Abstract: In an approach to provide consistent job descriptions for global entities, computer-implemented methods, computer program products, and computer systems for standardizing global entity job descriptions are described. The computer-implemented method for standardizing global entity job descriptions may include one or more processors configured for receiving first job identifier data corresponding to a job posting having a plurality of job descriptions, generating second job identifier data by removing duplicate job descriptions and outlier job descriptions from the plurality of job descriptions, determining job description intents for the plurality of job descriptions based at least on the second job identifier data, generating third job identifier data corresponding to job description similarity groupings based on the job description intents and the second job identifier data, and generating fourth job identifier data comprising a standard job description based on the third job identifier data.

Abstract: A system and method for modeling preferences of customers to drive personalized contextual recommendations using cognitive deep constrained filtering includes receiving a user query on an online retail platform, in response to receiving the user query, performing a first online matrix manipulation and a second online matrix manipulation, and sending a list of ranked recommended products.

Abstract: An approach is provided for evaluating a recommender system. A user's purchase date of an item and attributes of the item are extracted from a test set. Drop probabilities are assigned to the attributes. Using bootstrapping with aggregation, queries for the user and the item are generated by omitting one or more attributes from each of the queries according to the drop probabilities. Data that became available to the recommender system after the purchase date is identified. Without using the identified data and using data that became available to the recommender system before the purchase date, ranked item recommendation sets for the queries are generated. Similarity at rank K (SIM@K) values for the recommendation sets are calculated. Average SIM@K values are calculated over multiple users specified in the test set. Based on the average SIM@K values, the performance of the recommender system is evaluated.

Abstract: A system and method for modeling preferences of customers to drive personalized contextual recommendations using cognitive deep constrained filtering includes receiving a user query on an online retail platform, in response to receiving the user query, performing a first online matrix manipulation and a second online matrix manipulation, and sending a list of ranked recommended products.

Abstract: Methods, systems, and computer readable storage media are disclosed that aid migration team members with migrating software applications from one platform to another platform, and more particularly, with tools that aid in migrating mainframe applications to a lower cost platform. The tools include legacy statistical generators that scan and analyze components of a mainframe application as well as the datasets associated with the mainframe application. The legacy statistical generators as a result of such analysis extract various statistical information regarding the application and datasets and provide such extracted information to a web-enabled application. Migration team members may use the web-enabled application to gain insight into the structure of the mainframe application as well as determine progress of migrating the mainframe application to the lower cost platform.

Abstract: Methods, systems, and computer readable storage media are disclosed that aid migration team members with migrating software applications from one platform to another platform, and more particularly, with tools that aid in migrating mainframe applications to a lower cost platform. The tools include legacy statistical generators that scan and analyze components of a mainframe application as well as the datasets associated with the mainframe application. The legacy statistical generators as a result of such analysis extract various statistical information regarding the application and datasets and provide such extracted information to a web-enabled application. Migration team members may use the web-enabled application to gain insight into the structure of the mainframe application as well as determine progress of migrating the mainframe application to the lower cost platform.

Abstract: Methods, systems, and computer readable storage media are disclosed that aid migration team members with migrating software applications from one platform to another platform, and more particularly, with tools that aid in migrating mainframe applications to a lower cost platform. The tools include legacy statistical generators that scan and analyze components of a mainframe application as well as the datasets associated with the mainframe application. The legacy statistical generators as a result of such analysis extract various statistical information regarding the application and datasets and provide such extracted information to a web-enabled application. Migration team members may use the web-enabled application to gain insight into the structure of the mainframe application as well as determine progress of migrating the mainframe application to the lower cost platform.