A method for archiving of documents of a query against a cognitive system can be provided. The cognitive system comprises at least a cognitive engine, several stored documents, and a learned model. The method comprises determining a plurality of evidence fragments, a related first list of documents and related metadata. The method also comprises removing a document from the stored documents, redetermining as second result a second list of documents, comparing the first and second list of documents, and upon determining identical documents in the compared first and second list of documents up to a confidence cliff, removing another document. Furthermore, the method comprises repeating the steps of removing, redetermining, and comparing until the first list of documents and the second list of documents differ above the confidence cliff and storing metadata of the documents of the first list, the plurality of evidence fragments, and the first query.

A system and method of processing a search request is provided. Identification of a desired content item is based on comparing a topic of the search request to previous user input. The method includes providing access to a set of content items with metadata that describes the corresponding content items and providing information about previous searches. The method further includes receiving a present input from the user and determining a relatedness measure between the information about the previous searches and an element of the present input. If the relatedness measure is high, the method also includes selecting a subset of content items based on comparing the present input and information about the previous searches with the metadata that describes the subset of content items. Otherwise, the method includes selecting a subset of content items based on comparing the present input with the metadata that describes the subset of content items.

Disclosed embodiments provide techniques for database query utilizing a multigram index. In embodiments, a search query is divided into multiple regex subcomponents. Regex subcomponent indexes are created and searched in parallel, and/or in a sequential manner on reduced data sets, increasing search performance, especially for NoSQL databases.

Disclosed are various embodiments for providing guided search results to items or network pages containing buying guides. A plurality of search terms in a search query are identified. It is then determined that at least one network page is a relevant search result for the search query based at least in part on the plurality of search terms in the search query, the network page including a plurality of items and a plurality of instances of user-submitted content related to each of the plurality of items. The network page is then added to a list of search results for the search query. The search results are then returned in response to the search query.

A search engine is provided that generates search results proportional to a natural distribution. Search results identified and ranked by the search engine for a search query are redistributed so that a fixed number of top ranked search results include search result attributes proportional to the natural distribution, as determined from interaction tracking of prior search results. A natural distribution index mapping prior search queries to search result attributes and a proportional representation of interactions with the search result attributes is generated. The natural distribution is determined from the proportional representation of interactions. The search engine redistributes the fixed number of top ranked search results by minimizing a gap between the ranked set of search results for the search query and the natural distribution.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for re-ranking a collection of documents according to a first metric and subject to a constraint on a function of one or more second metrics. One of the methods includes: obtaining, for each document in the first collection of documents, a respective first metric value corresponding to the first metric and respective one or more second metric values corresponding to the one or more second metrics; re-ranking the first collection of documents, comprising: determining the constraint on the function of one or more second metrics by computing a first threshold value using a variable threshold function that takes as input second metric values for the documents in the first collection of documents; and determining the re-ranking for the first collection of documents by solving a constrained optimization for the first metric constrained by the first threshold value.

A personal assistant system and method. A personal assistant electronic device receives input data indicative of a query specifying a request from a user within an environment. A context processing engine establishes a context for the query, the engine applying trained models to the input data to identify personal and environmental cues associated with the query. A response generator generates a response message based on the request, the query context and a response profile for the user, the response profile specifying one or more preferences for the user, each of the one or more preferences being associated with a manner in which the response generator responds to requests from the user, each of the one or more preferences being set by the response generator in response to feedback from the user to previous response messages.

A computing system includes a client device and a form template server. The client device has a display associated therewith to display an application page from an application, and generate a screenshot of the form. The application page includes a form requiring data to be filled in by a user. The form template server compares a form template extracted from the screenshot to a private form template database for a match. The private form template database includes private form templates from different applications, with each private form template having user data associated therewith previously filled in for the user. The client device then populates the form on the display with the data from the matched private form template.

For query auto completion (QAC) in an eCommerce platform with constantly changing product supply and demand, a Query Mover's Distance (QMD) framework for ranking queries is used, which formulates QAC as an optimal transport problem balancing product demand and supply.

A system and method of processing a search request is provided. Identification of a desired content item is based on comparing a topic of the search request to previous user input. The method includes providing access to a set of content items with metadata that describes the corresponding content items and providing information about previous searches. The method further includes receiving a present input from the user and determining a relatedness measure between the information about the previous searches and an element of the present input. If the relatedness measure is high, the method also includes selecting a subset of content items based on comparing the present input and information about the previous searches with the metadata that describes the subset of content items. Otherwise, the method includes selecting a subset of content items based on comparing the present input with the metadata that describes the subset of content items.