Abstract: A computing device hosting a website of a business may be operable to receive a first search input comprising a term submitted via a search bar on the website. Upon performing an internal search for the term with no result, the computing device may output information on the no-result. The computing device may then perform, using one or more external search engines, a search for the term. Search results of the search, performed using the external search engine(s), may be analyzed. Based on a result of the analysis, one or more particular character strings related to the term may be identified. The computing device may generate and store, based on the identifying of the particular character string(s), one or more alternative search suggestions. Upon subsequently receiving an input comprising at least a portion of the term entered in the search bar, the computing device may output the alternative search suggestion(s).

Abstract: A computing device hosting a website of a business may be operable to receive a first search input comprising a term submitted via a search bar on the website. Upon performing an internal search for the term with no result, the computing device may output information on the no-result. The computing device may then perform, using one or more external search engines, a search for the term. Search results of the search, performed using the external search engine(s), may be analyzed. Based on a result of the analysis, one or more particular character strings related to the term may be identified. The computing device may generate and store, based on the identifying of the particular character string(s), one or more alternative search suggestions. Upon subsequently receiving an input comprising at least a portion of the term entered in the search bar, the computing device may output the alternative search suggestion(s).

Abstract: Methods of operating a search engine may include calculating multi-modal document vector models for each of a plurality of electronic documents, training category-specific, search query-specific ranking models with respective machine learning algorithms based on those document vector models, and applying each of those models to further instances of the same search query to rank the documents responsive to that search query.

Abstract: A method for operating a search engine may include determining a multi-dimensional search parameter space comprising a set of possible weight values for each of a plurality of search parameters and dividing the search parameter space into a grid of evenly-spaced values that is a subset of the set of possible values. The method may further include defining one or more initial populations of search parameter weight values, wherein each population of search parameter weight values comprises a plurality of initial individuals, wherein each initial individual comprises a respective one of the evenly-spaced values for each of the search parameters. The method may further include executing one or more genetic algorithms based on the one or more initial populations to select a final set of search parameter weight values, and returning results of a user search in the search engine according to the final set of search parameter weight values.

Abstract: A method for operating a search engine may include determining a multi-dimensional search parameter space comprising a set of possible weight values for each of a plurality of search parameters and dividing the search parameter space into a grid of evenly-spaced values that is a subset of the set of possible values. The method may further include defining one or more initial populations of search parameter weight values, wherein each population of search parameter weight values comprises a plurality of initial individuals, wherein each initial individual comprises a respective one of the evenly-spaced values for each of the search parameters. The method may further include executing one or more genetic algorithms based on the one or more initial populations to select a final set of search parameter weight values, and returning results of a user search in the search engine according to the final set of search parameter weight values.

Abstract: A computing device hosting a website of a business may be operable to receive a first search input comprising a term submitted via a search bar on the website. Upon performing an internal search for the term with no result, the computing device may output information on the no-result. The computing device may then perform, using one or more external search engines, a search for the term. Search results of the search, performed using the external search engine(s), may be analyzed. Based on a result of the analysis, one or more particular character strings related to the term may be identified. The computing device may generate and store, based on the identifying of the particular character string(s), one or more alternative search suggestions. Upon subsequently receiving an input comprising at least a portion of the term entered in the search bar, the computing device may output the alternative search suggestion(s).

Abstract: Methods of operating a search engine may include calculating multi-modal document vector models for each of a plurality of electronic documents, training category-specific, search query-specific ranking models with respective machine learning algorithms based on those document vector models, and applying each of those models to further instances of the same search query to rank the documents responsive to that search query.

Abstract: A computing device hosting a website of a business may be operable to receive a first search input comprising a term submitted via a search bar on the website. Upon performing an internal search for the term with no result, the computing device may output information on the no-result. The computing device may then perform, using one or more external search engines, a search for the term. Search results of the search, performed using the external search engine(s), may be analyzed. Based on a result of the analysis, one or more particular character strings related to the term may be identified. The computing device may generate and store, based on the identifying of the particular character string(s), one or more alternative search suggestions. Upon subsequently receiving an input comprising at least a portion of the term entered in the search bar, the computing device may output the alternative search suggestion(s).

Abstract: Methods of operating a search engine may include calculating multi-modal document vector models for each of a plurality of electronic documents, training category-specific, search query-specific ranking models with respective machine learning algorithms based on those document vector models, and applying each of those models to further instances of the same search query to rank the documents responsive to that search query.

Abstract: A server device may receive a series of at least two screen capture representations of a graphical user interface on a client device. A first active window for a first screen capture representation of the series and a second active window for a second screen capture representation of the series may be determined. The first screen capture representation may have been screen captured by the client device at a first time and the second screen capture representation may have been screen captured by the client device at a second time. A first application associated with the first active window and a second application associated with the second active window may be identified, at least one of which may be a pre-determined target application. Based on the identified applications, an activity log for the client device may be determined.

