Abstract: Described are a system, method, and computer program product for generating a data storage server distribution pattern. The method includes determining a set of servers and raw data to be stored. The method also includes transforming the raw data according to an error-correcting code scheme to produce distributable data. The method further includes determining a server reliability of each server in the set of servers. The method further includes generating the data storage server distribution pattern based on maximizing a system reliability relative to maximizing a system entropy. System reliability may be based on a minimum reliability of the set of servers, and system entropy may be based on a cumulated information entropy of each server of the set of servers. The method further includes distributing the distributable data to be stored across at least two servers of the set of servers according to the data storage server distribution pattern.

Abstract: A message management service can enable a client to search and retrieve of messages from one or more messaging services. The message management service can stage delivery of results to the client to reduce response time for identification of messages satisfying a query. Initially, the message management service can send information descriptive of results, which the client can display. The message management service can send subsequent responses including supplemental information associated with a result and/or actual messages.

Abstract: A method for data visualization is provided. The method comprises receiving an input comprising a number of search parameters and then creating a cache node for the number of search parameters in the database, wherein the cache node comprises a first reference associated with the number of search parameters. Then identifying a number of search results related to the number of search parameters and storing the number of search results related to the number of search parameters in the cache node. Further, identifying a number of visualization options related to the number of search results stored in the cache node, wherein each visualization option comprises a second reference associated with the cache node.

Abstract: Methods and systems are described herein for improving data processing efficiency of classifying user files in a database. More particularly, methods and systems are described herein for improving data processing efficiency of classifying user files in a database in which the user files have a temporal element. The methods and system described herein accomplish these improvements by introducing time dependency into time-homogeneous probability models. Once time dependency has been introduced into the time-homogeneous probability models, these models may be used to improve the data processing efficiency of classifying the user files that feature a temporal element.

Abstract: An automated annotation system to automatically designate annotations to records within a report, which may perform operations that include: designating an annotation to a location, the annotation comprising a text string; identifying a record of the location within a report; selecting the annotation based on the record of the location within the report; and applying the text string of the annotation to the record within the report, according to certain example embodiments.

Abstract: The technology disclosed describes systems and methods for generating feature vectors from resource description framework (RDF) graphs. Machine learning tasks frequently operate on vectors of features. Available systems for parsing multiple documents often generate RDF graphs. Once a set of interesting features to be considered has been established, the disclosed technology describes systems and methods for generating feature vectors from the RDF graphs for the documents. In one example setting, a machine learning system can use generated feature vectors to determine how interesting a news article might be, or to learn information-of-interest about a specific subject reported in multiple articles. In another example setting, viable interview candidates for a particular job opening can be identified using feature vectors generated from a resume database, using the disclosed systems and methods for generating feature vectors from RDF graphs.

Abstract: A system dynamically changes a data de-identification ruleset applied to a dataset for de-identifying data and comprises at least one processor. The system periodically monitors a dataset derived from data that is de-identified according to a data de-identification ruleset under a set of conditions. The set of conditions for the data de-identification ruleset is evaluated with respect to the monitored data to determine applicability of the data de-identification. One or more rules of the data de-identification ruleset are dynamically changed in response to the evaluation indicating one or more conditions of the set of conditions for the data de-identification ruleset are no longer satisfied. Embodiments of the present invention may further include a method and computer program product for dynamically changing a data de-identification ruleset applied to a dataset for de-identifying data in substantially the same manner described above.

Abstract: A computer-implemented method for integration of machine learning components within a pipelined search query to generate a visualization is described. Herein, an interface is provided for receipt of pipelined code into a web-based programming application. The pipelined code features a series of operators configured to perform one or more tasks based on collective operations by the series of operators, wherein a first operator of the series of operators is to receive input data from a selected data source and each remaining operator of the series of operators to receive input based on an output from a preceding operator of the remaining operators. The task(s) performed by the pipelined code generate results including visualizations. The visualization is rendered in a manner that allows the pipelined code to be scrolled to display the pipelined code or the visualization.

Abstract: Techniques for tracing attributes through queries in a set of nested queries are disclosed. A graphical user interface displays individual sub-queries as separate visual representations. Based on detecting a selection, a system analyzes data underlying the visual representations to identify queries, among the set of nested queries, that are associated with a particular attribute. One selection results in the system analyzing the underlying data to identify an origin query for an attribute, from among the set of nested queries. Another selection results in the system analyzing the underlying data to identify queries, from among the set of nested queries, that use the attribute received from a selected query. Another selection results in the system generating SQL code for a selected subset of queries, among the set of nested queries.

Abstract: A system and a method are disclosed for optimally ranking and indexing accommodation listing information based on a set of constraints corresponding to a travel activity goal input on a client device. In an embodiment, an accommodation management system receives a travel activity goal input by a guest user on a client device with a corresponding set of constraints. Based on the constraints, the accommodation management system determines a set of geographic coordinates corresponding to the travel activity, and further identifies the set of candidate accommodation listings with accommodations within a threshold distance from the geographic coordinates. The accommodation management system filters and ranks the candidate accommodation listings based on the constraints, and sends a recommendation to the guest user for display on the client device which includes one or more of the ranked accommodation listings.

