Abstract:
Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for determining and suggesting query auto-completions (QACs). In some embodiments, when a user is inputting a search query, the disclosed systems and methods can provide a QAC suggestion based on the inputted text in addition to application programs installed and/or executing on the user's device.
Abstract:
Methods, systems and programming for providing query suggestions based on user's previous search query. In one example, an input including a prefix of a first query is received from a user in a user session. At least a second query that was previously received from the user in the user session is then obtained. A third query is obtained based on the second query and the prefix of the first query. One or more query suggestions are provided to the user as a response to the input. The one or more query suggestions include the third query.
Abstract:
Methods, systems and programming for providing query suggestions based on user's previous search query. In one example, an input including a prefix of a first query is received from a user in a user session. At least a second query that was previously received from the user in the user session is then obtained. A third query is obtained based on the second query and the prefix of the first query. One or more query suggestions are provided to the user as a response to the input. The one or more query suggestions include the third query.
Abstract:
Methods, systems and programming for providing query suggestions including entities. In one example, a prefix of a query is first received. A plurality of query suggestions are then identified based on the prefix of the query. The plurality of query suggestions include at least one entity. Scores of each of the plurality of query suggestions are computed using a first model. The first model includes an adjustable parameter used for computing the score of the at least one entity. The plurality of question suggestions are ranked based, at least in part, on the scores.
Abstract:
The present teaching relates to rewriting a query and providing search results. In one example, a plurality of queries is obtained. For each of the plurality of queries, one or more search results are identified. The one or more search results have been obtained in response to the query and have been previously selected by a user submitting the query. A plurality of titles is obtained. Each of the titles corresponds to one of the one or more search results with respect to one of the plurality of queries. A model is generated based on the plurality of queries and the plurality of titles. The model is to be used for rewriting a query.
Abstract:
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.
Abstract:
Methods, systems and programming for providing query suggestions including entities. In one example, a prefix of a query is first received. A plurality of query suggestions are then identified based on the prefix of the query. The plurality of query suggestions include at least one entity. Scores of each of the plurality of query suggestions are computed using a first model. The first model includes an adjustable parameter used for computing the score of the at least one entity. The plurality of question suggestions are ranked based, at least in part, on the scores.
Abstract:
The present teaching relates to providing a query suggestion. In one example, a request is received for query suggestions with respect to a query prefix input by a user. A plurality of query suggestions is determined based on the query prefix and a preceding query input by the user. A degree of popularity of the preceding query is determined. One or more query suggestions are selected from the plurality of query suggestions based on the degree of popularity of the preceding query. The one or more query suggestions are provided as a response to the request.
Abstract:
One or more suggested search query completion alternatives are provided to the user and are selectable by the user in completing the user's search query. The suggested search query completion alternatives may comprise local business query completion suggestions, each of which may correspond to a local business, and general query completion suggestions, each of which may correspond to a general query. A ranking of local business query completion suggestions and general query completion suggestions may be used to identify a number of top-ranked query completion suggestions for presentation to the user. The ranking may use a popularity measure associated with each business and a frequency measure associated with each general query. A popularity associated with a local business may be weighted using a granularity weighting, which may be determined using a local query intent confidence level.