Abstract: A method and system for selecting documents for inclusion into a search engine search index executed by a machine learning algorithm (MLA) comprising: acquiring a plurality of digital documents, each respective document having a respective size, determining a respective value parameter based on user interactions, ranking the digital documents to obtain a ranked list of documents based on: a respective quality value parameter based on the respective value parameter and the respective size, the ranking being performed such that a cumulative quality value parameter is maximized based on: the quality value parameter of a given digital document is weighted by a sum of the sizes of a given subset of documents, wherein the given subset consists of documents having a respective value parameter below the value parameter of the given digital document, selecting a subset from the ranked list and storing the subset in the search index.

Abstract: A method and a system for generating fresh query suggestions includes receiving an indication of at least a portion of a given search query, selecting, based on the indication, a set of query suggestions, each of the query suggestion being associated with a frequency of use of a first scale, acquiring a set of fresh query suggestions, each of the fresh query suggestions being associated with a frequency of use of a second scale, scaling each frequency of use of the second scale to obtain a frequency of use of the first scale, merging the set of query suggestions and the set of fresh query suggestions to generate an amalgamated suggestions set, and generating a subset of ranked query suggestions for displaying on a device based on the amalgamated suggestions set, a given query suggestion of the subset being one of a fresh query suggestion and a query suggestion.

Abstract: A method and system for selecting documents for inclusion into a search engine search index executed by a machine learning algorithm (MLA) comprising: acquiring a plurality of digital documents, each respective document having a respective size, determining a respective value parameter based on user interactions, ranking the digital documents to obtain a ranked list of documents based on: a respective quality value parameter based on the respective value parameter and the respective size, the ranking being performed such that a cumulative quality value parameter is maximized based on: the quality value parameter of a given digital document is weighted by a sum of the sizes of a given subset of documents, wherein the given subset consists of documents having a respective value parameter below the value parameter of the given digital document, selecting a subset from the ranked list and storing the subset in the search index.

Abstract: A method and server for indexing a page is disclosed. The method includes identifying recent data associated with the page and generating, via an MLA, a score for the page based on the recent data which is indicative of usefulness of the page as a search result of a search engine. The MLA has been trained based on a training page having data at a first moment in time and data at a second moment in time. The method also includes selectively adding the page to one of a real-time indexing queue and a postponed indexing queue based on a comparison between the score and a threshold. If the score is below the threshold, the page is added to the postponed indexing queue. If the score is above the threshold, the page is added to the real-time indexing queue. Pages in the real-time indexing queue are indexed in real-time.

Abstract: A method and a system for generating fresh query suggestions comprising: receiving an indication of at least a portion of a given search query, selecting, based on the indication, a set of query suggestions, each of the query suggestion being associated with a frequency of use of a first scale, acquiring a set of fresh query suggestions, each of the fresh query suggestions being associated with a frequency of use of a second scale, scaling each frequency of use of the second scale to obtain a frequency of use of the first scale, merging the set of query suggestions and the set of fresh query suggestions to generate an amalgamated suggestions set, and generating a subset of ranked query suggestions for displaying on a device based on the amalgamated suggestions set, a given query suggestion of the subset being one of a fresh query suggestion and a query suggestion.