Abstract: A system and method is provided which may comprise parsing an unstructured geographic web-search query into a field-based format, by utilizing conditional random fields, learned by semi-supervised automated learning, to parse structured information from the unstructured geographic web-search query. The system and method may also comprise establishing semi-supervised conditional random fields utilizing one of a rule-based finite state machine model and a statistics-based conditional random field model. Systematic geographic parsing may be used with the one of the rule-based finite state machine model and the statistics-based conditional random field model. Parsing an unstructured local geographical web-based query in local domain may be done by applying a learned model parser to the query, using at least one class-based query log from a form-based query system. The learned model parser may comprise at least one class-level n-gram language model-based feature harvested from a structured query log.

Abstract: A method and system for applying a task to a crowdsourcing platform for processing are disclosed. For example, a method forwards the task having a question to the crowdsourcing platform, and receives a plurality of answers to the question, wherein the plurality of answers is provided by a plurality of workers associated with the crowdsourcing platform. The method analyzes the plurality of answers on a per-worker basis to determine an adjustment, and applies the adjustment to the plurality of answers.

Abstract: A system and method is provided which may comprise parsing an unstructured geographic web-search query into a field-based format, by utilizing conditional random fields, learned by semi-supervised automated learning, to parse structured information from the unstructured geographic web-search query. The system and method may also comprise establishing semi-supervised conditional random fields utilizing one of a rule-based finite state machine model and a statistics-based conditional random field model. Systematic geographic parsing may be used with the one of the rule-based finite state machine model and the statistics-based conditional random field model. Parsing an unstructured local geographical web-based query in local domain may be done by applying a learned model parser to the query, using at least one class-based query log from a form-based query system. The learned model parser may comprise at least one class-level n-gram language model-based feature harvested from a structured query log.

Abstract: A method and system for applying a task to a crowdsourcing platform for processing are disclosed. For example, a method forwards the task having a question to the crowdsourcing platform, and receives a plurality of answers to the question, wherein the plurality of answers is provided by a plurality of workers associated with the crowdsourcing platform. The method analyzes the plurality of answers on a per-worker basis to determine an adjustment, and applies the adjustment to the plurality of answers.