ORDERING SEMANTIC QUERY FORMULATION SUGGESTIONS
Methods are provided for ordering semantically-identified query formulation suggestions. Semantic query patterns are identified for a plurality of search queries and a weight is identified for each. Also identified is a plurality of semantic categories, each having an identified weight. Terms/phrases commonly associated with the semantic categories are identified, as are semantic attributes as they pertain to the semantic categories. Semantic attribute patterns and respective weights therefore are identified. A text-parser is generated from the semantic query patterns and respective weights, the semantic category terms, and the semantic attribute patterns and respective weights, the text-parser for use in parsing input user queries or portions thereof. Upon receiving a user search query, the text-parser is applied to determine at least one likely attribute, attribute value, or term commonly associated with a semantic category, and the determined attribute/attribute value/term is transmitted for presentation with an order representative of the respective calculated weights.
1 . One or more computer-storage media storing computer-useable instructions that, when used by a computing device, cause the computing device to perform a method, comprising:
receiving a plurality of search queries from a query log, each of the plurality of search queries being associated with a respective set of matching entities;
identifying at least one semantic query pattern from the plurality of search queries;
identifying a plurality of semantic categories from an entity database, each of the plurality of semantic categories being associated with a respective set of entities;
identifying at least one term commonly associated with at least one of the semantic categories;
identifying a plurality of semantic attributes as they pertain to the plurality of semantic categories;
identifying at least one semantic attribute pattern from the plurality of semantic attributes; and
customizing a text-parser, at least in part, utilizing the at least one semantic query pattern, the at least one semantic category term, and the at least one semantic attribute patterns, the text parser for use in parsing input user queries or portions thereof.
2 . The one or more computer-storage media of claim 1 , wherein the method further comprises:
identifying a weight for each identified semantic query pattern; and
identifying a weight for each identified semantic attribute pattern.
3 . The one or more computer-storage media of claim 2 , wherein utilizing a text-parser generated, at least in part, from the at least one semantic query pattern, the at least one semantic category term, and the at least one semantic attribute patterns, comprises utilizing a text-parser generated, at least in part, from the at least one semantic query pattern and respective weights, the at least one semantic category term, and the at least one semantic attribute patterns and respective weights, the text parser for use in parsing user queries or portions thereof.
4 . The one or more computer-storage media of claim 1 , wherein identifying at least one term commonly associated with at least one of the semantic categories comprises identifying at least one phrase commonly associated with at least one of the semantic categories.
5 . The one or more computer-storage media of claim 1 , wherein identifying at least one term commonly associated with at least one of the semantic categories comprises identifying at least one n-gram commonly associated with at least one of the semantic categories.
6 . The one or more computer-storage media of claim 2 , wherein the method further comprises:
receiving at least a portion of an input user search query;
applying the text-parser to determine at least one likely attribute, attribute value, term, or combination thereof for expansion of the input user query; and
transmitting the at least one likely attribute, attribute value, term, or combination thereof for presentation as an attribute suggestion.
7 . The one or more computer-storage media of claim 6 , wherein applying the text-parser to determine at least one likely attribute, attribute value, term, or combination thereof for expansion of the input user query comprises applying the text-parser to determine a plurality of likely attributes, attribute values, terms, or any combination thereof for expansion of the input user query, each of the plurality of likely attributes, attribute values, terms, or any combination thereof having a calculated weight associated therewith.
8 . The one or more computer-storage media of claim 7 , wherein transmitting the at least one likely attribute, attribute value, term, or combination thereof for presentation as an attribute suggestion comprises transmitting at least a portion of the plurality of likely attributes, attribute values, terms or any combination thereof for presentation as attribute suggestions, the attribute suggestions representing the plurality of likely attributes, attribute values, terms, any combination thereof, or any portion thereof that are transmitted for presentation being arranged in an order representing their respective calculated weights.
9 . A method performed by a computing device having a processor and a memory for generating query formulation suggestions, the method comprising:
receiving a plurality of search queries from a query log, each of the plurality of search queries being associated with a respective set of matching entities;
identifying at least one semantic query pattern from the plurality of search queries;
identifying a weight for each identified semantic query pattern;
identifying a plurality of semantic categories from an entity database, each of the plurality of semantic categories being associated with a respective set of entities;
identifying at least one term commonly associated with at least one of the semantic categories;
identifying a plurality of semantic attributes as they pertain to the plurality of semantic categories;
identifying at least one semantic attribute pattern from the plurality of semantic attributes;
identifying a weight for each identified semantic attribute pattern; and
customizing a text-parser, at least in part, utilizing the at least one semantic query pattern and respective weights, the at least one semantic category term, and the at least one semantic attribute patterns and respective weights, the text-parser for use in parsing input user queries or portions thereof.