Abstract: A method for profile matching includes receiving a plurality of user profiles, each user profile comprising traits of a respective user. The method includes receiving a preference indication for a first user profile of the plurality of user profiles. The method also includes determining a potential match user profile of the plurality of user profiles based on the preference indication for the first user profile. The method also includes presenting the potential match user profile to a second user.

Abstract: Query restatements may be provided for explaining natural language query results. A natural language query is received at a natural language query processing system. An intermediate representation of the natural language query is generated for executing the natural language query. The intermediate representation is translated into a natural language restatement of the natural language query. The natural language restatement is provided with a result of the natural language query via an interface of the natural language query processing system.

Abstract: Techniques for suggesting a filter field based on a user input are disclosed. A system trains a machine learning model by obtaining historical data including sets of user search input, including a first search term and a first value for a first filter field. Based on the historical data, the system trains the machine learning model to associate the first filter field with the first search term. The system receives a first query for execution. The system applies the machine learning model to the first query to identify the first filter field as a suggestion. The system: recommends the first field for filtering a first set of search results corresponding to the first query. Responsive to receiving user input selecting a first value for the first filter field, the system filters using the first value to generate a set of filtered search results, and presents the filtered search results.

Abstract: A digital signage system provides a processor and memory; a media player for delivering content to digital signage that stores at least one playlist having media slots for playing media spots, where at least one of the media spots is a content controlling spot that includes intelligent content including attributes and attribute values for commanding control of delivery of other media spots, where the content controlling spot is configured to, upon being instigated, use the intelligent content to search for media spots to be played by the media player, identify a plurality of published media spots to be played based on a set of attributes and attribute values associated therewith, and cause one of the plurality of the published media spots to be retrieved based on the set of attributes and attribute values associated with the spot, and where the media player plays the retrieved spot on the digital signage.

Abstract: Devices and techniques are generally described for search using a micro-partitioned catalog. In some examples, a search system can determine a plurality of items in an online catalog. The search system can generate a similarity graph based on vector representations of the plurality of items and determine an item as a representative item for a cluster of items. The search system can receive a query and determine the cluster of items as a candidate cluster based on a comparison between the query and the representative item. The search system can determine a candidate item of the cluster of items based on a comparison between the query and the cluster of items.

Abstract: A method is provided. The method comprises accessing a target database comprising at least one table associated with a first concept or property of a reference ontology, defining a data source ontology for a data source comprising a dataset, said data source ontology comprising a second concept or property, wherein said second concept or property is different from said first concept or property, and creating a link between said second concept or property and said first concept or property, said link defining to which table of said target database data of said dataset, associated with said second concept or property, is related.

Abstract: Techniques are described for fast approximate conditional sampling by randomly sampling a dataset and then performing a nearest neighbor search on the pre-sampled dataset to reduce the data over which the nearest neighbor search must be performed and, according to an embodiment, to effectively reduce the number of nearest neighbors that are to be found within the random sample. Furthermore, KD-Tree-based stratified sampling is used to generate a representative sample of a dataset. KD-Tree-based stratified sampling may be used to identify the random sample for fast approximate conditional sampling, which reduces variance in the resulting data sample. As such, using KD-Tree-based stratified sampling to generate the random sample for fast approximate conditional sampling ensures that any nearest neighbor selected, for a target data instance, from the random sample is likely to be among the nearest neighbors of the target data instance within the unsampled dataset.

Abstract: In some examples, a database system receives data relating to plural micro-models that apply respective analytics, and distributes a plurality of data segments of the received data across the plurality of processing engines based on values of a segmentation key included in the received data. A plurality of processing engines, performs in parallel, operations associated with the plural micro-models using respective data segments of the plurality of data segments, where different processing engines of the plurality of processing engines perform operations associated with respective micro-models of the plural micro-models.

Abstract: A system, method, and computer-readable medium to extract information from at least one of code and text documentation, the extracted information conforming to a base ontology and being extracted in the context of a knowledge graph; add the extracted information to the knowledge graph; generate, in a mixed interaction with a user selectively in communication with the system, computational models including scientific knowledge; and persist, in a memory, a record of the generated computational models.

Abstract: A computer-implemented system and method for searching comprises, in an initial training phase, storing a plurality of user journeys in a stored journey database (SJDB), and storing a plurality of intents in a stored intents database (SIDB). The plurality of user journeys comprise a plurality of intents linked together by weighted links. In a first use phase, the method comprises determining a first intent of a first user or a second user, and modifying a first weighting of the weightings based on the first intent. In a second use phase, the method comprises receiving, from the second user, a second user question, determining a second intent from the second user question, and locating a user journey from the plurality of user journeys in the SJDB related to the second intent.