Abstract:
Various embodiments include systems and methods for generating query rewrite records which may be used to generate standardized query rewrites for a search engine. Such records may identify rewrite triggers as well as constraints and other metadata flags which may be associated with certain rewrites in query rewrite identification (QRIL) records. In certain embodiments, such records may be analyzed with other QRIL records or rewrite information to prevent rewrite conflicts and to generate standardized rewrites. This information may then be used by a search engine to generate responses to user queries.
Abstract:
Various embodiments include systems and methods tier processing query rewrite records to generate standardized query rewrites usable by a search engine. Such systems and method may involve analysis of query rewrite input language (QRIL) records to identify relationships and conflicts between multiple QRIL records, and to resolve these relationships and conflicts to generate a standardized rewrite in a semantic language recognizable by the search engine. Such systems and methods may gather QRIL records from a QRIL record database, process the QRIL records using precedence rules, and then communicate a set of standardized and optimized query rewrites to the search engine.
Abstract:
Various embodiments include systems and methods for data mining of search engine and network operations to automatically identify query events. Data aggregated from such query events and stored as query history data may be processed to identify query ranking mismatches. These identified mismatches may be used with the query history data and target settings to automatically generate query rewrite data. In certain embodiments, this query rewrite data may be used to generate query rewrite input language (QRIL) records. Such QRIL records may then be used to automatically generate standardized rewrites which automatically resolve any conflicts between rewrites in a particular search engine.
Abstract:
Various embodiments include systems and methods for data mining of search engine and network operations to automatically identify query events. Data aggregated from such query events and stored as query history data may be processed to identify query ranking mismatches. These identified mismatches may be used with the query history data and target settings to automatically generate query rewrite data. In certain embodiments, this query rewrite data may be used to generate query rewrite input language (QRIL) records. Such QRIL records may then be used to automatically generate standardized rewrites which automatically resolve any conflicts between rewrites in a particular search engine.
Abstract:
Various embodiments include systems and methods tier processing query rewrite records to generate standardized query rewrites usable by a search engine. Such systems and method may involve analysis of query rewrite input language (QRIL) records to identify relationships and conflicts between multiple QRIL records, and to resolve these relationships and conflicts to generate a standardized rewrite in a semantic language recognizable by the search engine. Such systems and methods may gather QRIL records from a QRIL record database, process the QRIL records using precedence rules, and then communicate a set of standardized and optimized query rewrites to the search engine.
Abstract:
Various embodiments include systems and methods for generating query rewrite records which may be used to generate standardized query rewrites for a search engine. Such records may identify rewrite triggers as well as constraints and other metadata flags which may be associated with certain rewrites in query rewrite identification (QRIL) records. In certain embodiments, such records may he analyzed with other QRIL records or rewrite information to prevent rewrite conflicts and to generate standardized rewrites. This information may then be used by a search engine to generate responses to user queries.
Abstract:
Various embodiments include systems and methods for data mining of search engine and network operations to automatically identify query events. Data aggregated from such query events and stored as query history data may be processed to identify query ranking mismatches. These identified mismatches may be used with the query history data and target settings to automatically generate query rewrite data. In certain embodiments, this query rewrite data may be used to generate query rewrite input language (QRIL) records. Such QRIL records may then be used to automatically generate standardized rewrites which automatically resolve any conflicts between rewrites in a particular search engine.