Techniques are described herein for generating, editing, and optimizing queries using neural networks. In some embodiments, the techniques include training a neural network using a set of performant database queries to automatically learn patterns between different sequences of tokens in performant queries. Once trained, the neural network may receive an incomplete query as input, where the incomplete query includes one or more query tokens. The trained neural network may then perform next token prediction to project a set of one or more additional query tokens that may follow the one or more query tokens in the incomplete query to form a completed, performant query.

Methods, systems, and media for providing search suggestions are provided. In accordance with some embodiments, the method comprises: receiving user input that includes a partial search query; identifying a group of candidate search suggestions; determining whether each candidate search suggestion is included on a list of search suggestions that are prohibited, wherein the list is generated by: receiving previously submitted search queries and search results; determining, for each of the search queries, a number of search results associated with a particular content rating; determining whether the number meets a threshold value; and in response to determining that the number does not meet the threshold value, inserting the search query to the list; generating a modified group of search suggestions by removing search suggestions that are on the list; and causing a subset of the modified group of search suggestions to be presented as the remaining portion of the search query.

Embodiments of search systems that leverage the search or access activities of a core group of users to improve search functionality and performance of such search systems are disclosed. Specifically, embodiments may utilize users' search activity to generate clusters of users and associated labels for those clusters. These clusters can be leveraged during a search to generate suggestions for a user conducting the search.

A media content item recommendation system recommends media content items based on one or more attributes of a seed playlist. The recommended media content items can be determined from a plurality of existing playlists that have been created over a period of time. Such existing playlists can be selected based on similarity to the seed playlist.

A method executed by a computing device includes determining a set of identigens for each query word of a query to produce sets of identigens. The method further includes interpreting the sets of identigens to produce different first and second query entigen groups. The method further includes generating an interim response based on the first and second query entigen groups. The method further includes determining a set of identigens for each updated query word of an updated query to produce updated sets of identigens. The method further includes selecting one of the first or second query entigen group based on the updated sets of identigens to produce a selected query entigen group. The method further includes generating a response entigen group utilizing the selected query entigen group and generating a response to the query utilizing the response entigen group.

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.

This application relates to apparatus and methods for automatically determining query corrections based on prior interactions of users with a search query. In some examples, a computing device receives a search query from a user, and returns a query correction to the user in response to the search query. The computing device obtains engagement data corresponding to the query correction from the user. The computing device also updates one of a query-correction database and a typo-candidate database based at least in part on the engagement data. When the computing device receives the search query from another user, it corrects the search query from the another user using the query-correction database and the typo-candidate database.

A query suggestion to expand an initial query is calculated whereby the cost of the expanded initial query is bounded in both time and quality. The user validates a subset of the top-n answers Q(G) to a query Q and provides adjusted configuration parameters. The top-n diversified δ-expansion terms Q′ are calculated from the validated subset of answers Q(G) to the query Q and are provided to an interactive user interface for selection. Answers Q′(G) for the top-n diversified δ-expansion terms Q′ are cost bounded by cost threshold δ and exploration range r specified by the user. The user selects a new term of terms Q′ and an incremental query evaluation of the new term is invoked to compute expanded query answers Q′(G) by incrementally updating the validated subset of answers Q(G), without re-evaluating an expanded query Q′ including the new term from scratch.

Methods, systems, and media for providing search suggestions are provided. In accordance with some embodiments, the method comprises: receiving user input that includes a partial search query; identifying a group of candidate search suggestions; determining whether each candidate search suggestion is included on a list of search suggestions that are prohibited, wherein the list is generated by: receiving previously submitted search queries and search results; determining, for each of the search queries, a number of search results associated with a particular content rating; determining whether the number meets a threshold value; and in response to determining that the number does not meet the threshold value, inserting the search query to the list; generating a modified group of search suggestions by removing search suggestions that are on the list; and causing a subset of the modified group of search suggestions to be presented as the remaining portion of the search query.

Methods, systems and programming for providing query suggestions based on user feedback. In one example, a prefix of a query is first received. An input including a prefix of a query is received from a user in a search session. A plurality of query suggestions are fetched based on the prefix of the query. Rankings of the plurality of query suggestions are determined based, at least in part, on the user's previous interactions in the search session with respect to at least one of the plurality of query suggestions. The at least one of the plurality of query suggestions has been previously provided to the user in the search session. The plurality of query suggestions are provided in the search session based on their rankings as a response to the input.