Abstract: Artificial intelligence for next best action. In an embodiment, contact data and contact-specific activity data are received from a user system. A profile model is applied to the contact data to generate a profile score for each contact, and an intent model is applied to the contact-specific activity data to generate an intent score for each contact. Contact recommendations are determined based on the profile scores and the intent scores, and a recommended contact list is generated based on the contact recommendations. The recommended contact list may then be provided to a user.

Abstract: Artificial intelligence for keyword recommendations. In an embodiment, raw keyword data are received. The raw keyword data comprise keyword activity records that each comprises a uniform resource locator (URL) for an online resource and metadata for the online resource. Arrays of keywords are extracted from the keyword activity records, with each array of keywords associated with the URL in the keyword activity record from which the array of keywords was extracted. User-specified keyword(s) are received, and a subset of the arrays of keywords that match at least one of the user-specified keyword(s) is identified. A training dataset is generated from the subset, and used to train a machine-learning model to output recommended keywords based on an input keyword.

Abstract: The disclosure herein describes generating test data based on a set of linked data nodes and associated data value rules. A plurality of data fields of a data structure is identified. A plurality of linked data nodes is generated based on the identified data fields, wherein each data node comprises a probability value and data value rules for generating data values for the data fields. Parent nodes of the linked data nodes are collapsed into associated child nodes to form combined data nodes. Test data values for the plurality of data fields are generated based on the combined data nodes and a data structure instance is populated with the generated test data values. The populated data structure instance is provided for use in executing tests. The generation of test data based on the data value rules of linked data nodes provides a realistic data environment for testing.

Abstract: The disclosure herein describes generating test data based on a set of linked data nodes and associated data value rules. A plurality of data fields of a data structure is identified. A plurality of linked data nodes is generated based on the identified data fields, wherein each data node comprises a probability value and data value rules for generating data values for the data fields. Parent nodes of the linked data nodes are collapsed into associated child nodes to form combined data nodes. Test data values for the plurality of data fields are generated based on the combined data nodes and a data structure instance is populated with the generated test data values. The populated data structure instance is provided for use in executing tests. The generation of test data based on the data value rules of linked data nodes provides a realistic data environment for testing.