DETERMINING TERM SCORES BASED ON A MODIFIED INVERSE DOMAIN FREQUENCY

Determining term scores based on a modified inverse domain frequency is disclosed. One example is a system including a data processing engine, an evaluator, and a data analytics module. The data processing engine identifies a key term associated with a system, and a sub-plurality of a plurality of d...

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Bibliographische Detailangaben
Hauptverfasser: Maurer Ron, Fischer Mani, Awad Morad, Maor Alina, Elgrably Gil, Krohn Mike, Shain Olga, Nor Igor, Keshet Renato, Shaked Doron
Format: Patent
Sprache:eng
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Zusammenfassung:Determining term scores based on a modified inverse domain frequency is disclosed. One example is a system including a data processing engine, an evaluator, and a data analytics module. The data processing engine identifies a key term associated with a system, and a sub-plurality of a plurality of documents, the sub-plurality of documents associated with the event. The evaluator determines, based on the presence or absence of the key term, a first distribution related to the sub-plurality of documents, and a second distribution related to the plurality of documents, and evaluates, for the key term, a term score based on the first distribution and the second distribution, the term score indicative of a modified inverse domain frequency based on the sub-plurality of documents. The data analytics module includes the key term in a word cloud when the term score for the key term satisfies a threshold.