Abstract: Building a semantics graph for an enterprise communication network can include calculating a distance metric between a first signifier and a second signifier associated with an enterprise communication network, wherein the distance metric includes a plurality of relationships defined based on a frequency of co-occurrences of the first signifier and the second signifier, and building a semantics graph for the enterprise communication network using the calculated distance metric.

Abstract: Suggesting email tags. A non-transitory machine-readable storage device includes executable instructions that when executed, cause one or more processor to provide a suggestion for at least one suggested tag based on content of an email, receive a selection of a selected tag store the email in a computer database, thus creating a stored email, and associate the selected tag with the stored email in the computer database.

Abstract: A technique includes receiving a submission classified by a plurality of human classifiers. Based at least in part on a classification model for the plurality of human classifiers and classification decisions made by the human classifiers, the submission is classified.

Abstract: Building a semantics graph for an enterprise communication network can include calculating a distance metric between a first signifier and a second signifier associated with an enterprise communication network, wherein the distance metric includes a plurality of relationships defined based on a frequency of co-occurrences of the first signifier and the second signifier, and building a semantics graph for the enterprise communication network using the calculated distance metric.

Abstract: An example of task management can include receiving a message between a sending user and a receiving user. The message can be analyzed to determine whether the message includes a requested task. A parameter of the requested task can be extracted from the message based on directives in the message. An update to a status of the task can be sent to the sending user and the receiving user.

Abstract: Building a semantics graph for an enterprise communication network can include extracting a first signifier and a second signifier from the enterprise communication network, determining a semantic proximity of the first signifier and the second signifier using an engine executing computer readable instructions, and building the semantics graph, wherein the first signifier and the second signifier are represented as nodes connected by an edge representing the semantic proximity of the first signifier and the second signifier.

Abstract: A method for calculating a content subset can include crawling a number of webpages for content, determining a relevance to a particular domain of the content, determining a penalty value for each of the number of webpages; and calculating, utilizing a data tree-based model, a subset of the content to analyze based on the relevance and the penalty value.

Abstract: Clustering signifiers in a semantics graph can comprise coarsening a semantics graph associated with an enterprise communication network containing a plurality of nodes into a number of sub-graphs containing supernodes; partitioning each of the number of sub-graphs into a number of clusters; and iteratively refining the number of clusters to reduce an edge-cut of the semantics graph, based on the number of clusters.

Abstract: Systems, methods, and machine-readable and machine-executable instructions are provided to determine context-aware information item recommendations for deals. An example of a computing system to determine context-aware information item recommendations can extract a set of information concerning pursuit of a deal by an enterprise, where a first portion of the set can be extracted from an electronic communication network and a second portion of the set can be extracted from a profile of elements to be included in a completed deal. The computing system can form a context-aware query by determination of semantic relevance of the set of information and can determine an output based upon correlation of the context-aware query with content of a resource description framework (RDF) triple store, where the output includes the context-aware information item recommendations for the deal.

Abstract: Identifying a subset of signifiers to analyze can include determining a set of distance metrics between a first signifier and each of a plurality of second signifiers, identifying a subset of the plurality of second signifiers to analyze based on the set of distance metrics using a computing device, and determining a relation between the subset of the plurality of second signifiers and the first signifier based a subset of the set of distance metrics.

Abstract: An example of identifying tasks and commitments can include receiving a communication message. A task and a parameter can be identified in the communication message. Information related to the task can be extracted from the communication message using natural language processing (NLP) and machine learning (ML). A commitment related to the task can be identified using NLP extracted information. A state of the commitment can be identified using NLP and ML based on the extracted information.

Abstract: A flow model of an activity flow that is based on cases is provided. The flow model is annotated with information from the cases. A matching step in the activity flow that matches a given step of a particular case is identified, and a next step is recommended based on the matching step in the activity flow of the flow model.

Abstract: Methods, systems, and computer-readable and executable instructions are provided for keyword extraction. A method for keyword extraction can include extracting a number of keywords from content inside an enterprise social network utilizing pattern recognition, constructing a semantics graph based on the number of keywords, and determining content themes within the enterprise social network based on the constructed semantics graph.

Abstract: Methods, systems, and computer-readable and executable instructions are provided for organizing content. A method for organizing content can include building a customized content corpus for a user, building a concept graph customized for the user's context based on the customized corpus, and organizing, utilizing multi-view clustering, the content within the corpus based on the concept graph.

Abstract: A method and system for project and portfolio management is disclosed. The method may include tagging one or more data records of projects of a plurality of projects with one or more tags, and displaying on a display device the one or more tagged data records with information relating to said one or more tags. A computer program product is also disclosed.

Abstract: A system including one or more processors and memory. The memory stores computer-executable instructions that control the one or more processors to receive a set of emails, process the set of emails to produce information related to the set of emails, evaluate the information related to the set of emails to answer one or more questions and produce evaluation results, and aggregate the evaluation results into a feedback report.

Abstract: A system including one or more processors and memory. The memory stores computer-executable instructions that control the one or more processors to receive requests, interpret the requests in the context of a process, and provide responses based on interpretations of the requests in the context of the process.

Abstract: Embodiments of the present invention disclose a method and system for combinatorial document matching. According to one embodiment, a target document and a plurality of source documents are received by the system. Thereafter, consolidated source document information associated with the plurality of source documents and permutated concept data affiliated with the target document are created. Based on comparisons of the permutated concept data and the consolidated source document information, a set of relevant documents from the plurality of source documents are determined.

Abstract: Information relating to project metric data and occurrence of events in a plurality of projects is received (102). Uncertainty data is determined (106) based on the received information, where the uncertainty data represents a probability distribution of at least one metric associated with the active project. Input relating to a scenario to perform what-if analysis is received (108), and based on the input, what-if analysis is performed (110).

Abstract: One embodiment of the present invention is directed to a project search system, implemented on one or more computer systems, comprising two or more stored projects represented by electronically stored, computer-accessible data that are stored in a project-database component; a project-comparator subsystem, executed on the one or more computer systems, that generates a similarity metric for two electronically-represented projects input to the project-comparator subsystem; and a project search engine, executed on the one or more computer systems, that receives data that represents an input project, identifies, by pairwise comparison of the stored projects with the input project using the project-comparator subsystem, one or more stored projects with greatest similarity to the input project, and outputs, to a graphical interface displayed on a computer display or to an application program, indications of the one or more stored projects with greatest similarity to the input project.