Conferenceclassification

Conferenceclassification refers to the process of assigning conferences to standardized topic areas and, in some systems, quality categories to support the organization and retrieval of conference proceedings. It is used by digital libraries, indexing services, and bibliometric platforms to map conferences to domains such as artificial intelligence, databases, and networks, and to help users and systems navigate scholarly output.

Taxonomies such as the ACM Computing Classification System and IEEE Taxonomy provide structured topic codes that can be assigned to conferences based on their scope, tracks, and typical topics of presented papers. Classification can be done manually by domain experts or automatically through machine learning on conference metadata (titles, abstracts, keywords, tracks) and historical publication records. Methods include supervised learning, unsupervised clustering, and topic modeling.

Outputs include topic labels, field codes, and sometimes prestige or tier classifications (for example, conference rankings). These classifications support search and filtering, conference recommendations, and bibliometric analyses, as well as institutional evaluation and research trend monitoring.

Common challenges include name ambiguity (similar or changing conference names), scope drift as conferences broaden or narrow their aims, multi-disciplinary conferences that span several topics, and keeping taxonomies up to date with emerging fields.

Related taxonomies and rankings include the ACM CCS, IEEE Taxonomy, CORE conference rankings, Scopus subject areas, and Google Scholar classification.