Abstract: In non-limiting examples, passive information is used to verify the location of a client computing device and to create segment categories for directed information using location-based services and/or applications. In aspects, passive information is received from a client computing device. The client computing device is detected as being located at a predicted venue using the passive information. It may be determined whether directed information associated with the predicted venue has been displayed at an earlier time on a predetermined portion of the client computing device. In response to determining directed information associated with the predicted venue has been displayed on the predetermined portion of the client computing device, a statistical model may be applied to calculate a confidence score that the client computing device is located at the predicted venue. When the confidence score meets a predetermined threshold, a directed information conversion record may be stored in a data store.

Abstract: In non-limiting examples, passive information is used to verify the location of a client computing device and to create segment categories for directed information using location-based services and/or applications. In aspects, passive information is received from a client computing device. The client computing device is detected as being located at a predicted venue using the passive information. It may be determined whether directed information associated with the predicted venue has been displayed at an earlier time on a predetermined portion of the client computing device. In response to determining directed information associated with the predicted venue has been displayed on the predetermined portion of the client computing device, a statistical model may be applied to calculate a confidence score that the client computing device is located at the predicted venue. When the confidence score meets a predetermined threshold, a directed information conversion record may be stored in a data store.

Abstract: The Messaging Search and Management Apparatuses, Methods and Systems (“MSM”) transforms message, ranking request inputs via MSM components into work graphs, ML structure input data, ML structure, ranking response outputs. A work graph generation request that includes group level access control data may be obtained. A set of metadata access control carrying messages, a set of users, a set of channels, and a set of topics with access control data corresponding to the group level access control data may be determined. A user priority score for each of the other users, a channel priority score for each of the channels, and a topic priority score for each of the topics, from the perspective of each user, may be calculated. A work graph data structure may be generated that includes, for each user, data regarding the calculated user priority scores, channel priority scores, and topic priority scores.

Abstract: Methods, apparatus and computer program product for improving data indexing in a group-based communication platform are described herein. The group-based communication platform having a computed collection and one or more live collections. The computer-implemented method includes generating a new collection, the new collection being generated at a snapshot time point; associating a collection manager with the new collection; retrieving a plurality of electronic messages from the computed collection and the one or more live collections; writing the plurality of electronic messages to the new collection, the writing being completed at a cut-over time point; synchronizing the new collection with the one or more live collections based on the plurality of electronic messages; and redirecting the read alias and the write alias from the computed collection to the new collection.

Abstract: Methods, apparatuses and computer program products for improving data retrieval in a group-based communication system are described herein. The apparatus is configured to at least receive a first search query comprising a first search string, identify a first index object of a plurality of index objects based at least in part on the first search string, retrieve a first message object based at least in part on the first index object, and cause rendering of the first message object within a group-based communication user interface on a client device based at least in part on at least one element content attribute and at least one element style attribute of the first message object.

Abstract: A mobile application is provided that provides intelligent recommendations based on the knowledge of where the user has been, and what venues the user would like to visit. Further, such an application may be capable of determining where people in a user's social network have been and what venue locations these related users would like to visit. Also, in another implementation, the application may be capable of determining where people with similar taste have been, and where they would like to go. Some or all of this information may be used by a mobile application that provides recommendations to a user. For instance, in one implementation, a user having a mobile device such as a cell phone wishes to locate a venue based on one or more parameters, and some or all of this information may be used to order to rank recommendations with the interface.

Abstract: Methods, apparatuses and computer program products for improving data retrieval in a group-based communication system are described herein. The apparatus is configured to at least receive a first search query comprising a first search string, identify a first index object of a plurality of index objects based at least in part on the first search string, retrieve a first message object based at least in part on the first index object, and cause rendering of the first message object within a group-based communication user interface on a client device based at least in part on at least one element content attribute and at least one element style attribute of the first message object.

