Applying domain knowledge and academic information to enhance unknown-item search in OPAC

Abstract

Many students usually use the unknown-item search strategies, including subject and keyword searches, to retrieve books or other materials provided in library catalogs. However, the success rates for unknown-item searching is relatively low compared with the known-item search strategies, i.e., title or author searches. In this paper, a framework for improving the unknown-item search is proposed. The main contributions of our framework concern both user's keywords and book indexing: (i) To enhance a user's keyword, the framework will select other relevant terms in a domain-related ontology; (ii) Topics expressed in course description are used as book indexing. A preliminary experiment shows that the proposed framework gives satisfactory results in terms of the numbers and the precision scores of retrieved books. Furthermore, the proposed interesting-score measure can facilitate to lift the precision levels.

Using Linked Data Sources to Enhance Catalog Discovery

“…The foil to known item search, serendipitous discovery, has been more difficult to facilitate in an online discovery system. As Intarapaiboon and Kesamoon (2019) point out, the user experience for unknown item searching in library catalogs is sometimes lacking and could benefit from browsing aided by domain ontologies. While rooted in a common refrain of library users seeking to recreate shelf browsing or coming across materials in a physical space, serendipitous discovery in the online context has often been ignored.…”