Salesforce Com, Inc.

Open Invention Network LLC

Other

Red Hat, Inc.

Salesforce, Inc.

Commerce One, LLC

Commerce One Operations, Inc.

Matthew Daniel Fuchs

Arun Kumar Jagota

Bart Alan Meltzer

Robert John Glushko

Terry Allen

Murray Maloney

Andrew Everett Davidson

Changyi Zhu

Jari Koistinen

Mehmet Gokmen Orun

Antonio Garrote

Stanislav Georgiev

Lei Ming

Kelly Henvy

Gregory Haardt

Kelly Lane Schwarzhoff

Govardana Sachithanandam Ramachandran

Fang Wong

Zandro Luis Gonzalez

Craig Howland

George Vitchev

Davidson Andrew

Kenneth Persson

Pawel Psztyc

Pawel Uchida-Psztyc

A system allows translation across API models represented using different API description languages. The system stores model bindings from a common visualization model format to multiple API description languages. The model bindings map constructs of the API description language to and from modeling constructs of the common visualization model format. The system uses the model bindings to convert API models to and from representations based on API description languages to the common visualization model format. The system used the common visualization model format to generate visualizations of the API model that can be displayed via a user interface and also allow users to modify the API model.

Extensible binding mechanism for translating between application programming interface description languages

Techniques are disclosed relating to the serialization of data of a database. A computer system may maintain a database that stores data as a plurality of triples. A triple may include a first data entity that is connected to a second data entity via an edge, and triples of the plurality of triples may be connected to form graphs. The computer system may store metadata defining types of edges between data entities. An edge's type may indicate a procedure for serializing a target data entity connected to that edge's type. The computer system may receive a request to access a data entity associated with a plurality of descendant data entities connected to the data entity via edges. The computer system may generate an output having the data entity and one or more of the plurality of descendant data entities that are serialized according to the types of edges.

Mechanisms for serializing triples of a database store

A system and method of operation of an augmented reality system includes: a position sensor for calculating a current location; an orientation sensor, coupled to the position sensor, for calculating a current orientation; and a control mechanism, coupled to the position sensor, for presenting a system object based on the current location, the current orientation, an object location, an object orientation, an access right, a visibility, and a persistence.

Augmented reality system and method of operation thereof

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.

Generating feature vectors from RDF graphs

A system and method of operation of an augmented reality system includes: a position sensor () for calculating a current location (); an orientation sensor (), coupled to the position sensor (), for calculating a current orientation (); and a control mechanism (), coupled to the position sensor (), for presenting a system object () based on the current location (), the current orientation (), an object location (), an object orientation (), an access right (), a visibility (), and a persistence ().

Disclosed embodiments are related to Master Data Management (MDM) technologies. Each DB entity (record) in component databases (DB) is represented as a judgment, and an MDM system unifies judgments obtained from the component DBs into a unified set of judgments. In the unified set of judgments, linkages are judgments asserting that particular DB entities from different DBs are the same/similar, and a golden record comprises field values describing each of the DB entities. In making judgments, the MDM system consolidates judgments (or records) describing the same subject into a single judgment, and performs updates to field values in a manner that does not violate referential integrity. Each update is associated with an MDM consistent state. Updates in the form of judgments are provided to the relevant component DBs, which are converted into serializable transactions associated with respective MDM consistent states. Other embodiments may be described and/or claimed.

Master data management technologies

A system receives a character sequence entered in a search box, identifies a first item that includes the character sequence and a second item that includes the character sequence, identifies a first item set that includes the first item and a second item set that includes the second item; and outputs the first item set and the second item set to a location associated with the search box. The system receives a selection of a third item from the first item set, identifies a third item set that includes the third item and a fourth item set that includes the third item, and outputs the third item set and the fourth item set to the location associated with the search box. The system receives a selection of any item set from the location associated with the search box, and executes a search based on the selected item set.

Suggesting query items based on frequent item sets

Systems and methods for processing user-submitted updates based on user reliability scores. An update score is determined for an update submitted by a user based on a similarity of a field value provided by the update to corresponding field values in identified records. A user score is determined based on update scores, including the update score, determined for corresponding updates submitted by the user. The update is then processed based on the user score.

Processing user-submitted updates based on user reliability scores

The technology disclosed relates to improving parallel functional processing using abstractions and methods defined based on category theory. In particular, the technology disclosed provides a range of useful categorical functions for processing large data sets in parallel. These categorical functions manage all phases of distributed computing, including dividing a data set into subsets of approximately equal size and combining the results of the subset calculations into a final result, while hiding many of the low-level programming details. These categorical functions are extraordinarily well-ordered and have a sophisticated type system and type inference, which allows for generating maps and reducing them in an elegant and succinct way using concise and expressive programs that can significantly efficientize a whole software development process.

Systems and methods of improving parallel functional processing

A system creates a graph of nodes connected by arcs, and identifies a first compound attribute associated with contacts purchased by a current user. The first compound attribute includes a first attribute associated with a first value and a second attribute associated with a second value. The system identifies a directed arc from a first node to a second node. The directed arc is associated with a probability that previous users who purchased a first contact associated with the first compound attribute also purchased a second contact associated with a second compound attribute. The second compound attribute includes the first attribute, associated with a third value which matches the first value, and the second attribute, associated with a fourth value, which lacks a match with the second value. The system outputs a recommendation for the current user to purchase contacts associated with the second compound attribute if the probability exceeds a threshold.

Bulk contact recommendations based on attribute purchase history

A system receives an association of first item with first system user, generates first hash value by applying first hash function associated with first system user to first item identifier associated with first item, and sets a bit corresponding to first hash value in array. The system receives an association of second item with second system user, generates second hash value by applying second hash function associated with second user to second item identifier associated with second item, and sets a bit corresponding to second hash value in array. The system receives a request to determine whether third item is associated with first system user, generates third hash value by applying first hash function to third item identifier associated with third item, and outputs message that third item is not associated with first user if a bit corresponding to third hash value is not set in array.

Multi-user probabalistic array

A system determines a count of each item in each item set, sorts each count into ascending order, assigns an ascending identifier to each item corresponding to each sorted count, and sorts each identifier in each item set in descending order. The system partitions item sets into a first group of item sets and a second group of item sets, each item set in the first group including a common largest identifier, determines a count for each subset of each item set of the first group, and determines a count of each subset of each item set by summing each count for each subset of each item set of the first group with each corresponding count for each corresponding subset of each item set of the second group. The system outputs a recommended item set based on the count of each subset of each item set.

Identifying frequent item sets

Suggesting query items based on database fields is described. A database system receives a character sequence entered in a search box. The database system identifies a first distribution of first field-based items that include the character sequence, and a second distribution of second field-based items that include the character sequence. The database system identifies a first item based on combining the first distribution with a distribution of queried fields, and a second item based on combining the second distribution with the distribution of queried fields. The database system outputs the first item and the second item to a location associated with the search box. The database system executes a search based on any requested item, in response to receiving a request to search for any item output to the location associated with the search box.

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Los Gatos, CA, United States of America

Matthew Daniel Fuchs