Abstract: A training query generation system is usable to generate fully formed training questions from prior search queries, some of which may be fully formed search queries and some of which are not fully formed. The system may identify fully formed questions from a query database stored on a storage device. The query database includes a plurality of search query character string, The system further identifies partially formed questions from the query database, creates question templates from the identified fully formed questions, and stores the question templates in a template database. The system then identifies entities with the partially formed questions, classifies each entity, and stores the classified entities in an entity database. Fully formed questions can then be generated using the question templates from the template database and classified entities from the entity database.

Abstract: Embodiments provide a computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to implement a full question generation system, the method comprising ingesting a query dataset derived from one or more search queries entered by one or more users of an internet search engine; identifying questions from the ingested query dataset; separating one or more prior full questions from the ingested dataset; identifying one or more question intent queries from the query dataset; for each identified question intent query; sorting the question intent query into one or more bins based on one or more missing interrogative words; and appending the missing interrogative word and a verb onto the question intent query to generate a full question. The full question generation method can additionally generate un-canonical questions.

Abstract: Embodiments provide a computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to implement a full question generation system, the method comprising ingesting, into the full question generation system, a query dataset derived from one or more search queries entered by one or more users of an internet search engine; identifying questions from the ingested query dataset; separating, through a full question identification module, one or more prior full questions from the ingested dataset; identifying, through a question intent query identification module, one or more question intent queries from the query dataset; for each identified question intent query: sorting, through a sorting module, the question intent query into one or more bins based on one or more missing interrogative words; and appending, through an appending module, the missing interrogative word and a verb onto the question intent

Abstract: A training query generation system is usable to generate fully formed training questions from prior search queries, some of which may be fully formed search queries and some of which are not fully formed. The system may identify fully formed questions from a query database stored on a storage device. The query database includes a plurality of search query character string, The system further identifies partially formed questions from the query database, creates question templates from the identified fully formed questions, and stores the question templates in a template database. The system then identifies entities with the partially formed questions, classifies each entity, and stores the classified entities in an entity database. Fully formed questions can then be generated using the question templates from the template database and classified entities from the entity database.

Abstract: A training query generation system is usable to generate fully formed training questions from prior search queries, The system may include a training dataset generation service that is configured to receive a message containing an indicator of a topic over a network, access a template database containing a plurality of question templates and associated topic indicators, each question template including one or more argument values indicative of a role, and select those question templates from the template database that match the received topic indicator. The training dataset generation service also is configured to select entities from an entity database that map to the argument values of the selected question templates and generate a plurality of fully formed questions, each generated fully formed question comprising a character string containing the question template and at least one of the selected agents.

Abstract: Embodiments provide a computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to implement a full question generation system, the method comprising ingesting a query dataset derived from one or more search queries entered by one or more users of an internet search engine; identifying questions from the ingested query dataset; separating one or more prior full questions from the ingested dataset; identifying one or more question intent queries from the query dataset; for each identified question intent query; sorting the question intent query into one or more bins based on one or more missing interrogative words; and appending the missing interrogative word and a verb onto the question intent query to generate a full question. The full question generation method can additionally generate un-canonical questions.

Abstract: Embodiments provide a computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to implement a full question generation system, the method comprising ingesting, into the full question generation system, a query dataset derived from one or more search queries entered by one or more users of an internet search engine; identifying questions from the ingested query dataset; separating, through a full question identification module, one or more prior full questions from the ingested dataset; identifying, through a question intent query identification module, one or more question intent queries from the query dataset; for each identified question intent query: sorting, through a sorting module, the question intent query into one or more bins based on one or more missing interrogative words; and appending, through an appending module, the missing interrogative word and a verb onto the question intent