Abstract:
A location-aware search assist capability identifies location-aware search query suggestions using location information associated with the location-aware search query suggestions. A user's search query input and location and a location associated with each location-aware search query suggestion candidates may be used to identify a set of search query suggestions for presentation to the user. Location-aware search query suggestion candidates may be ranked in accordance with a closeness of each one's location to the user's location. The ranking may be performed using a score, such as a popularity score associated with each search query suggestion candidate. The location-aware search query suggestion candidates having a location closer to the user's location may be promoted by adjusting each candidate's popularity score upward, and the search query suggestion candidates that are farther away from the user's location may be demoted by adjusting each such candidate's popularity score downward.
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.
Abstract:
The present teaching, which includes methods, systems and computer-readable media, relates to providing query suggestions based on a number of data sources including person's personal data and non-personal data. The disclosed techniques may include receiving an input from a person, obtaining a first set of suggestions based on information from a first data source, presenting the first set of suggestions to the person, and presenting, to the person, a second set of suggestions obtained from a person corpus when a portion of the person corpus relevant to the input is accessible. The person corpus may be from a second data source that is private to the person.
Abstract:
The present teaching, which includes methods, systems and computer-readable media, relates to providing query suggestions based on a number of data sources that include person's personal data and non-personal data. The disclosed techniques may include receiving an input from a person, obtaining a first set of suggestions based on a person corpus derived from at least one data source private to the person, obtaining a second set of suggestions based on information from an additional data source, ranking the first and second sets of suggestions to generate a ranked list of suggestions, and presenting at least some of the ranked suggestions.
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:
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, which includes methods, systems and computer-readable media, relates to providing query suggestions based on multiple data sources including at least person's personal data. The disclosed techniques may include receiving an input from a person, obtaining one or more suggestions based on a person corpus derived from at least one data source private to the person, and presenting at least the one or more suggestions.