A Novel Combined Term Suggestion Service for Domain-Specific Digital Libraries

TL;DR

This paper presents a new combined term suggestion service for domain-specific digital libraries, demonstrating that integrating thesaurus and statistical methods improves user query formulation and search effectiveness.

Contribution

The paper introduces a novel combined term suggestion approach that outperforms existing methods by integrating thesaurus and statistical relations for domain-specific search assistance.

Findings

Thesaurus-based suggestions are most frequently used.

Domain-specific vocabularies aid in alternative concept discovery.

Combined approach outperforms single-method suggestions.

Abstract

Interactive query expansion can assist users during their query formulation process. We conducted a user study with over 4,000 unique visitors and four different design approaches for a search term suggestion service. As a basis for our evaluation we have implemented services which use three different vocabularies: (1) user search terms, (2) terms from a terminology service and (3) thesaurus terms. Additionally, we have created a new combined service which utilizes thesaurus term and terms from a domain-specific search term re-commender. Our results show that the thesaurus-based method clearly is used more often compared to the other single-method implementations. We interpret this as a strong indicator that term suggestion mechanisms should be domain-specific to be close to the user terminology. Our novel combined approach which interconnects a thesaurus service with additional statistical relations out-performed all other implementations. All our observations show that domain-specific vocabulary can support the user in finding alternative concepts and formulating queries.