Digital libraries (DLs) are a resource for answering complex questions. Up to now, such systems mainly support keyword-based searching and browsing. The mapping from a research question to keywords and the assessment whether an article is relevant for a research question is completely with the user. In this paper, we present a two-layered digital library model. The aim is to enhance current DLs to support different levels of human cognitive acts, thus enabling new kinds of knowledge exchange among library users. The low layer of the model, namely, the tactical cognition support layer, provides users with requested relevant documents, as searching and browsing do. The upper layer of the model, namely, the strategic cognition support layer, not only provides users with relevant documents but also directly and intelligently answers users' cognitive questions. On the basis of the proposed model, we divide the DL information space into two subspaces, i.e., a knowledge subspace and a document subspace, where documents in the document subspace serves as the justification for the corresponding knowledge in the knowledge subspace. Detailed description of the knowledge subspace and its construction, as well as query facilities against the enhanced DLs for users' knowledge sharing and exchange, are particularly discussed.
- DB-IRNOX: INFORMATION RETRIEVAL (NON-XML)
- DB-DM: DATA MINING
Feng, L., Jeusfeld, M. A., & Hoppenbrouwers, J. (2005). Beyond Information Searching and Browsing: Acquiring Knowledge from Digital Library. Information processing & management, 41(1), 97-120. [10.1016/j.ipm.2004.04.005]. https://doi.org/10.1016/j.ipm.2004.04.005