallelism for executing the query is determined by calculating different possible execution times for the incoming query at least partially concurrently with the set of executing queries. Execution times are calculated for different parallel thread options and based on query features, system state, or query states of executing queries. The execution of the incoming query is initialized with the parallel thread option corresponding to a specific execution completion time.

Abstract: The disclosed embodiments provide a system for performing unified management of targeting attributes in A/B tests. During operation, the system obtains attribute configurations for attributes to be used in subsequent targeting of users by A/B tests. Next, the system configures, based on the attribute configurations, onboarding of the attributes from an offline environment, a near-real-time environment, and an online environment. During an A/B test, the system retrieves values of one or more of the attributes for a user from locations specified in the attribute configurations. Finally, the system outputs the values with targeting conditions for the A/B test for use in selecting a treatment assignment for the user in the A/B test.

Abstract: Described herein is a system and method for a static streaming job startup sequence. During compilation of a streaming job, a graph of computing nodes of the streaming job is traversed to determine a minimum start time of computing node(s) downstream of each input computing node of the streaming job. Also, during compilation, a start time is assigned to each input computing node in accordance with the determined minimum start time. During execution of the streaming job, responsive to receipt of the trigger anchor by a particular input node, processing of the particular input computing node using the determined minimum start time is commenced. The input computing node further generates an anchor. Input data is received, and, a batch of data provided in accordance with the received input data and generated anchor.

Abstract: In one embodiment, a complex query includes components that are arranged in a hierarchical structure including a first type of filter and a second type of filter and are connected by connectors. The method selects a first data set and selects a second data set for the components. The second data set being generated by processing data in the first data set for the second type of filter and the second data set includes entries describing a result of the processing. The first type of filter is applied to the first data set and the second type of filter to the second data set for the components where the information describing the result is used by the second type of filter to filter entries and first type of filter filters entries based on column values in the first data set. The method combines outputs of the components using the connectors.

Abstract: Machine data is collected from multiple sources of an operating environment such as an information technology system, factory floor, or the like, into a data intake and query system, in one embodiment. Metrics representative of the environment are included in or derived from the data. Users may interact with an interface to depict a representation of various metrics and interdependencies and that depiction is reflected in a computer storage model. Changes to the computer storage model based on the user interaction may also result in training of a machine learning model according to the user interaction, the machine learning model configured to determine a prediction, classification or clustering of a result of a first search query by utilizing a result of at least a second search query as input to the machine learning model.

Abstract: Machine data is collected from multiple sources of an operating environment such as an information technology system, factory floor, or the like, into a data intake and query system, in one embodiment. Metrics representative of the environment are included in or derived from the data. Users may interact with an interface to depict a representation of various metrics and interdependencies and that depiction is reflected in a computer storage model. Changes to the computer storage model based on the user interaction may also result in automatic changes to control information reflected in the computer storage model that directs the processing of various monitoring functions associated with the metrics.

Abstract: Disclosed is system for visually representing user's browsing history in structured manner, system comprising: memory unit for storing user's browsing history having plurality of search queries and Uniform Resource Identifiers; ontological databank comprising plurality of concepts; data processing arrangement communicably coupled to memory unit and ontological databank, data processing arrangement comprising: retrieval module for retrieving the plurality of search queries, analyzer module for analyzing plurality of search queries for determining concept associated with the search query based on keyword present therein using ontological databank, semantic relations between search queries, based on concepts associated therewith, and generator module for generating hierarchical structure having display elements and hierarchical-relations between display elements, wherein display elements correspond to search queries and corresponding Uniform Resource Identifiers, and wherein hierarchical-relations between displa

Abstract: Techniques for migrating clients from one technology stack to another are provided. In one technique, while a legacy service is hosted that is actively serving requests from multiple clients, a new service is initiated and one or more clients send requests to the new service. The legacy service reads data from and writes data to a legacy database in response to the requests. The new service forwards, to the legacy service, a first set of client requests that were directed to the new service. A new database is synchronized with the legacy database. After synchronization, the legacy service forwards, to the new service, a second set of client requests, which the new service processes.

Abstract: Methods and systems for managing synchronization among databases are described. One method includes establishing a trigger within a transactional database storing a plurality of transaction records, the trigger having a trigger condition associated with storing a new transaction record in the transactional database. The method includes, in response to each occurrence of the trigger condition, storing a primary key of the new transaction record into a primary key table. The method also includes aggregating transaction record information into a transaction dataset, the transaction record information being from each of a plurality of transaction records that are associated with primary keys stored in the primary key table during a predetermined time period; and transmitting the transaction dataset to a remote analysis database as streaming data.

Abstract: For each unique pair of a complete set of data items, a computing device determines a distance between the data items of the unique pair. The computing device repeats the following until no data items remain in the complete set. For each data item remaining in the complete set, the computing device determines a similarity subset including each other data item that the distance between the data item and the other data item is less than a target difference threshold. The computing device moves a selected data item from a largest similarity subset to a reference database that is a subset of the complete set. The computing device removes each data item from the complete set that the distance between the selected data item and the data item is less than the threshold. A new data item can be classified using the reference database.