Abstract: The Messaging Search and Management Apparatuses, Methods and Systems (“MSM”) transforms message, ranking request inputs via MSM components into work graphs, ML structure input data, ML structure, ranking response outputs. A work graph generation request that includes group level access control data may be obtained. A set of metadata access control carrying messages, a set of users, a set of channels, and a set of topics with access control data corresponding to the group level access control data may be determined. A user priority score for each of the other users, a channel priority score for each of the channels, and a topic priority score for each of the topics, from the perspective of each user, may be calculated. A work graph data structure may be generated that includes, for each user, data regarding the calculated user priority scores, channel priority scores, and topic priority scores.

Abstract: A mobile application is provided that provides intelligent recommendations based on the knowledge of where the user has been, and what venues the user would like to visit. Further, such an application may be capable of determining where people in a user's social network have been and what venue locations these related users would like to visit. Also, in another implementation, the application may be capable of determining where people with similar taste have been, and where they would like to go. Some or all of this information may be used by a mobile application that provides recommendations to a user. For instance, in one implementation, a user having a mobile device such as a cell phone wishes to locate a venue based on one or more parameters, and some or all of this information may be used to order to rank recommendations with the interface.

Abstract: The Messaging Search and Management Apparatuses, Methods and Systems (“MSM”) transforms message, ranking request inputs via MSM components into work graphs, ML structure input data, ML structure, ranking response outputs. A work graph generation request that includes group level access control data may be obtained. A set of metadata access control carrying messages, a set of users, a set of channels, and a set of topics with access control data corresponding to the group level access control data may be determined. A user priority score for each of the other users, a channel priority score for each of the channels, and a topic priority score for each of the topics, from the perspective of each user, may be calculated. A work graph data structure may be generated that includes, for each user, data regarding the calculated user priority scores, channel priority scores, and topic priority scores.

Abstract: In non-limiting examples, passive information is used to verify the location of a client computing device and to create segment categories for directed information using location-based services and/or applications. In aspects, passive information is received from a client computing device. The client computing device is detected as being located at a predicted venue using the passive information. It may be determined whether directed information associated with the predicted venue has been displayed at an earlier time on a predetermined portion of the client computing device. In response to determining directed information associated with the predicted venue has been displayed on the predetermined portion of the client computing device, a statistical model may be applied to calculate a confidence score that the client computing device is located at the predicted venue. When the confidence score meets a predetermined threshold, a directed information conversion record may be stored in a data store.

Abstract: Methods, apparatus and computer program product for improving data indexing in a group-based communication platform are described herein. The group-based communication platform having a computed collection and one or more live collections. The computer-implemented method includes generating a new collection, the new collection being generated at a snapshot time point; associating a collection manager with the new collection; retrieving a plurality of electronic messages from the computed collection and the one or more live collections; writing the plurality of electronic messages to the new collection, the writing being completed at a cut-over time point; synchronizing the new collection with the one or more live collections based on the plurality of electronic messages; and redirecting the read alias and the write alias from the computed collection to the new collection.

Abstract: The Messaging Search and Management Apparatuses, Methods and Systems (“MSM”) transforms message, ranking request inputs via MSM components into work graphs, ML structure input data, ML structure, ranking response outputs. A work graph generation request that includes group level access control data may be obtained. A set of metadata access control carrying messages, a set of users, a set of channels, and a set of topics with access control data corresponding to the group level access control data may be determined. A user priority score for each of the other users, a channel priority score for each of the channels, and a topic priority score for each of the topics, from the perspective of each user, may be calculated. A work graph data structure may be generated that includes, for each user, data regarding the calculated user priority scores, channel priority scores, and topic priority scores.

