Abstract: Systems and methods may use natural language processing (NLP) and machine-learning techniques to detect an impact that an event will have on a domain-specific topic. For example, the system may use multi-stage cleaning using a rules-based and an artificial intelligence (AI)-based filter to filter large quantities of event items that may not be relevant to a domain of interest. The AI-based filter may be trained using labeled event items that were previously known to be impactful. The system may cluster the cleaned event items to group similar event items and eliminate redundancy. The system may then predict and quantify the impact that events described by clustered event items will have on the domain-specific topic. Such prediction may be based on a classifier trained using various model features that correlate with impactful events, including prior similar events.

Abstract: Systems and methods may use natural language processing (NLP) and machine-learning techniques to detect an impact that an event will have on a domain-specific topic. For example, the system may use multi-stage cleaning using a rules-based and an artificial intelligence (AI)-based filter to filter large quantities of event items that may not be relevant to a domain of interest. The AI-based filter may be trained using labeled event items that were previously known to be impactful. The system may cluster the cleaned event items to group similar event items and eliminate redundancy. The system may then predict and quantify the impact that events described by clustered event items will have on the domain-specific topic. Such prediction may be based on a classifier trained using various model features that correlate with impactful events, including prior similar events.

Abstract: In a method and system for monitoring oil well development and operations, an area of interest is defined. Imagery of the area of interest is periodically received and analyzed to identify a cleared area of land, which confirms that construction of an oil well at a site has commenced. Additional imagery of the site is subsequently received and analyzed to identify one or more milestones associated with development of the oil well, including arrival of a drilling rig at the site, departure of the drilling rig from the site, completion of construction of the oil well, and building of production facilities at the site. Information about completion of the oil well and/or information about the status of the development of the oil well is then communicated to third-party market participants and other interested parties.