Grapevine

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Finding a suitable research advisor is a significant challenge for undergraduate students, especially for those who are new to the intricacies of academic research. Grapevine addresses this challenge by offering a tailored system that simplifies the process of matching students with research advisors. It's particularly beneficial for first-generation college students who may not have prior exposure to navigating academic environments. Grapevine's aim is to facilitate these students' entry into the research domain, providing a supportive tool to identify advisors whose interests align with their own.

Grapevine System


The interface of Grapevine, illustrated in Figure 1, is user-centric and intuitive. It features a search box, a list of suggested keywords, sliders for adjusting research interests, and a display of potential advisors. This design enables students to actively engage in refining their research preferences, helping them to clarify and articulate their interests more effectively. Detailed advisor profiles, as seen in Figure 2, offer in-depth information about each advisor’s research areas, assisting students in making informed decisions. The system's underlying knowledge graph, shown in Figure 3, links advisors, research topics, and keywords to generate personalized recommendations, adapting to each student's evolving research interests.

Grapevine System

In essence, Grapevine serves as a practical and accessible platform for undergraduate students embarking on their research journeys. It's designed to demystify the process of finding a research advisor, making it more approachable and aligned with individual student needs. By leveraging technology to connect students with compatible advisors, Grapevine hopes to contribute to creating a supportive environment for the next generation of researchers.

Grapevine System

Publications

  • Rahdari, B., Brusilovsky, P., and Babichenko, D. (2020) Personalizing Information Exploration with an Open User Model. In: Proceedings of 31st ACM Conference on Hypertext and Social Media, July 13-15, 2020, ACM, pp. 167-176 (paper)
  • Rahdari, B., Brusilovsky, P., Babichenko, D., Littleton, E. B., Patel, R., Fawsett, J., and Blum, Z. (2020) Grapevine: A profile‐based exploratory search and recommendation system for finding research advisors. In: Proceedings of 83rd Annual Meeting of the Association for Information Science & Technology, October 25-29, 2020 (paper)
  • Rahdari, B., Brusilovsky, P., and Sabet, A. J. (2021) Controlling Personalized Recommendations in Two Dimensions with a Carousel-Based Interface. In: Proceedings of Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS’21) at 2021 ACM Conference on Recommender Systems (RecSys’21), September 25, 2021, CEUR, pp. 112-122. (paper)
  • Rahdari, B., Brusilovsky, P., and Sabet, A. J. (2021) Connecting Students with Research Advisors Through User-Controlled Recommendation. In: Proceedings of Fifteenth ACM Conference on Recommender Systems, Amsterdam, Netherlands, 27 September 2021 - 1 October 2021, ACM, pp. 745-748. (paper)