Abstract: The disclosed embodiments provide a system that performs A/B testing using ego network clusters. During operation, the system obtains a graph that includes a set of nodes representing users in an online network and a set of edges representing relationships or interactions between pairs of the nodes. Next, the system selects egos containing a subset of the users that are representative of a distribution of an attribute across the users. The system then generates clusters of users, such that each cluster contains an ego and alters selected from the ego's connections in the graph. The system further divides the clusters between a treatment group and a control group, exposes alters in the treatment group to a treatment variant of an A/B test, and exposes alters in the control group to a control variant of the A/B test. Finally, the system outputs a result of the A/B test.

Abstract: A database system performs lookalike analysis on a data set including a plurality of user identifiers, which are associated with one or more attribute records. The database system classifies the user identifiers into one or more segments of user identifiers based on the attribute records. The database system performs Linear Discriminant Analysis (LDA) to calculate a measure of importance of the attribute records relative to the one or more segments. The database system auto-correlates the attribute records based on the numbers of attribute records in the user identifier population and the one or more segments. The database system identifies a set of user identifiers relative to one or more segments using the measures of importance and the auto-correlated parameters.

Abstract: A method of mapping a first graphical data structure representation to a second graphical data structure representation, the first graphical data structure representation comprising nodes, with at least one of a plurality of relations between said nodes, the second graphical data structure representation comprising nodes, the mapping comprises using an attention mechanism, wherein said attention mechanism establishes the importance of specific nodes dependent on their neighbourhood and the relations between the nodes.

Abstract: One embodiment provides a method comprising receiving a first set of information corresponding to a first entity and receiving a second set of information corresponding to a second entity. Each set of information received corresponding to each entity comprises visual information relating to the entity. The method further comprises encoding each set of information, and classifying the first entity and the second entity as either matching entities or non-matching entities based on the encoding.

Abstract: The systems, devices, and techniques described herein are directed to tracking keyword performance associated with search engine optimization. For example, the systems, devices, and techniques described herein can include determining a list of keywords relevant to a website and determining a ranking of the website in search results responsive to individual keywords of the list of keywords. A selection rate associated with search rankings can be determined, as well as a query volume of keywords over time. A keyword ranking index (KRI) can be determined based on the list of keywords, rankings of keywords, selection rates associated with rankings, and expected query volumes. In some instances, the KRI may represent a weighted sum of expected query volume divided by a maximum expected volume associated with the keyword list. Thus, the KRI provides an improved determination of keyword performance with respect to search engines and keyword rankings associated with a website.

Abstract: Systems and methods described receiving a set of example data and a set of knowledge based data and combine the set of example data and the set of knowledge based data to generate a set of combined data. The combined set can be used to train a machine learning model based on the set of combined data. The machine learning model is applied to a new set of received data for a new subject.

Abstract: This disclosure relates generally to an information retrieval technology and more particularly to a creation of a taxonomy to facilitate subsequent search and retrieval of information. In one embodiment, an information retrieval device is disclosed, that comprises a processor and a memory that stores instructions, which, on execution, causes the processor to receive an input corpus. Thereafter, input document clusters are generated from top input n-grams associated with the input corpus. Further, top-ranked input n-grams are determined from the top input n-grams. Thereafter, an external corpus is identified based on the top-ranked input n-grams. An enriched corpus (external and input corpus), is clustered based on top enriched n-grams associated with the enriched corpus to generate enriched document clusters. Further, for each n-gram of the enriched corpus, corresponding n-gram clusters are determined.

Abstract: A question answering (QA) system comprising memory for storing instructions, and a processor configured to execute the instructions to ingest source documents that include structured data and unstructured data to create a knowledge base, wherein the unstructured data includes table data; create table annotations to represent the table data; store the ingested structured data, unstructured data, and the table annotations in the knowledge base; and determine answers to questions using the knowledge base.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for expanding search queries using query term weighting. A search system receives a search term comprising multiple keywords and executes a search query based on the search term. In response to determining that the number of search results is less than a threshold number, the search system determines, based on historical query reformulation data, weight values for the keywords included in the search term. The weight values indicate a probability that each respective keyword would be removed when reformulating the search term. The search system generates a reformulated search term based on the weight values and executes a second search query based on the reformulated search term. The search system causes presentation of at least a portion of the search results on a client device of the requesting user.

Abstract: Disclosed is system for presenting information related to a search query, comprising: a client device configured to receive the search query; a database arrangement; an ontological databank and a server arrangement communicably coupled to the client device and the database arrangement, wherein the server arrangement is configured to: receive the search query, segment the search query into one or more query segments; identify one or more query concepts associated with one or more query segments, wherein each of the one or more query concepts are tagged with a corresponding entity class; determine a data structure for the information related to the search query based on one or more metrics of the relationships of the one or more query concepts, and render, on the client device, the information related to the search query presented in the data structure.