Words as Bridges: Exploring Computational Support for Cross-Disciplinary Translation Work
This work addresses the challenge for scholars seeking to explore literature outside their own discipline, though it is incremental as it adapts existing techniques to a new application.
The paper tackled the problem of cross-disciplinary literature exploration hindered by field-specific jargon by developing a prototype search engine that uses aligned domain-specific word embeddings to preserve jargon as conceptual bridges, and tested it in two case studies to provide qualitative insights.
Scholars often explore literature outside of their home community of study. This exploration process is frequently hampered by field-specific jargon. Past computational work often focuses on supporting translation work by removing jargon through simplification and summarization; here, we explore a different approach that preserves jargon as useful bridges to new conceptual spaces. Specifically, we cast different scholarly domains as different language-using communities, and explore how to adapt techniques from unsupervised cross-lingual alignment of word embeddings to explore conceptual alignments between domain-specific word embedding spaces.We developed a prototype cross-domain search engine that uses aligned domain-specific embeddings to support conceptual exploration, and tested this prototype in two case studies. We discuss qualitative insights into the promises and pitfalls of this approach to translation work, and suggest design insights for future interfaces that provide computational support for cross-domain information seeking.