Abstract: Systems and methods for monitoring network activity. The methods include receiving at an interface a first logging parameter for a first network device, wherein the first logging parameter specifies how the first network device is to record data associated with the first network device; communicating the first logging parameter to the first network device; and indicating to the first network device a first network-accessible location to where the first network device is to transmit its recorded data, wherein the first network device is configured to record data in accord with the first logging parameter and transmit the recorded data to the first network-accessible location.

Abstract: Systems and methods for training an object detection network are described. Embodiments train an object detection network using a labeled training set, wherein each element of the labeled training set includes an image and ground truth labels for object instances in the image, predict annotation data for a candidate set of unlabeled data using the object detection network, select a sample image from the candidate set using a policy network, generate a labeled sample based on the selected sample image and the annotation data, wherein the labeled sample includes labels for a plurality of object instances in the sample image, and perform additional training on the object detection network based at least in part on the labeled sample.

Abstract: The present disclosure relates to a method and system for automated optimization of delivery of products to users on a digital platform. Said method comprising: (1) fetching, by a processing unit [102], a location data of the multiple users of the digital platform and a hub location data of one or more hubs of the digital platform, from a memory unit [104]; (2) generating, by a pixel generator [106], a set of one or more geographic pixels from the location data of the multiple users; (3) determining, by the processing unit [102], a set of distance parameters (4) mapping, by a mapping unit [108], the set of one or more geographic pixels with the one or more hubs and (5) determining, by the mapping unit [108], an optimized hub for each subset of geographic pixels.

Abstract: A system and method of predicting a last mile design productivity of a delivery hub. The method comprises predicting: an inter-shipment time for last mile agent(s) of the delivery hub, and a productive on field time in a day for the last mile agent(s). The method thereafter encompasses predicting, a total number of delivery attempts in a day for the last mile agent(s) based on: the predicted inter-shipment time and the predicted productive on field time. Further, the method comprises predicting, a total number of successful deliveries in a day for the last mile agent(s) based on: the predicted total number of delivery attempts in a day, and an average hub conversion data. The method further comprises predicting the last mile design productivity of the delivery hub based on the predicted total number of successful deliveries in a day.

Abstract: There is a need for solutions for more effective and efficient natural language processing systems. This need can be addressed, for example, by a system configured to obtain a term correlation data object for a plurality of digital documents; determine, based at least in part on the term correlation data object, a term-topic correlation data object for the plurality of digital documents; determine, based at least in part on the term-topic correlation data object, a document-topic correlation data object for the plurality of digital documents; determine, based at least in part on the term-topic correlation data object, a document-sentiment correlation data object for the plurality of digital documents; generate the topic detection based at least in part on the document-topic correlation object; and generate the sentiment detection based at least in part on the document-sentiment correlation object.

Abstract: There is a need for solutions for more effective and efficient natural language processing systems. This need can be addressed, for example, by a system configured to obtain a term correlation data object for a plurality of digital documents; determine, based at least in part on the term correlation data object, a term-topic correlation data object for the plurality of digital documents; determine, based at least in part on the term-topic correlation data object, a document-topic correlation data object for the plurality of digital documents; determine, based at least in part on the term-topic correlation data object, a document-sentiment correlation data object for the plurality of digital documents; generate the topic detection based at least in part on the document-topic correlation object; and generate the sentiment detection based at least in part on the document-sentiment correlation object.