Abstract: Aspects described herein include systems and methods for determining addresses for assets, prioritizing the addresses for inspection by users, and applying natural language processing techniques to unstructured text input by the users. According to some aspects, a message may be received that includes unstructured text that was input by a user. The unstructured text may be associated with an inspection, by the user, of an address for an asset. One or more natural language techniques may be applied to the unstructured text to, among other things, facilitate the determination and sending of a response message to the unstructured text in an automated fashion. The response message may, if the asset was not found, include another address as a suggestion for the user to inspect for the asset. This suggested address may be determined based on changes to address priority that were caused by processing of the unstructured text.

Abstract: Systems and methods for determining accurate addresses for assets are described herein. According to some aspects, a plurality of addresses associated with an asset are compiled from sources such as database systems. For the plurality of address records, scores that correspond to attributes of the address records can be determined. Attributes associated with the address records may include a recency, a source, a date, license plate data, or address type, to name several non-limiting examples. Additionally, a zone of interest for the asset can be determined based on the plurality of address records. The plurality of address records is prioritized based on their distance from the zone of interest and the scores associated with them and, based on the priority, a subset of the plurality of address records is sent to, for example, a service provider.

Abstract: Aspects described herein include systems and methods for determining addresses for assets, prioritizing the addresses for inspection by users, and applying natural language processing techniques to unstructured text input by the users. According to some aspects, a message may be received that includes unstructured text that was input by a user. The unstructured text may be associated with an inspection, by the user, of an address for an asset. One or more natural language techniques may be applied to the unstructured text to, among other things, facilitate the determination and sending of a response message to the unstructured text in an automated fashion. The response message may, if the asset was not found, include another address as a suggestion for the user to inspect for the asset. This suggested address may be determined based on changes to address priority that were caused by processing of the unstructured text.

Abstract: A method or system for monitoring data quality issues in non-native data over disparate computer networks is described. The system may monitor incoming data entries of non-native data over a disparate computer network. The system may generate for display, on a user interface, a recommendation based on a difference between a number of the first plurality of data entries and a dynamic threshold.

Abstract: Systems and methods for determining accurate addresses for assets are described herein. According to some aspects, a plurality of addresses associated with an asset are compiled from sources such as database systems. For the plurality of address records, scores that correspond to attributes of the address records can be determined. Attributes associated with the address records may include a recency, a source, a date, license plate data, or address type, to name several non-limiting examples. Additionally, a zone of interest for the asset can be determined based on the plurality of address records. The plurality of address records is prioritized based on their distance from the zone of interest and the scores associated with them and, based on the priority, a subset of the plurality of address records is sent to, for example, a service provider.