Techniques for natural language searches are described. In an example, a computer system receives a search associated with a computing device. Based on the search, the computer system determines first search results from a first data source and associated with a first type and second search results from a second data source and associated with a type. The computer system also determines a context associated with at least one of the computing device or a user. Based on the context, the computer system generates instructions associated with a presentation of the first search results and the second search results at a user interface of the computing device. The instructions indicate a first presentation order of the first search results and the second search results and a second presentation order of search results within the first search results. The computer system sends the instructions to the computing device.

Techniques for natural language searches are described. In an example, a computer system receives a search associated with a computing device. Based on the search, the computer system determines first search results from a first data source and associated with a first type and second search results from a second data source and associated with a type. The computer system also determines a context associated with at least one of the computing device or a user. Based on the context, the computer system generates instructions associated with a presentation of the first search results and the second search results at a user interface of the computing device. The instructions indicate a first presentation order of the first search results and the second search results and a second presentation order of search results within the first search results. The computer system sends the instructions to the computing device.

Analytics system onboarding of web content is described. In one example, an analytics onboarding system is configured to process web content to generate recommendations, automatically and without user intervention. The recommendations are configured to assist in mapping of web content variables in web content to data elements supported by an analytics system to generate metrics that describe occurrence of events as part of user interaction with web content.

Analytics system onboarding of web content is described. In one example, an analytics onboarding system is configured to process web content to generate recommendations, automatically and without user intervention. The recommendations are configured to assist in mapping of web content variables in web content to data elements supported by an analytics system to generate metrics that describe occurrence of events as part of user interaction with web content.

A system and method are disclosed for creating solution design blueprints. A solution design blueprint is a machine-readable data structure that includes a conceptual design model for an application framework. A user interface is configured to receive a plain language textual request from a user that describes a desired application or solution to a problem. Artificial Intelligence is leveraged to fit the textual request to semantic data models and map elements of the textual request to components of a design library. The resulting solution design blueprint can be presented to a user, and the user interface can be used to provide feedback related to the solution design blueprint that can be utilized to update machine learning algorithms and/or neural networks. In some embodiments, the solution design blueprint can be converted to an application framework that is provided to the use in an integrated development environment of the user interface.

An improved search engine is disclosed. The search engine receives search queries from client devices and inputs these queries into a first neural network (an action understanding model) that includes an action embedding layer. The action embedding layer can be a word embedding layer constructed using action terms. The action understanding model outputs a filter match associated with a type of filter and, in some scenarios, an action-condition pair. The action-condition pair includes an action associated with the type of filter and a condition comprising an adaptive value associated with the action. Based on the filter and, if present, action-condition pair(s), the embodiments generate a structured query and issue the structured query to a data repository (e.g., database). The search engine then returns a search results page responsive to the search query that includes the results returned by the data repository in response to the structured query.

An improved search engine is disclosed. The search engine receives search queries from client devices and inputs these queries into a first neural network (an action understanding model) that includes an action embedding layer. The action embedding layer can be a word embedding layer constructed using action terms. The action understanding model outputs a filter match associated with a type of filter and, in some scenarios, an action-condition pair. The action-condition pair includes an action associated with the type of filter and a condition comprising an adaptive value associated with the action. Based on the filter and, if present, action-condition pair(s), the embodiments generate a structured query and issue the structured query to a data repository (e.g., database). The search engine then returns a search results page responsive to the search query that includes the results returned by the data repository in response to the structured query.

Disclosed are techniques for faceted search queries through interactive graphical objects. A text search query corresponding to a faceted search is received from a user, which is then parsed for keywords. Attributes associated with the keywords are then extracted and used to generate a graphical representation corresponding to the results associated with the text search query. Further user input to refine the query is provided through manipulation of the graphical representation by the user (such as dragging a leg of a table to change the length of legs on a table) corresponding to modification of one or more facets of the faceted search, narrowing the available search results corresponding to the faceted search.

Disclosed are techniques for faceted search queries through interactive graphical objects. A text search query corresponding to a faceted search is received from a user, which is then parsed for keywords. Attributes associated with the keywords are then extracted and used to generate a graphical representation corresponding to the results associated with the text search query. Further user input to refine the query is provided through manipulation of the graphical representation by the user (such as dragging a leg of a table to change the length of legs on a table) corresponding to modification of one or more facets of the faceted search, narrowing the available search results corresponding to the faceted search.

A computer-implemented method for generating a search query completion suggestion by a search engine by receiving an indication of at least a portion of a search query from an electronic device; generating, based on the indication, a ranked set of search query completion suggestions; analyzing a top one of the ranked set of search query completion suggestions to determine if the top one of the ranked set of search query completion suggestions meets a pre-determined trigger condition; in response to a positive outcome, generating a set of search results that are responsive to an intermediate search query that includes the at least the portion of the search query and the top one of the ranked set of search query completion suggestions; transmitting to the electronic device: the ranked set of search query completion suggestions; and a Search Engine Result Page (SERP) containing the set of search results.