Abstract: The present system pertains to event tracking, involving the acquisition of event information, generation of compound hashes, and formation of a search data structure. Event information includes time-and-geolocation data and topic data for each event. Compound hashes, comprising a spacetime hash and a topic hash for each event, are generated based on this information. A search data structure is formed using these compound hashes, enabling the grouping of spacetime hashes and structuring of topic hashes. Upon receiving a query, the system executes a search based on the query's compound hash or parameters, returning matching event content. The system can also generate semantic descriptions of relevant events using a narrative generation model and predict event relevance using a preferential learning model.

Abstract: The present system pertains to event tracking, involving the acquisition of event information, generation of compound hashes, and formation of a search data structure. Event information includes time-and-geolocation data and topic data for each event. Compound hashes, comprising a spacetime hash and a topic hash for each event, are generated based on this information. A search data structure is formed using these compound hashes, enabling the grouping of spacetime hashes and structuring of topic hashes. Upon receiving a query, the system executes a search based on the query's compound hash or parameters, returning matching event content. The system can also generate semantic descriptions of relevant events using a narrative generation model and predict event relevance using a preferential learning model.

Abstract: The present system pertains to event tracking, involving the acquisition of event information, generation of compound hashes, and formation of a search data structure. Event information includes time-and-geolocation data and topic data for each event. Compound hashes, comprising a spacetime hash and a topic hash for each event, are generated based on this information. A search data structure is formed using these compound hashes, enabling the grouping of spacetime hashes and structuring of topic hashes. Upon receiving a query, the system executes a search based on the query's compound hash or parameters, returning matching event content. The system can also generate semantic descriptions of relevant events using a narrative generation model and predict event relevance using a preferential learning model.

Abstract: Disclosed are methods, systems and non-transitory computer readable memory for geospatial correlation. For instance, a method may include: obtaining a plurality of records, wherein each record has a key value that points to the record in a database, and each of the plurality of records includes at least data for an observation of an entity; and generating an index based on the plurality of records. The generating the index may include: determining a plurality of observations based on the plurality of records, an observation including a device identifier and time-and-geolocation data for a record of the plurality of records; encoding the plurality of observations into a plurality of spacetime hashes; and forming a search data structure of the index for a plurality of key values based on the plurality of spacetime hashes, wherein the search data structure groups subsets of the plurality of spacetime hashes.

Abstract: Disclosed are methods, systems and non-transitory computer readable memory for geospatial correlation. For instance, a method may include: obtaining a plurality of records, wherein each record has a key value that points to the record in a database, and each of the plurality of records includes at least data for an observation of an entity; and generating an index based on the plurality of records. The generating the index may include: determining a plurality of observations based on the plurality of records, an observation including a device identifier and time-and-geolocation data for a record of the plurality of records; encoding the plurality of observations into a plurality of spacetime hashes; and forming a search data structure of the index for a plurality of key values based on the plurality of spacetime hashes, wherein the search data structure groups subsets of the plurality of spacetime hashes.