AUTOMATIC AGGREGATION ACROSS DATA STORES AND CONTENT TYPES

An analysis module, when triggered by a synchronization framework when a new data item is added to a project data store, runs a series of analysis feature extractors on the new content. An analysis may be conducted, and features of interest may be extracted from the data item. The analysis utilizes...

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Hauptverfasser: GAMON, MICHAEL, TER HORST, PAULUS WILLEM, CALDWELL, NICHOLAS, CHITRAPU, ARUN, CAI, YIZHENG, WANG, YE-YI, PHAN, TU HUY, WALVEKAR, MUKTA PRAMOD, CALCAGNO, MICHAEL, CHILDS, BENJAMIN EDWARD, DIMMICK, STEVEN, POWELL, KEVIN, CHILAKAMARRI, VENKAT PRADEEP, LUDWIG, JONATHAN C, AZZAM, SALIHA, SHAH, JIGNESH, SHARMA, ASHISH, KUO, SHIUN-ZU, KOHLMEIER, BERNHARD SJ, MANIS, KIMBERLY, O'KEEFE, COURTNEY ANNE, PEREZ DEL CARPIO, DIEGO
Format: Patent
Sprache:eng ; fre ; ger
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Zusammenfassung:An analysis module, when triggered by a synchronization framework when a new data item is added to a project data store, runs a series of analysis feature extractors on the new content. An analysis may be conducted, and features of interest may be extracted from the data item. The analysis utilizes natural language processing, as well as other technologies, to provide an automatic or semi-automatic extraction of information. The extracted features of interest are saved as metadata within the project data store, and are associated with the data item from which it was extracted. The analysis module may be utilized to discover additional information that may be gleaned from content that is already in the project data store.