Abstract: At least one unique collection of storage artifacts can be specified to indicate that the storage artifact is a member of the unique collection. Each storage artifact can be a discrete object comprising digitally encoded content that is stored as a node within a tree structure of a tangible storage medium. The collection can be referenced by a set of different storage artifacts to form a collection of related storage artifacts. Each storage artifact can correspond to different collections, wherein membership within a collection is independent of a storage path within the tree structure. A file management action relating to the storage artifact can be performed. The file management action can be dependent upon the storage artifact being a member of the unique collection.

Abstract: A method and a system for agitation detection and response for a programming language are provided. The method includes collecting software code and activity data pertaining to one or more activities performed by a developer that is using a segment of a programming language. The method also includes evaluating the activity data to generate an agitation level of the developer when using the segment of the programming language. The method can also include generating a developer context by evaluating the software code. The developer context can include insights into the operation of features in the programming language by the developer. The activity and developer context can be provided to a software development provider for independent analysis.

Abstract: A method can include evaluating each of a plurality of collaborative systems, using a processor, for suitability hosting an artifact according to at least one attribute of the artifact. A first collaborative system can be selected from the plurality of collaborative systems according to the evaluation. The artifact can be stored in the first collaborative system.

Abstract: Methods, systems, and computer program products for a collaborative cognition platform for creating and hosting social machines are provided herein. A computer-implemented method includes creating a social machine for collaborative tasks, wherein the social machine comprises (i) one or more human agents, (ii) one or more machine-based agents, (iii) an algorithm, and (iv) a set of rules prescribed for executing the collaborative tasks. The method also includes generating one or more collaborative resolutions for the collaborative tasks by executing, in an automated fashion, the collaborative tasks via implementation of the algorithm, wherein the algorithm facilitates, in accordance with the set of rules, systematic iterations of collaboration among (i) the one or more human agents and (ii) the one or more machine-based agents. Further, the method includes outputting the one or more collaborative resolutions to at least one user.

Abstract: At least one unique collection of storage artifacts can be specified to indicate that the storage artifact is a member of the unique collection. Each storage artifact can be a discrete object comprising digitally encoded content that is stored as a node within a tree structure of a tangible storage medium. The collection can be referenced by a set of different storage artifacts to form a collection of related storage artifacts. Each storage artifact can correspond to different collections, wherein membership within a collection is independent of a storage path within the tree structure. A file management action relating to the storage artifact can be performed. The file management action can be dependent upon the storage artifact being a member of the unique collection.

Abstract: A method can include evaluating each of a plurality of collaborative systems, using a processor, for suitability hosting an artifact according to at least one attribute of the artifact. A first collaborative system can be selected from the plurality of collaborative systems according to the evaluation. The artifact can be stored in the first collaborative system.

Abstract: At least one unique collection of storage artifacts can be specified to indicate that the storage artifact is a member of the unique collection. Each storage artifact can be a discrete object comprising digitally encoded content that is stored as a node within a tree structure of a tangible storage medium. The collection can be referenced by a set of different storage artifacts to form a collection of related storage artifacts. Each storage artifact can correspond to different collections, wherein membership within a collection is independent of a storage path within the tree structure. A file management action relating to the storage artifact can be performed. The file management action can be dependent upon the storage artifact being a member of the unique collection.

Abstract: A computer-implemented technique is described herein for scheduling events. The technique involves recommending one or more candidate spaces (e.g., candidate meeting rooms) based on a selected visit profile for each attendee to the event. More specifically, the technique selects a visit profile for each attendee from a group including a live visit profile, a short-term visit profile, and a long-term visit profile. Each such visit profile describes one or more visits made by the attendee within a prescribed timespan. The technique captures visit data for each such visit based on movement-related signals provided by one or more movement-determining mechanisms. A mobile computing device provides at least one movement-determining mechanism. In a preliminary phase, the technique can identify the geographical position of each candidate meeting space using a crowdsourcing operation.

Abstract: A method can include evaluating each of a plurality of collaborative systems, using a processor, for suitability hosting an artifact according to at least one attribute of the artifact. A first collaborative system can be selected from the plurality of collaborative systems according to the evaluation. The artifact can be stored in the first collaborative system.

Abstract: A computer-implemented technique is described herein for scheduling events. The technique involves recommending one or more candidate spaces (e.g., candidate meeting rooms) based on a selected visit profile for each attendee to the event. More specifically, the technique selects a visit profile for each attendee from a group including a live visit profile, a short-term visit profile, and a long-term visit profile. Each such visit profile describes one or more visits made by the attendee within a prescribed timespan. The technique captures visit data for each such visit based on movement-related signals provided by one or more movement-determining mechanisms. A mobile computing device provides at least one movement-determining mechanism. In a preliminary phase, the technique can identify the geographical position of each candidate meeting space using a crowdsourcing operation.

Abstract: A method and a system for agitation detection and response for a programming language. The method includes collecting software code and activity data pertaining to one or more activities performed by a developer that is using a segment of a programming language. The method also includes evaluating the activity data to generate an agitation level of the developer when using the segment of the programming language. The method can also include generating a developer context by evaluating the software code. The developer context can include insights into the operation of features in the programming language by the developer. The activity and developer context can be provided to a software development provider for independent analysis.

