A unified strategy for search and result representation for an online bibliographical catalogue

Purpose – One of the biggest concerns of modern information retrieval systems is reducing the user effort required for manual traversal and filtering of long matching document lists. Thus, the first goal of this research is to propose an improved scheme for representation of search results. Further, it aims to explore the impact of various user information needs on the searching process with the aim of finding a unified searching approach well suited for different query types and retrieval tasks. Design/methodology/approach – The BoW online bibliographical catalogue is based on a hierarchical concept index to which entries are linked. The key idea is that searching in the hierarchical catalogue should take advantage of the catalogue structure and return matching topics from the hierarchy, rather than just a long list of entries. Likewise, when new entries are inserted, a search for relevant topics to which they should be linked is required. Therefore, a similar hierarchical scheme for query‐topic matching can be applied for both tasks. Findings – The experiments show that different query types used for the above tasks are best treated by different topic ranking functions. To further examine this phenomenon a user study was conducted, where various statistical weighting factors were incorporated and their impact on the performance for different query types was measured. Finally, it is found that the mixed strategy that applies the most suitable ranking function to each query type yielded a significant increase in precision relative to the baseline and to employing any examined strategy in isolation on the entire set of user queries. Originality/value – The main contributions of this paper are: the alternative approach for compact and concise representation of search results, which were implemented in the BoW online bibliographical catalogue; and the unified or mixed strategy for search and result representation applying the most suitable ranking function to each query type, which produced superior results compared to different single‐strategy‐based approaches.