10 . The method of claim 9 , wherein identifying at least one term commonly associated with at least one of the semantic categories comprises identifying at least one phrase commonly associated with at least one of the semantic categories.
11 . The method of claim 9 , wherein identifying at least one term commonly associated with at least one of the semantic categories comprises identifying at least one n-gram commonly associated with at least one of the semantic categories.
12 . The method of claim 9 , wherein the method further comprises:
receiving at least a portion of an input user search query;
applying the text-parser to determine at least one likely attribute, attribute value, term, or combination thereof for expansion of the input user query; and
transmitting the at least one likely attribute, attribute value, term, or combination thereof for presentation as an attribute suggestion.
13 . The method of claim 12 , wherein applying the text-parser to determine at least one likely attribute, attribute value, term, or combination thereof for expansion of the input user query comprises applying the text-parser to determine a plurality of likely attributes, attribute values, terms, or any combination thereof for expansion of the input user query, each of the plurality of likely attributes, attribute values, terms, or any combination thereof having a calculated weight associated therewith.
14 . The method of claim 13 , wherein transmitting the at least one likely attribute, attribute value, term, or combination thereof for presentation as an attribute suggestion comprises transmitting at least a portion of the plurality of likely attributes, attribute values, terms or any combination thereof for presentation as attribute suggestions, the attribute suggestions representing the plurality of likely attributes, attribute values, terms, any combination thereof, or any portion thereof that are transmitted for presentation being arranged in an order representing their respective calculated weights.
15 . One or more computer-storage media storing computer-useable instructions that, when used by a computing device, cause the computing device to perform a method for ordering query formulation suggestions, the method comprising:
receiving a plurality of search queries from a query log, each of the plurality of search queries being associated with a respective set of matching entities;
identifying at least one semantic query pattern from the plurality of search queries;
identifying a weight for each identified semantic query pattern;
identifying a plurality of semantic categories from an entity database, each of the plurality of semantic categories being associated with a respective set of entities;
identifying at least one term commonly associated with at least one of the semantic categories;
identifying a plurality of semantic attributes as they pertain to the plurality of semantic categories;
identifying at least one semantic attribute pattern from the plurality of semantic attributes;
identifying a weight for each identified semantic attribute pattern;
customizing a text-parser, at least in part, utilizing the at least one semantic query pattern and respective weights, the at least one semantic category term, and the at least one semantic attribute patterns and respective weights, the text parser for use in parsing input user queries or portions thereof;
receiving at least a portion of an input user search query;
applying the text-parser to determine at least one likely attribute, attribute value, term, or combination thereof for expansion of the input user query; and
transmitting the at least one likely attribute, attribute value, term, or combination thereof for presentation as an attribute suggestion, the attribute suggestions representing the plurality of likely attributes, attribute values, terms, any combination thereof, or any portion thereof that are transmitted for presentation being arranged in an order representing their respective calculated weights.
16 . The one or more computer-storage media of claim 15 , wherein identifying at least one term commonly associated with at least one of the semantic categories comprises identifying at least one phrase commonly associated with at least one of the semantic categories.
17 . The one or more computer-storage media of claim 15 , wherein identifying at least one term commonly associated with at least one of the semantic categories comprises identifying at least one n-gram commonly associated with at least one of the semantic categories.
18 . The one or more computer-storage media of claim 15 , wherein applying the text-parser to determine at least one likely attribute, attribute value, term, or combination thereof for expansion of the input user query comprises applying the text-parser to determine a plurality of likely attributes, attribute values, terms, or any combination thereof for expansion of the input user query, each of the plurality of likely attributes, attribute values, terms, or any combination thereof having a calculated weight associated therewith.
19 . The one or more computer-storage media of claim 15 , wherein transmitting the at least one likely attribute, attribute value, term, or combination thereof for presentation as an attribute suggestion comprises transmitting at least a portion of the plurality of likely attributes, attribute values, terms or any combination thereof for presentation as attribute suggestions, the attribute suggestions representing the plurality of likely attributes, attribute values, terms, any combination thereof, or any portion thereof that are transmitted for presentation being arranged in an order representing their respective calculated weights.