Abstract: A contribution management system and process for facilitating the identification of individual users who have made contributions to an electronic content item, and the extent of that contribution. As an example, a reader may review the list of contributors with a representation of their relative degree or amount of contribution to the document, and also allow for access to other documents that have been developed by the identified contributor. These tools can provide collaborative document users the ability to more clearly distinguish casual contributors or non-contributing owners of the document from higher-level contributors whose authorship has significantly shaped the content. In addition, the listing or identification of top contributors can be configured to facilitate communication between an interested reader and the identified contributor, which increases the ease with which members of larger organizations can collaborate, seek mentorship, or develop useful relationships.

Abstract: A system for determining qualified contributors of a document is provided. A system can analyze user activities associated with a document to provide meaningful insights indicating the key contributors of the document based on a contributor policy. The contributor policy defines contribution factors and criteria that is used to determine when a user is deemed as a qualified contributor. The contribution factors can be used in an analysis of one or more user activities to determine a contribution score for each user associated with a document. The contribution scores of the users can be compared with a threshold to identify qualified contributors. The identified users are listed as qualified contributors of the document and associated with the document in the metadata. The contributor information can be utilized to inform readers of the document, identity expertise of these contributors, or recommend relevant documents to the contributors.

Abstract: The techniques disclosed herein enable a system to drive collaboration between users by analyzing user interactions with productivity applications. The system provides intelligence mechanisms that work in concert with telemetry mechanisms to create interactive experiences that encourage users to embrace technology, improve productivity, and increase collaboration. In some configurations, the system can drive collaboration between users by correlating signals that define user interactions with individual productivity applications with contextual data that indicates how time has been allocated. During, or upon completion of a group activity, the system can identify individuals of interest and enable a user to readily share relevant files with the identified individuals.

Abstract: A contribution management system and process for facilitating the identification of individual users who have made contributions to an electronic content item, and the extent of that contribution. As an example, a reader may review the list of contributors with a representation of their relative degree or amount of contribution to the document, and also allow for access to other documents that have been developed by the identified contributor. These tools can provide collaborative document users the ability to more clearly distinguish casual contributors or non-contributing owners of the document from higher-level contributors whose authorship has significantly shaped the content. In addition, the listing or identification of top contributors can be configured to facilitate communication between an interested reader and the identified contributor, which increases the ease with which members of larger organizations can collaborate, seek mentorship, or develop useful relationships.

Abstract: A system for determining qualified contributors of a document is provided. A system can analyze user activities associated with a document to provide meaningful insights indicating the key contributors of the document based on a contributor policy. The contributor policy defines contribution factors and criteria that is used to determine when a user is deemed as a qualified contributor. The contribution factors can be used in an analysis of one or more user activities to determine a contribution score for each user associated with a document. The contribution scores of the users can be compared with a threshold to identify qualified contributors. The identified users are listed as qualified contributors of the document and associated with the document in the metadata. The contributor information can be utilized to inform readers of the document, identity expertise of these contributors, or recommend relevant documents to the contributors.

Abstract: The techniques disclosed herein enable a system to drive collaboration between users by analyzing user interactions with productivity applications. The system provides intelligence mechanisms that work in concert with telemetry mechanisms to create interactive experiences that encourage users to embrace technology, improve productivity, and increase collaboration. In some configurations, the system can drive collaboration between users by correlating signals that define user interactions with individual productivity applications with contextual data that indicates how time has been allocated. During, or upon completion of a group activity, the system can identify individuals of interest and enable a user to readily share relevant files with the identified individuals.

Abstract: MCR provided estimated pure component time series spectra as extracted from infrared or other spectroscopy is capable of being compared to spectra in a reference library to find the best matches. The best match spectra can then each in turn be combined with the reference spectra, with the combinations also being screened for best matches versus any one of the estimated pure component time series spectra. These resulting best matches can then also undergo the foregoing combination and comparison steps. The process can repeat in this manner in an unbounded fashion if desired until an appropriate stopping point is reached, for example, when a desired number of best matches are identified, when some predetermined number of iterations has been performed, etc. This methodology is able to return best-match spectra with far fewer computational steps and greater speed than if all possible combinations of reference spectra are considered.

Abstract: An unknown spectrum obtained from infrared or other spectroscopy can be compared to spectra in a reference library to find the best matches. The best match spectra can then each in turn be combined with the reference spectra, with the combinations also being screened for best matches versus the unknown spectrum. These resulting best matches can then also undergo the foregoing combination and comparison steps. The process can repeat in this manner until an appropriate stopping point is reached, for example, when a desired number of best matches are identified, when some predetermined number of iterations has been performed, etc. This methodology is able to return best-match spectra (and combinations of spectra) with far fewer computational steps and greater speed than if all possible combinations of reference spectra are considered.

Abstract: An unknown spectrum obtained from infrared or other spectroscopy can be compared to spectra in a reference library to find the best matches. The best match spectra can then each in turn be combined with the reference spectra, with the combinations also being screened for best matches versus the unknown spectrum. These resulting best matches can then also undergo the foregoing combination and comparison steps. The process can repeat in this manner until an appropriate stopping point is reached, for example, when a desired number of best matches are identified, when some predetermined number of iterations has been performed, etc. This methodology is able to return best-match spectra (and combinations of spectra) with far fewer computational steps and greater speed than if all possible combinations of reference spectra are considered.