Augmenting Scientific Creativity with Retrieval across Knowledge Domains
Abstract
Exposure to ideas in domains outside a scientist's own may benefit her in reformulating existing research problems in novel ways and discovering new application domains for existing solution ideas. While improved performance in scholarly search engines can help scientists efficiently identify relevant advances in domains they may already be familiar with, it may fall short of helping them explore diverse ideas \textit{outside} such domains. In this paper we explore the design of systems aimed at augmenting the end-user ability in cross-domain exploration with flexible query specification. To this end, we develop an exploratory search system in which end-users can select a portion of text core to their interest from a paper abstract and retrieve papers that have a high similarity to the user-selected core aspect but differ in terms of domains. Furthermore, end-users can `zoom in' to specific domain clusters to retrieve more papers from them and understand nuanced differences within the clusters. Our case studies with scientists uncover opportunities and design implications for systems aimed at facilitating cross-domain exploration and inspiration.
- Publication:
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arXiv e-prints
- Pub Date:
- June 2022
- DOI:
- arXiv:
- arXiv:2206.01328
- Bibcode:
- 2022arXiv220601328K
- Keywords:
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- Computer Science - Information Retrieval;
- Computer Science - Computation and Language
- E-Print:
- NLP+HCI Workshop at NAACL 2022