- From: W3C Community Development Team <team-community-process@w3.org>
- Date: Fri, 13 Nov 2015 17:23:28 +0000
- To: public-collaboration@w3.org
A number of technologies including Office Graph can ensure that relevant, fresh, information and documents are available to individuals and groups during the performance of their tasks. Items that can be recommended, that can be routed, sorted and presented include documents, multimedia and data. Office Graph utilizes sophisticated machine learning algorithms to connect people to the relevant content, conversations and people around them, including based upon their multiple simultaneous interests, tasks, groups or roles. Innovations are possible with regard to the determination of contextual, task-based, relevance for routing and presenting content to individuals and groups, enhancing their performance or providing them with serendipitous discovery. Multi-document natural language processing algorithms can provide new conveniences to groups during their various processes and are interoperable with advanced machine learning algorithms such as those utilized by Office Graph. Multi-document natural language processing technology innovations include, but are not limited to, real-time fact checking, sentiment analysis and spin and persuasion detection. Multi-document natural language processing algorithms process collections of documents and of multimedia utilized by individuals and groups in all scenarios including those of business, education and e-participation. ---------- This post sent on Collaborative Software Community Group 'Recommender Systems, Machine Learning and Multi-document Natural Language Processing' https://www.w3.org/community/collaboration/2015/11/13/recommender-systems-machine-learning-and-multi-document-natural-language-processing/ Learn more about the Collaborative Software Community Group: https://www.w3.org/community/collaboration
Received on Friday, 13 November 2015 17:23:30 UTC