Systems and methods for responding to a subscriber's text-based request for content items are presented. In response to a request from a subscriber, word pieces are generated from the text-based terms of the request. A request embedding vector of the word pieces is obtained from a trained machine learning model. Using the request embedding vector, a set of content items, from a corpus of content items, is identified. At least some content items of the set of content items are returned to the subscriber in response to the text-based request for content items.

Systems and methods for responding to a subscriber's text-based request for content items are presented. In response to a request from a subscriber, word pieces are generated from the text-based terms of the request. A request embedding vector of the word pieces is obtained from a trained machine learning model. Using the request embedding vector, a set of content items, from a corpus of content items, is identified. At least some content items of the set of content items are returned to the subscriber in response to the text-based request for content items.

A process of presenting statements captured at an incident scene. First real-time multimedia streams captured corresponding to an incident scene are converted into digital statements. Each statement is tagged to a person identity that is determined based on a biometric attribute extracted from the multimedia streams. When a responder arrives at the incident scene, second real-time multimedia streams are captured corresponding to the incident scene and an identity of a person present at the incident scene is determined. If the identity of the person determined from the second multimedia streams matches with the person identity determined from the first multimedia streams, statements tagged to the person identity are selected and a post-arrival notification is generated for the responder indicating a presence of the person at the incident scene and including the selected statements. The notification is then provided via a visual and/or audio output device operated by the responder.

A process of presenting statements captured at an incident scene. First real-time multimedia streams captured corresponding to an incident scene are converted into digital statements. Each statement is tagged to a person identity that is determined based on a biometric attribute extracted from the multimedia streams. When a responder arrives at the incident scene, second real-time multimedia streams are captured corresponding to the incident scene and an identity of a person present at the incident scene is determined. If the identity of the person determined from the second multimedia streams matches with the person identity determined from the first multimedia streams, statements tagged to the person identity are selected and a post-arrival notification is generated for the responder indicating a presence of the person at the incident scene and including the selected statements. The notification is then provided via a visual and/or audio output device operated by the responder.

A system provides communications between local device installations and a remote monitoring computer and includes a plurality of computerized devices communicating on a bi-directional network. At least one local device transmits local device data to a remote monitoring computer on the bi-directional communications network. An interface computer receives the local device data and formats the local device data for further transmission to the remote monitoring computer, wherein the interface computer has at least one processor and computer memory storing interface software that implements a method of translating data of any kind into a preferred format. The method includes storing the local device data in the computer memory of the interface computer; transforming the local device data into a formatted data set; and transmitting the formatted data set to at least one remote monitoring computer.

A system provides communications between local device installations and a remote monitoring computer and includes a plurality of computerized devices communicating on a bi-directional network. At least one local device transmits local device data to a remote monitoring computer on the bi-directional communications network. An interface computer receives the local device data and formats the local device data for further transmission to the remote monitoring computer, wherein the interface computer has at least one processor and computer memory storing interface software that implements a method of translating data of any kind into a preferred format. The method includes storing the local device data in the computer memory of the interface computer; transforming the local device data into a formatted data set; and transmitting the formatted data set to at least one remote monitoring computer.

The present disclosure relates to generating a complex entity index based on a combination of atomic and deep learned attributes associated with instances of a complex entity. For example, systems described herein generate a multi-dimensional representation of entity instances based on evaluation of digital content associated with the respective entity instances. Systems described herein further generate an index representation in which similarity of entity instances are illustrated and presented via an interactive presentation that enables a user to traverse instances of an entity to observe similarities and differences between instances of an entity that have similar embeddings to one another within a multi-dimensional index space.

The present disclosure relates to generating a complex entity index based on a combination of atomic and deep learned attributes associated with instances of a complex entity. For example, systems described herein generate a multi-dimensional representation of entity instances based on evaluation of digital content associated with the respective entity instances. Systems described herein further generate an index representation in which similarity of entity instances are illustrated and presented via an interactive presentation that enables a user to traverse instances of an entity to observe similarities and differences between instances of an entity that have similar embeddings to one another within a multi-dimensional index space.

A multidimensional system for generating a multimedia search engine is provided. A computer device identifies a plurality of independently separable aspects of a multimedia file. The computing device provides at least one independently separable aspect of the plurality of independently separable aspects as input into an object detection model. The computing device receives, from the object detection model, an identification of at least one object and a corresponding level of confidence that the object is present in the multimedia file. The computing device classifies the object as either confident or not confident, based on whether the level of confidence meets a threshold level of confidence. The computing device generates a multimedia search engine based, at least in part, on the object and the classification.

A multidimensional system for generating a multimedia search engine is provided. A computer device identifies a plurality of independently separable aspects of a multimedia file. The computing device provides at least one independently separable aspect of the plurality of independently separable aspects as input into an object detection model. The computing device receives, from the object detection model, an identification of at least one object and a corresponding level of confidence that the object is present in the multimedia file. The computing device classifies the object as either confident or not confident, based on whether the level of confidence meets a threshold level of confidence. The computing device generates a multimedia search engine based, at least in part, on the object and the classification.