Abstract: Systems, methods and articles of manufacture for determining the relevancy of tax matters to a particular taxpayer and prioritizing the tax matters in a tax preparation system for preparing an electronic tax return. A computerized tax preparation system accesses taxpayer data and generates a taxpayer data profile using the taxpayer data. The system executes at tax logic agent which evaluates missing tax data required to prepare the tax return for the taxpayer and outputs a plurality of suggested tax matters for obtaining the missing tax data to a user interface manager. The tax logic agent utilizes the taxpayer data profile and a tax matter relevancy module having a plurality of tax data profiles to determine a relevancy ranking for each suggested tax matter. A user interface manager receives the suggested tax matters and the corresponding relevancy rankings and determines one or more tax questions to present to the user.

Abstract: Computer-implemented methods, systems and articles of manufacture detecting inconsistent electronic tax return data. In a tax return preparation application in which a tax logic agent and user interface controller share a data store, and the tax logic agent including or executing a cross-field validation engine is separate from or loosely coupled to a user interface controller, the tax logic agent reads runtime data of the electronic tax return from the data store, and the validation engine compares runtime data cross-field rule conditions. A cross-field rule having a condition that is not satisfied by the runtime data is identified, and a non-binding suggestion is generated by the tax logic agent and received by the user interface controller, which generates an interview screen concerning the detected inconsistency for display to the user.

Abstract: Computer-implemented methods, system and computer program products for determining questions or potential questions to present to a user of a tax preparation application based at least in part upon analysis of pre-determined semantic dependencies of interview questions. Questions that are determined to be independent or free of semantic dependency can be selected as questions to be presented to the user or questions that are the subject of non-binding suggestions generated by a rule module and provided to an interface controller, which processes the non-binding suggestions.

Abstract: Systems, methods and articles of manufacture for determining the relevancy of tax matters to a particular taxpayer and prioritizing the tax matters in a tax preparation system for preparing an electronic tax return. A computerized tax preparation system accesses taxpayer data and generates a taxpayer data profile using the taxpayer data. The system executes at tax logic agent which evaluates missing tax data required to prepare the tax return for the taxpayer and outputs a plurality of suggested tax matters for obtaining the missing tax data to a user interface manager. The tax logic agent utilizes the taxpayer data profile and a tax matter relevancy module having a plurality of tax data profiles to determine a relevancy ranking for each suggested tax matter. A user interface manager receives the suggested tax matters and the corresponding relevancy rankings and determines one or more tax questions to present to the user.

Abstract: Computer-implemented methods, system and computer program products for determining questions or potential questions to present to a user of a tax preparation application based at least in part upon analysis of pre-determined semantic dependencies of interview questions. Questions that are determined to be independent or free of semantic dependency can be selected as questions to be presented to the user or questions that are the subject of non-binding suggestions generated by a rule module and provided to an interface controller, which processes the non-binding suggestions.