CROSS-PROVIDER TOPIC CONFLATION
Examples of the present disclosure describe systems and methods for cross-provider topic conflation. In aspects, a request relating to one or more topics may be received by a content surfacing platform. One or more data sources of multiple content providers may be searched for documents relating to...
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| creator | WINN, John M WEBSTER, Samuel ZAYKOV, Yordan VENANZI, Matteo POCHERNINA, Elena MYSHKOV, Pavel GVOZDEV, Vladimir V KOROSTELEV, Ivan MEYERZON, Dmitriy SPENGLER, Alexander A VORONKOV, Nikita |
| description | Examples of the present disclosure describe systems and methods for cross-provider topic conflation. In aspects, a request relating to one or more topics may be received by a content surfacing platform. One or more data sources of multiple content providers may be searched for documents relating to the topic(s). Document content (e.g., document metadata and sentences, phrases, and other word content within the document) relating to the topic(s) may be extracted from the documents of the various content providers. The document content may be classified and/or separated into subparts. The subparts may be clustered and/or conflated by topic, thereby removing duplicated data while preserving the unique information in each subpart. The conflated topics may be stored in a single knowledge base, such as an enterprise knowledge graph, and/or presented in response to the request. |
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| subjects | CALCULATING COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
| title | CROSS-PROVIDER TOPIC CONFLATION |
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