Abstract: There is a need for more effective and efficient detection of cross-data-column relationships. This need can be addressed by, for example, techniques for detecting cross-data-column data relationships that utilize at least one of feature-based similarity models and deep-learning-based similarity models. The cross-data-column data relationships may be displayed to an end-user using a cross-column relationship detection user interface.

Abstract: There is a need for more effective and efficient detection of cross-data-column relationships. This need can be addressed by, for example, techniques for detecting cross-data-column data relationships that utilize at least one of feature-based similarity models and deep-learning-based similarity models. The cross-data-column data relationships may be displayed to an end-user using a cross-column relationship detection user interface.

Abstract: In general, embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for software process failure prevention are provided herein. Such embodiments may include steps of: generating error logs at one or more phases of a software process lifecycle; preprocessing each error log to standardize error log data; grouping the preprocessed error logs based on similar characteristics of the preprocessed error logs; associating each group of preprocessed error logs with one or more discrete events of the software process lifecycle; converting each preprocessed error log into a sequence of associated discrete events of the software process lifecycle; merging redundant sequences of associated discrete events of the software process lifecycle; and identifying one or more error causing patterns for software process failure prediction from the sequences of associated discrete events of the software process lifecycle.

Abstract: In general, embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for software process failure prevention are provided herein. Such embodiments may include steps of: generating error logs at one or more phases of a software process lifecycle; preprocessing each error log to standardize error log data; grouping the preprocessed error logs based on similar characteristics of the preprocessed error logs; associating each group of preprocessed error logs with one or more discrete events of the software process lifecycle; converting each preprocessed error log into a sequence of associated discrete events of the software process lifecycle; merging redundant sequences of associated discrete events of the software process lifecycle; and identifying one or more error causing patterns for software process failure prediction from the sequences of associated discrete events of the software process lifecycle.

Abstract: The present invention provides a method and system for recommending an optimal shopping path to a user. A shopping layout of a shopping store is downloaded on a handheld device. A shopping list is received from the user, comprising one or more shopping items. A final shopping list is created by appending one or more additional shopping items to the shopping list. The optimal shopping path representing a shortest path on the shopping layout traversing each shopping item of the final shopping list is generated.