Abstract: The technology disclosed relates to automatic generation of tuples from a record set for outlier analysis. Applying this new technology, user need not specify which 1-tuples to combine into n-tuples. The tuples are generated from structured records organized into features (that also could be fields, objects or attributes.) Tuples are generated from combinations of feature values in the records. Thresholding is applied to manage the number of tuples generated. The technology disclosed further relates to indexing and searching high dimensional tuple spaces in a computer-implemented system.

Abstract: The technology disclosed provides a so-called “joint many-task neural network model” to solve a variety of increasingly complex natural language processing (NLP) tasks using growing depth of layers in a single end-to-end model. The model is successively trained by considering linguistic hierarchies, directly connecting word representations to all model layers, explicitly using predictions in lower tasks, and applying a so-called “successive regularization” technique to prevent catastrophic forgetting. Three examples of lower level model layers are part-of-speech (POS) tagging layer, chunking layer, and dependency parsing layer. Two examples of higher level model layers are semantic relatedness layer and textual entailment layer. The model achieves the state-of-the-art results on chunking, dependency parsing, semantic relatedness and textual entailment.

Abstract: The technology disclosed provides a so-called “joint many-task neural network model” to solve a variety of increasingly complex natural language processing (NLP) tasks using growing depth of layers in a single end-to-end model. The model is successively trained by considering linguistic hierarchies, directly connecting word representations to all model layers, explicitly using predictions in lower tasks, and applying a so-called “successive regularization” technique to prevent catastrophic forgetting. Three examples of lower level model layers are part-of-speech (POS) tagging layer, chunking layer, and dependency parsing layer. Two examples of higher level model layers are semantic relatedness layer and textual entailment layer. The model achieves the state-of-the-art results on chunking, dependency parsing, semantic relatedness and textual entailment.

Abstract: The technology disclosed provides a so-called “joint many-task neural network model” to solve a variety of increasingly complex natural language processing (NLP) tasks using growing depth of layers in a single end-to-end model. The model is successively trained by considering linguistic hierarchies, directly connecting word representations to all model layers, explicitly using predictions in lower tasks, and applying a so-called “successive regularization” technique to prevent catastrophic forgetting. Three examples of lower level model layers are part-of-speech (POS) tagging layer, chunking layer, and dependency parsing layer. Two examples of higher level model layers are semantic relatedness layer and textual entailment layer. The model achieves the state-of-the-art results on chunking, dependency parsing, semantic relatedness and textual entailment.

Abstract: The disclosed systems and methods include pre-calculation, per object, of object feature bin values, for identifying close matches between objects, such as text documents, that have numerous weighted features, such as specific-length word sequences. Predetermined feature weights get scaled with two or more selected adjacent scaling factors, and randomly rounded. The expanded set of weighted features of an object gets min-hashed into a predetermined number of feature bins. For each feature that qualifies to be inserted by min-hashing into a particular feature bin, and across successive feature bins, the expanded set of weighted features get min-hashed and circularly smeared into the predetermined number of feature bins. Completed pre-calculated sets of feature bin values for each scaling of the object, together with the scaling factor, are stored for use in comparing sampled features of the object with sampled features of other objects by calculating an estimated Jaccard similarity index.

Abstract: The disclosed systems and methods include pre-calculation, per object, of object feature bin values, for identifying close matches between objects, such as text documents, that have numerous weighted features, such as specific-length word sequences. Predetermined feature weights get scaled with two or more selected adjacent scaling factors, and randomly rounded. The expanded set of weighted features of an object gets min-hashed into a predetermined number of feature bins. For each feature that qualifies to be inserted by min-hashing into a particular feature bin, and across successive feature bins, the expanded set of weighted features get min-hashed and circularly smeared into the predetermined number of feature bins. Completed pre-calculated sets of feature bin values for each scaling of the object, together with the scaling factor, are stored for use in comparing sampled features of the object with sampled features of other objects by calculating an estimated Jaccard similarity index.

Abstract: A computer implemented method includes receiving, at the browser application, a first request for web resources based on user selection of a first hyperlink outside of the web application; determining if the first hyperlink is associated with a record accessible by the web application from the database system; determining, when the first hyperlink is associated with the record for the web application, if a web application interface for the web application is active in at least one navigation tab of the browser application; and presenting, when the first hyperlink is associated with the record for the web application and the web application interface for the web application is active in the at least one navigation tab, the record within a console tab of the web application interface in the at least one navigation tab.

Abstract: Disclosed are systems, methods, apparatus and computer program products for facilitating text-based interaction by a mobile device with an enterprise database. In some implementations, a first one or more text messages sent from a mobile device during a session is parsed to identify a command and a type of enterprise work record. It is determined that the identified command and record type were previously identified. One or more fields of the record type required by the enterprise database to be populated to carry out the identified command is determined. A request message requesting user input to populate the one or more fields can be sent to the mobile device, and instructions can be sent to the enterprise database to carry out the identified command with respect to the identified type of enterprise work record using the field data.

