Indexing in Information Retrieval: Concept, Evolution, Process, and the Balance Between Recall and Precision

Indexing is the core process that enables effective Information Retrieval (IR) by transforming raw documents into structured, searchable representations. The quality of an IR system is largely determined by how well indexing captures the conceptual content of documents and supports efficient access to relevant information. This work presents an overview of indexing as both a theoretical concept and a practical mechanism, examining its definition, objectives, historical evolution, and role in modern information systems. It traces the progression from early manual cataloguing practices and hierarchical classification systems, such as the Dewey Decimal Classification, to computerized indexing milestones including MARC and early online retrieval systems. The shift toward total document indexing in the 1990s, driven by reduced computing costs and the availability of full-text digital documents, marked a significant transformation in retrieval practices. The study highlights the changing role of human indexers, emphasizing concept abstraction and value judgment, while automated systems handle large-scale, exhaustive indexing. Different types of index coverage document files, public index files, and private index files are discussed to illustrate how modern systems balance comprehensive coverage with selective relevance. Finally, the fundamental trade-off between recall and precision is examined, showing how contemporary IR systems integrate automatic and manual indexing approaches to achieve both broad retrieval and high relevance.