Abstract: Examples disclosed herein relate to recommending content segments based on annotations. In one implementation, a processor determines content segments based on user data related to annotations of the content. The processor recommends at least one of the content segments based on the relative value of the content segment to the other content segments. For example, the value of a content segment may be determined based on the annotations associated with the content segment.

Abstract: Examples herein disclose identifying multiple topics within a selected passage. The examples disclose processing the multiple topics in accordance with a statistical model to determine relevant topics to the selected passage. Additionally, the examples disclose outputting a resource related to the relevant topics.

Abstract: Embodiments of the present invention relate to a new method of entity integration using high-level scripting languages. In one embodiment, a method of and computer product for entity integration is provided. An entity declaration is read from a machine readable medium. The entity declaration describes an entity including at least one nested entity. An index declaration is read from a machine readable medium. The index declaration describes an index of nested entities. An entity population rule is read from a machine readable medium. The entity population rule describes a mapping from an input schema to an output schema. The output schema conforms to the entity declaration. A plurality of input records is read from a first data store. The input records conform to the input schema. The entity population rule applies to the plurality of records to create a plurality of output records complying with the output schema. An index of nested entities is populated. The index complies with the index declaration.

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: Embodiments of the present invention relate to a new method of entity integration using high-level scripting languages. In one embodiment, a method of and computer product for entity integration is provided. An entity declaration is read from a machine readable medium. The entity declaration describes an entity including at least one nested entity. An index declaration is read from a machine readable medium. The index declaration describes an index of nested entities. An entity population rule is read from a machine readable medium. The entity population rule describes a mapping from an input schema to an output schema. The output schema conforms to the entity declaration. A plurality of input records is read from a first data store. The input records conform to the input schema. The entity population rule applies to the plurality of records to create a plurality of output records complying with the output schema. An index of nested entities is populated. The index complies with the index declaration.

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: Matching of an input document to documents in a document collection is described herein. In an example, a similarity correspondence between an input document and one or more documents in a base document collection is established. A set of base document segments and a set of message types associated to document segments in the set of base document segments is provided. The set of base document segments is derived from documents in the base document collection. The input document is segmented into input document segments corresponding to message types. Segment similarity between input document segments and base document segments corresponding to the same message types is computed. The similarity correspondence between the input document and at least one document in the base document collection is based on the computed segment similarity.

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: Methods for analyzing a Uniform Resource Locator (URL) and apparatus for performing such methods. The methods include parsing the URL into text segments and generating n-grams from the text segments. The methods further include generating annotations, each annotation corresponding to one of the n-grams and comprising a match value for its corresponding n-gram, a description of its match value, and a score. The methods still further include selecting a subset of the annotations.

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: Inferring facts from online user activity includes performing an analysis of a uniform resource locator of a web page in response to predetermined user activity, mapping data about the web page to a structured object based on the analysis, and inferring a fact about the user activity based on the mapped data.

Abstract: A system can include a print type classifier to receive a print message that indicates that a file has been selected to be printed. The print type classifier can also determine a print type of the file. The system can also include a print content analyzer to assign a category to the file characterizing a topic of the file based on the content of the file. The print type analyzer can also generate a content representation of the file that characterizes a summary of content of the file. The system can further include a recommendation engine to provide supplemental content based on at least one of the print type, the category and the content representation of the file, wherein the supplemental content is in a printable format.

Abstract: A computer-implemented method of automatically determining a name of a person appearing in an image includes receiving a collection of web pages containing a plurality of images. For each of the images, a set of names associated with the image is identified based on a text analysis of at least one of the web pages. Face detection and clustering is performed on the plurality of images to generate a plurality of face clusters. For each of the face clusters, a label for the face cluster is identified based on the set of names associated with each image in the face cluster. A name of a first person appearing in at least one of the images is determined based on the identified label for one of the face clusters associated with the first person.

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.

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: Embodiments of the present invention relate to a new method of entity integration using high-level scripting languages. In one embodiment, a method of and computer product for entity integration is provided. An entity declaration is read from a machine readable medium. The entity declaration describes an entity including at least one nested entity. An index declaration is read from a machine readable medium. The index declaration describes an index of nested entities. An entity population rule is read from a machine readable medium. The entity population rule describes a mapping from an input schema to an output schema. The output schema conforms to the entity declaration. A plurality of input records is read from a first data store. The input records conform to the input schema. The entity population rule applies to the plurality of records to create a plurality of output records complying with the output schema. An index of nested entities is populated. The index complies with the index declaration.

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: Disclosed herein are a system, non-transitory computer readable medium and method for fulfilling requests for source code. A description is associated with each section of source code text. A section of source code, whose description at least partially matches a source code request, is obtained and displayed.

Abstract: Methods for analyzing a Uniform Resource Locator (URL) and apparatus for performing such methods. The methods include parsing the URL into text segments and generating n-grams from the text segments. The methods further include generating annotations, each annotation corresponding to one of the n-grams and comprising a match value for its corresponding n-gram, a description of its match value, and a score. The methods still further include selecting a subset of the annotations.

Abstract: A system can include a print type classifier to receive a print message that indicates that a file has been selected to be printed. The print type classifier can also determine a print type of the file. The system can also include a print content analyzer to assign a category to the file characterizing a topic of the file based on the content of the file. The print type analyzer can also generate a content representation of the file that characterizes a summary of content of the file. The system can further include a recommendation engine to provide supplemental content based on at least one of the print type, the category and the content representation of the file, wherein the supplemental content is in a printable format.