Abstract: In an example, a database system may be configured to receive configuration data including a mapping of objects of a relational database to query generation parameters; compare values in a received first query to the mapping to identify column definition data of the query generation parameters; ascertain whether to identify table definition data of the configuration data based on the column definition data; determine whether to create one or more subqueries for one or more tables based on the table definition data; in response to determining to create the one or more subqueries, join a table of the one or more tables to a root table based on table relationship data of the configuration data; and build a second relational datastore query using the one or more subqueries.

Abstract: An indexing scheme generates a token index associating token index values with keywords in queries and generates expression trees for the queries that use the token index values to represent the keywords. The indexing scheme generates a document index assigning document index values to uploaded documents. The indexing scheme generates a document-token index that associates the token index values with the document index values for the documents containing the keywords associated with the token index values. The indexing scheme applies the expression trees to the document-token index to quickly identify the documents satisfying the queries. For example, the indexing scheme may generate bit arrays for each of the token index values identifying the documents containing the keywords and apply logical operators from the queries to the bit arrays. The resulting data structure provides a list of documents satisfying the queries.

Abstract: Systems and methods are provided for searchable screen sharing sessions. A system records at least one image associated with a screen sharing session. The system extracts content from the at least one image. The system stores the content as searchable content associated with the screen sharing session.

Abstract: In accordance with disclosed embodiments, there are provided systems and methods for implementing and maintaining sampled tables in a database system.

Abstract: Techniques are disclosed relating to limiting malicious-code analysis of webpage content. In one embodiment, a computing system receives a webpage requested by a client device. The computing system randomly alters content of the webpage to limit analysis of the content by malicious code such that the altering does not affect how the webpage is displayed by the client device. The computing system may then serve the webpage with the altered content to the client device. In some embodiments, the altering includes searching the webpage for an HTML element that specifies a plurality of attributes in a particular ordering and rearranging the plurality of attributes to have a new ordering different from the particular ordering. In some embodiments, the altering includes parsing the webpage for an HTML element that specifies an identifier attribute and modifying an identifier attribute of the element.

Abstract: Disclosed are systems, apparatus, methods and computer-readable media for updating information stored in a database system over a network. In some implementations, first contact data is retrieved from a first virtual portion of a database system, where the first contact data provides first contact information associated with at least one entity. In some instances, the first contact data is compared with second contact data, where the second contact data provides second contact information associated with the at least one entity. In some instances, at least some of the second contact information is retrieved from a social networking system. In various implementations, at least one difference between the first contact data and the second contact data is identified, where the at least one difference is capable of being presented in a user interface displayed at a computer system. In some instances, a selection identifying contact data to store is received.

Abstract: The technology disclosed relates to creating and frequently updating multiple online analytic processing (OLAP) analytic databases from an online transaction processing (OLTP) transaction updatable system that includes transaction commit, rollback, and field level security capabilities. It also relates to transparently decoupling extraction from rebuilding of frequently updated OLAP analytic databases from the OLTP transaction updatable system.

Abstract: A method of operating a database system to select multiple files distributed across a plurality of file folders is disclosed. The method generates a first graphical user interface formatted for presentation at a client device and having a first list of selectable files contained in a first file folder maintained by the database system. A first user input is received that identifies at least one selected file from the first list of selectable files, and the database system generates a second graphical user interface formatted for presentation at the client device and having a second list of selectable files contained in a second file folder. A second user input is received that identifies at least one selected file from the second list of selectable files. The database system performs an action involving the selected files from the first list and involving the selected files from the second list.

Abstract: The technology disclosed relates to discovering multiple previously unknown and undetected technical problems in fault tolerance and data recovery mechanisms of modern stream processing systems. In addition, it relates to providing technical solutions to these previously unknown and undetected problems. In particular, the technology disclosed relates to discovering the problem of modification of batch size of a given batch during its replay after a processing failure. This problem results in over-count when the input during replay is not a superset of the input fed at the original play. Further, the technology disclosed discovers the problem of inaccurate counter updates in replay schemes of modern stream processing systems when one or more keys disappear between a batch's first play and its replay. This problem is exacerbated when data in batches is merged or mapped with data from an external data store.

Abstract: Computer systems, methods and software for responding to remote clients with content selected based on when the request is made. The method may include selecting one or more interface components based on the time of day and/or date of the request, and returning a response including the selected interface components. The method may include adjusting the time for a time zone for the remote client and/or user. Interface components may be fully embedded in the response, or may be references to external components. Interface components may include data relating to a user task associated with the date and/or time of day, formatting information for displaying the task data to the user of the remote client, instructions for user interaction with the task data, etc.