Designing a Metadata-Driven Semantic Search Interface for Literary Works
Abstract
In this paper, we design and implement an intelligent interface for classification and retrieval of digital literary works within a search interface system based on standardized metadata. By building on the Dublin Core metadata schema, which supports automated indexing and retrieval processes based on attributes such as author, title, genre, language, and subject, it offers automated indexing and retrieval by way of attributes. The system is built on a modular architecture with Metadata Extraction, Indexing Engine, Search Interface components. Semantic search and multi-criteria filtering capabilities increase search accuracy and contextual relevance. Experimental analysis of 2,500 literary records validated its performance with respect to retrieval speed and semantic consistency, compared to the conventional keyword-based methods. The paper concludes by outlining future prospects for extending the system to multilingual environments and incorporating ontological models for enriched semantic representation in digital libraries for enriched semantic representation in digital libraries.