Abstract: Technologies are described here for, among other things, improving search query relevance by executing a query on a search engine, retrieving search-page-data generated from executing the query, the search-page-data including document-titles and universal resource locators (URLs), each document-title being a title of a document associated with a URL, determining relevant-entity-words in the query from an entity relevance score for matching search terms in the query, Domain-URLs, and Domain-Titles, determining relevant-intent-words in the query from an intent-word relevance score based on a number of times a search term appears in the query and the URLs relative to other search terms in the query and the URLs, comparing each of the determined relevant-entity-words and each of the determined relevant-intent-words with a plurality of stored past-user queries, retrieving the plurality of stored past-user search queries including the relevant-entity-words and the relevant-intent-words, and transmitting a set of qu

Abstract: Technologies are described here for, among other things, improving search query relevance by executing a query on a search engine, retrieving search-page-data generated from executing the query, the search-page-data including document-titles and universal resource locators (URLs), each document-title being a title of a document associated with a URL, determining relevant-entity-words in the query from an entity relevance score for matching search terms in the query, Domain-URLs, and Domain-Titles, determining relevant-intent-words in the query from an intent-word relevance score based on a number of times a search term appears in the query and the URLs relative to other search terms in the query and the URLs, comparing each of the determined relevant-entity-words and each of the determined relevant-intent-words with a plurality of stored past-user queries, retrieving the plurality of stored past-user search queries including the relevant-entity-words and the relevant-intent-words, and transmitting a set of qu

Abstract: A method for a search engine to provide domain-agnostic options for structured exploration based on a query. The method comprises clustering a corpus of historical queries into a plurality of query clusters. The method further comprises identifying a set of variable query terms in each query cluster. Then, a query structure of a new user query is identified, and a specific query cluster matching the query structure of the new user query is selected. Furthermore, the variable query term in the query structure of the new user query is identified. The method further comprises providing a query exploration interface offering user-selectable options for structured exploration of the new user query. Each of the user-selectable option corresponds to a variable query term in the identified set of variable query terms for the specific query cluster identified as matching the query structure of the new user query.

Abstract: A method for a search engine to provide domain-agnostic options for structured exploration based on a query. The method comprises clustering a corpus of historical queries into a plurality of query clusters. The method further comprises identifying a set of variable query terms in each query cluster. Then, a query structure of a new user query is identified, and a specific query cluster matching the query structure of the new user query is selected. Furthermore, the variable query term in the query structure of the new user query is identified. The method further comprises providing a query exploration interface offering user-selectable options for structured exploration of the new user query. Each of the user-selectable option corresponds to a variable query term in the identified set of variable query terms for the specific query cluster identified as matching the query structure of the new user query.

Abstract: Technologies are described here for, among other things, improving search query relevance by executing a query on a search engine, retrieving search-page-data generated from executing the query, the search-page-data including document-titles and universal resource locators (URLs), each document-title being a title of a document associated with a URL, determining relevant-entity-words in the query from an entity relevance score for matching search terms in the query, Domain-URLs, and Domain-Titles, determining relevant-intent-words in the query from an intent-word relevance score based on a number of times a search term appears in the query and the URLs relative to other search terms in the query and the URLs, comparing each of the determined relevant-entity-words and each of the determined relevant-intent-words with a plurality of stored past-user queries, retrieving the plurality of stored past-user search queries including the relevant-entity-words and the relevant-intent-words, and transmitting a set of qu

Abstract: A method for a search engine to provide domain-agnostic options for structured exploration based on a query. The method comprises clustering a corpus of historical queries into a plurality of query clusters. The method further comprises identifying a set of variable query terms in each query cluster. Then, a query structure of a new user query is identified, and a specific query cluster matching the query structure of the new user query is selected. Furthermore, the variable query term in the query structure of the new user query is identified. The method further comprises providing a query exploration interface offering user-selectable options for structured exploration of the new user query. Each of the user-selectable option corresponds to a variable query term in the identified set of variable query terms for the specific query cluster identified as matching the query structure of the new user query.

Abstract: Technologies are described here for, among other things, improving search query relevance by executing a query on a search engine, retrieving search-page-data generated from executing the query, the search-page-data including document-titles and universal resource locators (URLs), each document-title being a title of a document associated with a URL, determining relevant-entity-words in the query from an entity relevance score for matching search terms in the query, Domain-URLs, and Domain-Titles, determining relevant-intent-words in the query from an intent-word relevance score based on a number of times a search term appears in the query and the URLs relative to other search terms in the query and the URLs, comparing each of the determined relevant-entity-words and each of the determined relevant-intent-words with a plurality of stored past-user queries, retrieving the plurality of stored past-user search queries including the relevant-entity-words and the relevant-intent-words, and transmitting a set of qu