Abstract: A device, system and method for training machine learning models using messages associated with provider objects is provided. One or more computing devices: receives messages associated with provider objects representing items provided by provider systems, the messages having more than one format; stores harmonized objects corresponding to the messages, the harmonized objects generated using mappings of harmonized data of the harmonized objects to message data of the messages, the harmonized objects having common formats for a harmonized object type; extracts, from the harmonized objects, for a given machine learning model, given machine learning training data; generates, for the given machine learning model, using the given machine learning training data, at least one machine learning classifier; and provides the at least one machine learning classifier to the given machine learning model at one or more servers configured to implement the given machine learning model on received provider objects.

Abstract: A device, system and method for training machine learning models using messages associated with provider objects is provided. One or more computing devices: receives messages associated with provider objects representing items provided by provider systems, the messages having more than one format; stores harmonized objects corresponding to the messages, the harmonized objects generated using mappings of harmonized data of the harmonized objects to message data of the messages, the harmonized objects having common formats for a harmonized object type; extracts, from the harmonized objects, for a given machine learning model, given machine learning training data; generates, for the given machine learning model, using the given machine learning training data, at least one machine learning classifier; and provides the at least one machine learning classifier to the given machine learning model at one or more servers configured to implement the given machine learning model on received provider objects.

Abstract: A data cache platform maintains pre-computed database query results computed by a computation platform based on data maintained in the computation platform and is configured to determine probabilities of the pre-computed database query results being outdated, to automatically issue re-computation orders to the computation platform for updating pre-computed database query results on the basis of the determined probabilities of the pre-computed database query results being outdated and to receive the updated pre-computed database query results as results of the re-computation orders. The probability determination depends on a probabilistic model and on the occurrence of asynchronous real-time events. The real-time events are indeterministic with regard to the expiration of the cached database query results and only have a probabilistic influence on the discrepancies between the database query results maintained in the data cache platform and presumed actual database query results.

Abstract: A data cache platform maintains pre-computed database query results computed by a computation platform based on data maintained in the computation platform and is configured to determine probabilities of the cached database query results being outdated, to automatically issue re-computation orders to the computation platform for updating cached database query results on the basis of the determined probabilities of the pre-computed database query results being outdated and to receive the updated pre-computed database query results as results of the re-computation orders. The probability determination depends on a probabilistic model and on the occurrence of asynchronous real-time events. The real-time events are indeterministic with regard to the expiration of the cached database query results and only have a probabilistic influence on the discrepancies between the cached database query results maintained in the data cache platform and presumed actual database query results.

Abstract: A data cache platform maintains pre-computed database query results computed by a computation platform based on data maintained in the computation platform and is configured to determine probabilities of the cached database query results being outdated, to automatically issue re-computation orders to the computation platform for updating cached database query results on the basis of the determined probabilities of the pre-computed database query results being outdated and to receive the updated pre-computed database query results as results of the re-computation orders. The probability determination depends on a probabilistic model and on the occurrence of asynchronous real-time events. The real-time events are indeterministic with regard to the expiration of the cached database query results and only have a probabilistic influence on the discrepancies between the cached database query results maintained in the data cache platform and presumed actual database query results.

Abstract: Methods, systems, and computer program products for processing database query results. Database query results are retrieved from a database. The database query results are classified according to multiple, distinct categories and at least one of the database query results for each of the multiple categories is stored as a featured result and then provided to a client device upon receipt of a travel search request from an end user of the client device.

Abstract: A method and system for planning and booking a trip, voyage or other travel service or product by using a social network on a network.