Abstract
Helping Interdisciplinary Vocabulary Engineering (HIVE) is an automatic indexing, machine learning technology that addresses cost, interoperability and usability challenges associated with traditional vocabulary frameworks. HIVE supports dynamic subject metadata generation using multiple SKOS encoded controlled vocabularies. Kea++/Maui algorithms are used for the machine learning activity. Professionally indexed documents representing the gold standard are processed via Kea++ or Maui, to train HIVE. The HIVE-ES (España) initiative extends HIVE to Spanish language vocabularies. This chapter introduces HIVE automatic indexing capabilities and reports on training the HIVE-ES server in connection with the Wine Thesaurus, a SKOSified vocabulary in Spanish. The results highlight the value of the HIVE approach for information management systems seeking to work with multiple vocabularies for metadata generation in an intelligent manner.
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