Abstract: A computing device hosting a website of a business may be operable to receive a first search input comprising a term submitted via a search bar on the website. Upon performing an internal search for the term with no result, the computing device may output information on the no-result. The computing device may then perform, using one or more external search engines, a search for the term. Search results of the search, performed using the external search engine(s), may be analyzed. Based on a result of the analysis, one or more particular character strings related to the term may be identified. The computing device may generate and store, based on the identifying of the particular character string(s), one or more alternative search suggestions. Upon subsequently receiving an input comprising at least a portion of the term entered in the search bar, the computing device may output the alternative search suggestion(s).

Abstract: Methods of operating a search engine may include calculating multi-modal document vector models for each of a plurality of electronic documents, training category-specific, search query-specific ranking models with respective machine learning algorithms based on those document vector models, and applying each of those models to further instances of the same search query to rank the documents responsive to that search query.

Abstract: A computing device hosting a website of a business may be operable to receive a first search input comprising a term submitted via a search bar on the website. Upon performing an internal search for the term with no result, the computing device may output information on the no-result. The computing device may then perform, using one or more external search engines, a search for the term. Search results of the search, performed using the external search engine(s), may be analyzed. Based on a result of the analysis, one or more particular character strings related to the term may be identified. The computing device may generate and store, based on the identifying of the particular character string(s), one or more alternative search suggestions. Upon subsequently receiving an input comprising at least a portion of the term entered in the search bar, the computing device may output the alternative search suggestion(s).

Abstract: Systems and methods for providing suggestions responsive to search queries for a search engine are disclosed. Such suggestions may include one or more related search queries and/or a spell correction. Related search queries may be provided by converting the search query into a document vector space, determining documents that are similar to the query in the vector space, and determining prior search queries to which those similar documents are responsive. Spell corrections may be provided by comparing n-tuple word combinations in the search query to a library of correct n-tuple word combinations and making appropriate corrections.

Abstract: A computing device hosting a website of a business may be operable to receive a first search input comprising a term submitted via a search bar on the website. Upon performing an internal search for the term with no result, the computing device may output information on the no-result. The computing device may then perform, using one or more external search engines, a search for the term. Search results of the search, performed using the external search engine(s), may be analyzed. Based on a result of the analysis, one or more particular character strings related to the term may be identified. The computing device may generate and store, based on the identifying of the particular character string(s), one or more alternative search suggestions. Upon subsequently receiving an input comprising at least a portion of the term entered in the search bar, the computing device may output the alternative search suggestion(s).

Abstract: Methods of operating a search engine may include calculating multi-modal document vector models for each of a plurality of electronic documents, training category-specific, search query-specific ranking models with respective machine learning algorithms based on those document vector models, and applying each of those models to further instances of the same search query to rank the documents responsive to that search query.

Abstract: A computing device hosting a website of a business may be operable to receive a first search input comprising a term submitted via a search bar on the website. Upon performing an internal search for the term with no result, the computing device may output information on the no-result. The computing device may then perform, using one or more external search engines, a search for the term. Search results of the search, performed using the external search engine(s), may be analyzed. Based on a result of the analysis, one or more particular character strings related to the term may be identified. The computing device may generate and store, based on the identifying of the particular character string(s), one or more alternative search suggestions. Upon subsequently receiving an input comprising at least a portion of the term entered in the search bar, the computing device may output the alternative search suggestion(s).

Abstract: A method for operating a search engine may include determining a multi-dimensional search parameter space comprising a set of possible weight values for each of a plurality of search parameters and dividing the search parameter space into a grid of evenly-spaced values that is a subset of the set of possible values. The method may further include defining one or more initial populations of search parameter weight values, wherein each population of search parameter weight values comprises a plurality of initial individuals, wherein each initial individual comprises a respective one of the evenly-spaced values for each of the search parameters. The method may further include executing one or more genetic algorithms based on the one or more initial populations to select a final set of search parameter weight values, and returning results of a user search in the search engine according to the final set of search parameter weight values.

Abstract: A server device may receive a series of at least two screen capture representations of a graphical user interface on a client device. A first active window for a first screen capture representation of the series and a second active window for a second screen capture representation of the series may be determined. The first screen capture representation may have been screen captured by the client device at a first time and the second screen capture representation may have been screen captured by the client device at a second time. A first application associated with the first active window and a second application associated with the second active window may be identified, at least one of which may be a pre-determined target application. Based on the identified applications, an activity log for the client device may be determined.

Abstract: A server device may receive a series of at least two screen capture representations of a graphical user interface on a client device. A first active window for a first screen capture representation of the series and a second active window for a second screen capture representation of the series may be determined. The first screen capture representation may have been screen captured by the client device at a first time and the second screen capture representation may have been screen captured by the client device at a second time. A first application associated with the first active window and a second application associated with the second active window may be identified, at least one of which may be a pre-determined target application. Based on the identified applications, an activity log for the client device may be determined.