Data Conversion Laboratory (DCL), an industry leader in structured data and content transformations, has announced a major update to its Harmonizer software application. Harmonizer analyses document collections and incorporates Artificial Intelligence (AI) into its text analysis, using Natural Language Processing (NLP) to identify redundant and near redundant content in the collection.
Managers of large document collections often find similar text used in multiple ways with little standardisation. A Harmonizer analysis often reports that on average greater than 50 percent of the text in a document collection is repetitive. Identifying redundancies enables a reduction in the amount of content organisations are managing, thus reducing content management costs and the risk of errors. This latest Harmonizer release also provides more flexible configuration options. Configurable AI algorithms determine content matches, allowing stricter or looser controls to ‘match’ content.
To streamline content management, organisations need to strategically control leaner collections and ensure all business units operate with unified source content. This latest update builds upon previous releases to improve the user experience, making it possible to quickly search for and review content matches. Navigating massive content collections is now easier than ever with a resizable document map appearing alongside the paragraph match report. Improved linking on the document map allows users to quickly jump to the paragraph report that consolidates all content variations into one harmonised paragraph.
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