Abstract:
Examples disclosed herein relate to determine attention span style time correlation. In one implementation, a processor determines, based on information related to a users navigation of digital material and stored classifier information, time correlation information related to the users attention span style. The processor may output information related to the determination
Abstract:
Converting an input script includes obtaining an input script comprising at least one variable, obtaining at least one translation transformation rule from a library, converting the input script into a tree representation, folding the tree representation to hide a subset of variables in the input script to create a folded tree, and generating a natural language text by applying at least one translation transformation rule from the library to the folded tree.
Abstract:
Converting an input script includes obtaining an input script comprising at least one variable, obtaining at least one translation transformation rule from a library, converting the input script into a tree representation, folding the tree representation to hide a subset of variables in the input script to create a folded tree, and generating a natural language text by applying at least one translation transformation rule from the library to the folded tree.
Abstract:
According to an example, candidate scripts may be determined from a catalog of scripts to perform a requested operation. In determining the candidate scripts, a request for an operation may be received, in which the request includes an input and an output. In addition, based upon the input and the output, a plurality of candidate scripts that are to perform the requested operation may be identified from the catalog of scripts, in which each of the plurality of candidate scripts comprises at least one of a script that is to perform the requested operation individually or a number of scripts that, in combination, are to perform the requested operation. Moreover, a score for each of plurality of candidate scripts may be calculated based upon a plurality of factors respectively corresponding to the plurality of candidate scripts and the plurality of candidate scripts and the calculated scores may be outputted.
Abstract:
Examples associated with reading difficulty level based resource recommendation are disclosed. One example may involve instructions stored on a computer readable medium. The instructions, when executed on a computer, may cause the computer to obtain a set of candidate resources related to a source document. The candidate resources may be obtained based on content extracted from the source document. The instructions may also cause the computer to identify reading difficulty levels of members of the set of candidate resources. The instructions may also cause the computer to recommend a selected candidate resource to a user. The selected candidate resource may be recommended based on subject matter similarity between the selected candidate resource and the source document. The selected candidate resource may also be recommended based on reading difficulty level similarity between the selected candidate resource and the source document.
Abstract:
Automated content selection is disclosed. An example method includes generating a plurality of rankings for each document in a set of input documents, each ranking based on separate interesting document properties. The method also includes selecting a subset of the set of input documents, wherein each document selected for the subset is based on rankings of the selected document. The method also includes determining interesting properties of the subset. The method also includes selecting a subset with respect to parameters being optimized. The method also includes outputting a composition including the documents in the subset.
Abstract:
Systems and methods associated with external resource identification are disclosed. One example method may be embodied on a non-transitory computer-readable medium storing computer-executable instructions. The instructions, when executed by a computer may cause the computer to perform the method. The method includes classifying a segment of a document into a member of a set of topics discussed within the document. The method also includes identifying, based on the structure of the segment and keywords from the segment, information that a reader of the document could seek upon reading the segment. The method also includes obtaining, based on the member of the set of topics, a set of candidate external resources that potentially contain the information. The method also includes presenting, in response to a user interaction with the document, a member of the set of candidate external resources identified as being likely to contain the information.
Abstract:
A learning graph is generated for documents according to a sequencing approach. The learning graph includes nodes corresponding to the documents and edges. Each edge connects two of the nodes and indicates a sequencing relationship between two of the documents to which the two of the nodes correspond that specifies an order in which the two of the documents are to be reviewed in satisfaction of the learning goal. The learning graph is a directed graph specifying a learning path through the documents to achieve a learning goal in relation to a subject.
Abstract:
A system can include a print history analyzer to generate history data based on a document history that includes a list of documents selected to be printed. The history data can characterize a content and layout of documents selected for printing. The system can also include a user print profile builder to generate a user print profile based on the history data. The user print profile can characterize printing preferences of a user. The system can further include a recommendation engine to generate a composite to-print product for the user. The composite to-print product can be based on the user print profile.
Abstract:
A system can include a page type classifier to determine a page type of a file. The system can also include a print intent identifier to map the page type of the file to a print intent subtype of the file. The print intent identifier can also map the print intent subtype of the file to a print intent type of the file. The print intent type of the file can characterize a reason to at least one of print and store the file.