Natural language search results for intent queries

Abstract

Systems and methods provide natural language search results to clear-intent queries. To provide the natural language search results, a system may parse a document from an authoritative source to generate at least one heading-text pair, the text appearing under the heading in the document. The system may assign a topic and a question category to the heading-text pair and store the heading-text pair in a data store keyed by the topic and the question category. The system determines that a query corresponds to the topic and the question category, and provides the heading-text pair as a natural language search result for the query. In some implementations, the text portion of the heading-text pair may be a paragraph or a list of items and the natural language search result may be provided with conventional snippet-based search results in response to the query.

What is claimed is: 
     
         1 . A computer system comprising:
 at least one processor; and   memory storing instructions that, when executed by the at least one processor, cause the computer system to perform operations comprising:
 parsing documents from authoritative sources to generate a plurality of heading-text pairs, a heading-text pair being taken from document contents, 
 generating a set of potential templates from the heading-text pairs, 
 determining a quantity of occurrences for at least some of the set of potential templates, 
 storing potential templates with highest quantities as intent templates in a memory of the computer system; and 
 using the templates to populate a data store of heading-text pairs used to respond to natural language queries. 
   
     
     
         2 . The computer system of  claim 1 , wherein converting the heading to potential templates includes replacing subsets of consecutive terms in the heading with a variable portion. 
     
     
         3 . The computer system of  claim 1 , wherein the set of potential templates is a first set of potential templates and the memory stores instructions that, when executed by the at least one processor, cause the computer system to further perform operations including:
 determining, using search records, previously issued queries that have search results associated with the authoritative sources;   generating a second set of potential templates from the determined previously issued queries; and   including the second set of potential templates with the first set of potential templates when determining the quantity of occurrences.   
     
     
         4 . The computer system of  claim 1 , wherein the memory stores instructions that, when executed by the at least one processor, cause the computer system to further perform operations including:
 assigning a question category to the intent templates, the question category being stored as an attribute of the intent template.   
     
     
         5 . The computer system of  claim 4 , wherein the memory stores instructions that, when executed by the at least one processor, cause the computer system to further perform operations including:
 receiving a natural language query;   determining an intent template of the intent templates that corresponds to the natural language query, the intent template having an associated question category;   determining a topic for the natural language query using the intent template;   searching an index of documents for documents responsive to the topic and the associated question category; and   providing a search result to for the natural language query that includes the documents responsive to the topic and the associated question category.   
     
     
         6 . A system comprising:
 at least one processor;   a data store of heading-text pairs keyed by topic and question category, the heading-text pairs being extracted from content of authoritative sources; and   memory storing instructions that, when executed by the at least one processor, cause the system to perform operations including:
 determining that a query corresponds to an intent template of a plurality of intent templates, the intent template having an associated question category, 
 determining a topic for the query based on the intent template, 
 retrieving heading-text pairs from the data store that have a respective topic and question category key that corresponds with the topic for the query and the question category of the template, and 
 providing a search result for the query, wherein the search result includes at least one of the retrieved heading-text pairs. 
   
     
     
         7 . The system of  claim 6 , wherein the intent template includes one non-variable portion and one variable portion, and wherein corresponding the query to the intent template includes:
 determining that the query includes a first term that corresponds to the one non-variable portion;   determining that a second term in the query aligns with the variable portion; and   determining that the second term in the query corresponds to a topic in the data store.   
     
     
         8 . The system of  claim 7 , wherein corresponding the query to the intent template includes:
 generating potential templates from terms of the query; and   determining whether one of the potential templates corresponds to the intent template.   
     
     
         9 . The system of  claim 6 , the memory storing instructions that, when executed by the at least one processor, cause the system to perform further operations including:
 searching a document corpus using the topic for the query and the question category of the template as a new query instead of searching the document corpus with the query; and   providing search results from the document corpus with the at least one of the retrieved heading-text pairs.   
     
     
         10 . A method comprising:
 parsing a document from an authoritative source to generate at least one heading-text pair, the text appearing under the heading in the document;   assigning a topic and a question category to the heading-text pair;   storing the heading-text pair in a data store keyed by the topic and the question category;   determining that a query corresponds to the topic and the question category; and   providing the heading-text pair as a natural language search result for the query.   
     
     
         11 . The method of  claim 10 , further comprising:
 retrieve a plurality of heading-text pairs from the data store, each heading-text pair being keyed by the topic and the question category; and   rank the plurality of heading-text pairs; and   select a predetermined number of highest ranked heading-text pairs for the search result.   
     
     
         12 . The method of  claim 10 , further comprising:
 generate snippet-based search results by searching an index of documents for documents responsive to the query, and   provide the snippet-based search results with the natural language search result.   
     
     
         13 . The method of  claim 10 , wherein assigning a topic to the heading-text pair includes:
 identifying a topic for another heading text pair stored in the data store that matches a portion of a URL for the document and has the same question category as the heading-text pair; and   associating the heading-text pair with the topic of the other heading-text pair.   
     
     
         14 . The method of  claim 10 , wherein assigning a topic to the heading-text pair includes:
 identifying a topic for another heading-text pair stored in the data store that corresponds with dominant terms in the document and has the same question category as the heading-text pair; and   associating the heading-text pair with the topic of the other heading-text pair.   
     
     
         15 . The method of  claim 10 , wherein determining that the query corresponds to the topic and question category includes:
 determining that the query includes a topic used to key heading-text pairs in the data store; and   for each heading-text pair keyed by the topic in the data store:
 issue a second query that includes the topic and question category for the heading-text pair, 
 compare search results for the second query to search results obtained from a document corpus for the query, and 
 determine that the query corresponds to the topic and question category of the heading-text pair when search results for the second query meet a similarity threshold with regard to the search results for the query from the document corpus. 
   
     
     
         16 . The method of  claim 10 , further comprising memory storing a plurality of intent templates and wherein the heading-text pair is generated when the heading conforms to one of the plurality of intent templates. 
     
     
         17 . The method of  claim 16 , wherein the question category for the heading-text pair is determined by the intent template the heading conforms to. 
     
     
         18 . The method of  claim 10 , wherein generating the heading-text pair includes:
 determining a topic from a context of the heading in the document; and   adding the topic to a heading portion of the heading-text pair.