Recommender Systems, Machine Learning and Multi-document Natural Language Processing [via Collaborative Software Community Group]

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.



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'Recommender Systems, Machine Learning and Multi-document Natural Language
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Received on Friday, 13 November 2015 17:23:30 UTC