Abstract: Methods, systems, and computer program products for adapting the tone of the user interface of a cloud-hosted application based on user behavior patterns are provided herein. A computer-implemented method includes analyzing behavior of a user with respect to one or more software applications; automatically detecting, from a pre-established collection of multiple software tone settings, one or more appropriate software tone settings to be applied to the one or more software applications based on the analyzed behavior; dynamically updating the software tone settings of the one or more software applications, wherein updating comprises (i) defining the value for one or more strings of the one or more software applications as one or more run-time attributes and (ii) resolving the one or more run-time attributes upon detecting the one or more appropriate software tone settings; and outputting the one or more dynamically updated software applications to at least a display.

Abstract: Methods, systems, and computer program products for a collaborative cognition platform for creating and hosting social machines are provided herein. A computer-implemented method includes creating a social machine for collaborative tasks, wherein the social machine comprises (i) one or more human agents, (ii) one or more machine-based agents, (iii) an algorithm, and (iv) a set of rules prescribed for executing the collaborative tasks. The method also includes generating one or more collaborative resolutions for the collaborative tasks by executing, in an automated fashion, the collaborative tasks via implementation of the algorithm, wherein the algorithm facilitates, in accordance with the set of rules, systematic iterations of collaboration among (i) the one or more human agents and (ii) the one or more machine-based agents. Further, the method includes outputting the one or more collaborative resolutions to at least one user.

Abstract: Provided are techniques for providing dynamic throttling thresholds. A request from a client is received. A request count is incremented. A current dynamic throttling threshold is selected based on the request. In response to determining that the request count is less than the current dynamic throttling threshold, the request is sent to a server for processing and a response and a response time are received from the server. In response to determining one of 1) that the request count equals or exceeds a recalculation count and 2) that a time interval for recalculation has ended, a new dynamic throttling threshold is calculated using the response time and the current dynamic throttling threshold is set to the new dynamic throttling threshold. Then, the response is returned to the client. In response to determining that the request count is not less than the current dynamic throttling threshold, the request is throttled.

Abstract: A method can include evaluating each of a plurality of collaborative systems, using a processor, for suitability hosting an artifact according to at least one attribute of the artifact. A first collaborative system can be selected from the plurality of collaborative systems according to the evaluation. The artifact can be stored in the first collaborative system.

Abstract: At least one unique collection of storage artifacts can be specified to indicate that the storage artifact is a member of the unique collection. Each storage artifact can be a discrete object comprising digitally encoded content that is stored as a node within a tree structure of a tangible storage medium. The collection can be referenced by a set of different storage artifacts to form a collection of related storage artifacts. Each storage artifact can correspond to different collections, wherein membership within a collection is independent of a storage path within the tree structure. A file management action relating to the storage artifact can be performed. The file management action can be dependent upon the storage artifact being a member of the unique collection.

Abstract: An embodiment may be a cognitive event based file sharing system. The embodiment may include receiving a file share request by a user, wherein the file share request comprises a file selected for access by intended file recipients. The embodiment may include determining a storage capacity of a computing device of the user. The embodiment may include determining a storage capacity of computing devices of the intended file recipients. The embodiment may include allocating the file based on the storage capacity of the computing device of the user, the storage capacity of the computing devices of the intended file recipients, and a file management policy. The embodiment may include providing access to the file to the intended file recipients. The embodiment may include removing a portion of the file from at least one of the computing devices of the intended file recipients based on the occurrence of a specified event.

Abstract: A method can include evaluating each of a plurality of collaborative systems, using a processor, for suitability hosting an artifact according to at least one attribute of the artifact. A first collaborative system can be selected from the plurality of collaborative systems according to the evaluation. The artifact can be stored in the first collaborative system.

Abstract: At least one unique collection of storage artifacts can be specified to indicate that the storage artifact is a member of the unique collection. Each storage artifact can be a discrete object comprising digitally encoded content that is stored as a node within a tree structure of a tangible storage medium. The collection can be referenced by a set of different storage artifacts to form a collection of related storage artifacts. Each storage artifact can correspond to different collections, wherein membership within a collection is independent of a storage path within the tree structure. A file management action relating to the storage artifact can be performed. The file management action can be dependent upon the storage artifact being a member of the unique collection.

Abstract: One embodiment provides a method, including: receiving a requisition for a job position, the requisition having a plurality of recruiters, each having influence in selecting a candidate; generating a profile for an ideal candidate comprising (i) a plurality of attributes and (ii) weights corresponding to each of the attributes; receiving, for a plurality of candidates, profiles for each the candidates; comparing the profile of each of the plurality of candidates against the ideal candidate, using a distance method computation to determine the distance between the plurality of candidates and the ideal candidate based upon the weights; ranking the plurality of candidates and providing the ranking to each of the plurality of recruiters; receiving input from each of the plurality of recruiters that modifies the ranking, recalculating the weights of the attributes based upon the modified ranking, and modifying the ranking; and providing a final ranking of the plurality of candidates.