Abstract: The Messaging Search and Management Apparatuses, Methods and Systems (“MSM”) transforms message, ranking request inputs via MSM components into work graphs, ML structure input data, ML structure, ranking response outputs. A work graph generation request that includes group level access control data may be obtained. A set of metadata access control carrying messages, a set of users, a set of channels, and a set of topics with access control data corresponding to the group level access control data may be determined. A user priority score for each of the other users, a channel priority score for each of the channels, and a topic priority score for each of the topics, from the perspective of each user, may be calculated. A work graph data structure may be generated that includes, for each user, data regarding the calculated user priority scores, channel priority scores, and topic priority scores.

Abstract: In non-limiting examples, passive information is used to verify the location of a client computing device and to create segment categories for directed information using location-based services and/or applications. In aspects, passive information is received from a client computing device. The client computing device is detected as being located at a predicted venue using the passive information. It may be determined whether directed information associated with the predicted venue has been displayed at an earlier time on a predetermined portion of the client computing device. In response to determining directed information associated with the predicted venue has been displayed on the predetermined portion of the client computing device, a statistical model may be applied to calculate a confidence score that the client computing device is located at the predicted venue. When the confidence score meets a predetermined threshold, a directed information conversion record may be stored in a data store.

Abstract: The Messaging Search and Management Apparatuses, Methods and Systems (“MSM”) transforms message, ranking request inputs via MSM components into work graphs, ML structure input data, ML structure, ranking response outputs. A work graph generation request that includes group level access control data may be obtained. A set of metadata access control carrying messages, a set of users, a set of channels, and a set of topics with access control data corresponding to the group level access control data may be determined. A user priority score for each of the other users, a channel priority score for each of the channels, and a topic priority score for each of the topics, from the perspective of each user, may be calculated. A work graph data structure may be generated that includes, for each user, data regarding the calculated user priority scores, channel priority scores, and topic priority scores.

Abstract: In non-limiting examples, passive information is used to verify the location of a client computing device and to create segment categories for directed information using location-based services and/or applications. In aspects, passive information is received from a client computing device. The client computing device is detected as being located at a predicted venue using the passive information. It may be determined whether directed information associated with the predicted venue has been displayed at an earlier time on a predetermined portion of the client computing device. In response to determining directed information associated with the predicted venue has been displayed on the predetermined portion of the client computing device, a statistical model may be applied to calculate a confidence score that the client computing device is located at the predicted venue. When the confidence score meets a predetermined threshold, a directed information conversion record may be stored in a data store.

Abstract: A mobile application is provided that provides intelligent recommendations based on the knowledge of where the user has been, and what venues the user would like to visit. Further, such an application may be capable of determining where people in a user's social network have been and what venue locations these related users would like to visit. Also, in another implementation, the application may be capable of determining where people with similar taste have been, and where they would like to go. Some or all of this information may be used by a mobile application that provides recommendations to a user. For instance, in one implementation, a user having a mobile device such as a cell phone wishes to locate a venue based on one or more parameters, and some or all of this information may be used to order to rank recommendations with the interface.

Abstract: A mobile application is provided that provides intelligent recommendations based on the knowledge of where the user has been, and what venues the user would like to visit. Further, such an application may be capable of determining where people in a user's social network have been and what venue locations these related users would like to visit. Also, in another implementation, the application may be capable of determining where people with similar taste have been, and where they would like to go. Some or all of this information may be used by a mobile application that provides recommendations to a user. For instance, in one implementation, a user having a mobile device such as a cell phone wishes to locate a venue based on one or more parameters, and some or all of this information may be used to order to rank recommendations with the interface.

Abstract: A mobile application is provided that provides intelligent recommendations based on the knowledge of where the user has been, and what venues the user would like to visit. Further, such an application may be capable of determining where people in a user's social network have been and what venue locations these related users would like to visit. Also, in another implementation, the application may be capable of determining where people with similar taste have been, and where they would like to go. Some or all of this information may be used by a mobile application that provides recommendations to a user. For instance, in one implementation, a user having a mobile device such as a cell phone wishes to locate a venue based on one or more parameters, and some or all of this information may be used to order to rank recommendations with the interface.