A Proposal of the Information Retrieval System Based on the Generalized One-Sided Concept Lattices

One of the important issues in information retrieval is to provide methods suitable for searching in large textual datasets. Some improvement of the retrieval process can be achieved by usage of conceptual models created automatically for analysed documents. One of the possibilities for creation of such models is to use well-established theory and methods from the area of Formal Concept Analysis. In this work we propose conceptual models based on the generalized one-sided concept lattices, which are locally created for subsets of documents represented by object-attribute table (document-term table in case of vector representation of text documents). Consequently, these local concept lattices are combined to one merged model using agglomerative clustering algorithm based on the descriptive (keyword-based) representation of particular lattices. Finally, we define basic details and methods of IR system that combines standard full-text search and conceptual search based on the extracted conceptual model.