Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for transcoding and providing resources. A query is received. A resource is generated, and the resource, when processed by a client device, causes the client device to perform various operations. The operations include displaying a search result having an associated landing page and detecting user interaction with the search result. The operations include, in response to detecting user interaction with the search result, displaying a first portion of the landing page that is embedded within the resource and requesting, over a network, a second portion of the landing page. The operations include receiving the second portion of the landing page, and loading the second portion of the landing page. The generated resource is provided in response to the query.

An apparatus comprising an interface and a natural language processor. The interface receives a data retrieval request formatted in a natural language and the natural language processor processes the data retrieval request. Processing the data retrieval request includes identifying database entities, database relations, or any combination thereof based words in the data retrieval request. It can also include identifying database entity criterion, database relation criterion, or any combination thereof based on words in the data retrieval request. It also includes generating a database query based on the database entities, the database relations, the database entity criterion, the database relation criterion, or any combination thereof and causing the database query to be applied to a database. Wherein, processing the data retrieval request includes grammatically tagging the data retrieval request using part-of-speech tagging techniques, e.g. grammatical type, grammatical context, semantic, or any combination thereof, and a database ontology.

An apparatus comprising an interface and a natural language processor. The interface receives a data retrieval request formatted in a natural language and the natural language processor processes the data retrieval request. Processing the data retrieval request includes identifying database entities, database relations, or any combination thereof based words in the data retrieval request. It can also include identifying database entity criterion, database relation criterion, or any combination thereof based on words in the data retrieval request. It also includes generating a database query based on the database entities, the database relations, the database entity criterion, the database relation criterion, or any combination thereof and causing the database query to be applied to a database. Wherein, processing the data retrieval request includes grammatically tagging the data retrieval request using part-of-speech tagging techniques, e.g. grammatical type, grammatical context, semantic, or any combination thereof, and a database ontology.

An information processing apparatus acquires a plurality of lists including one or more rows from table data including a plurality of columns and a plurality of rows, based on a value of one column in the plurality of columns and extracts, based on a list including a predetermined search key among the acquired plurality of lists, a value corresponding to the search key. Thus, for example, even in a case where there is no character string on the right side of the search key, value information corresponding to the search key is extractable.

An information processing apparatus acquires a plurality of lists including one or more rows from table data including a plurality of columns and a plurality of rows, based on a value of one column in the plurality of columns and extracts, based on a list including a predetermined search key among the acquired plurality of lists, a value corresponding to the search key. Thus, for example, even in a case where there is no character string on the right side of the search key, value information corresponding to the search key is extractable.

A server system for a map-based social media platform maintains user location information to enable the rendering of friend icons on a map at a corresponding display locations. The system maintains a per user access control list (ACL) that lists all users whose icons can be viewed by a requesting user. The ACL can include a designation of respective display granularity levels for different friend users.

A server system for a map-based social media platform maintains user location information to enable the rendering of friend icons on a map at a corresponding display locations. The system maintains a per user access control list (ACL) that lists all users whose icons can be viewed by a requesting user. The ACL can include a designation of respective display granularity levels for different friend users.

Data transformation caching in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: identifying, in dependence upon one or more machine learning models to be executed on the GPU servers, one or more transformations to apply to a dataset; generating, in dependence upon the one or more transformations, a transformed dataset; storing, within one or more of the storage systems, the transformed dataset; receiving a plurality of requests to transmit the transformed dataset to one or more of the GPU servers; and responsive to each request, transmitting, from the one or more storage systems to the one or more GPU servers without re-performing the one or more transformations on the dataset, the transformed dataset.

A method is provided of communication between a user and a database of Patents and also of the display and the interactive exploration of data on information of interest relating to Patents/Patent applications. The method comprises: the generation, by means of an access interface, of a request allowing the database to be interrogated based on at least one selection criterion entered into the access interface; the interrogation of the database by means of the request and the loading of bibliographical data for the Patents/Patent applications found, the downloaded bibliographical data comprising data on the technological category; the processing of the bibliographical data, the processing comprising an analysis of co-occurrences comprising the determination of a number of co-occurrences of data on the technological category for all of the Patents/Patent applications found; the displaying, in interactive graphical and/or textual form, of a result and/or of an interpretation of the analysis of co-occurrences.

The improved exercise of artificial intelligence by providing a systematic way for a computing system to interface with output from AI models. To do this, the computing system obtains results of an input data set being applied to an AI model. The results are then refined based upon characteristic(s) of the AI model and perhaps the input data set. Based upon characteristic(s) of the AI model and perhaps the input data set, interface element(s) are identified that can be used to interface with the refined results. The interface element(s) are then communicated to an interface element that interfaces with the refined results. The interface element(s) may include, for instance, operator(s) or term(s) that may be used to query against the refined results and/or an identification of visualization(s) that may be used to present to a user results of queries against the refined results.