Difference between revisions of "The Pitt Grapevine"

Latest revision as of 18:18, 29 March 2024

About the project

The goal of the project is to connect students with research advisors at the University of Pittsburgh through an interactive recommender system.

The project was originally funded by the University of Pittsburgh through the Personalized Education program (2018-2020), however, it is still going on, several years after the end of the two original rounds of funding. In the course of the project, we developed and evaluated several versions of the interactive recommender system Grapevine.

Motivation

Systems

Grapevine - an interactive recommender system to help students in finding research advisors

Team

PIs: Peter Brusilovsky, Eliza Beth Littleton, Dmitriy Babichenko

Behnam Rahdari: The main developer of 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)

@@ Line 2: / Line 2: @@
 The goal of the project is to connect students with research advisors at the University of Pittsburgh through an interactive recommender system.
-Supported by the University of Pittsburgh through the Personalized Education program (2018-2020)
+The project was originally funded by the University of Pittsburgh through the [https://www.provost.pitt.edu/priorities/personalizing-education Personalized Education] program (2018-2020), however, it is still going on, several years after the end of the two original rounds of funding. In the course of the project, we developed and evaluated several versions of the interactive recommender system Grapevine.
-The project explored the use of personalization and mobile computing to increase user engagement in location-bound social systems. The project was originally funded by a Research Award from Google to Peter Brusilovsky, however it continued for many years following the original round of funding. In the course of the project we developed, extended, and explored several location-bounded systems such as Comet, Eventur, and CourseAgent. These systems were actively used for many years in local Pittsburgh community. We developed a range of new recommendation technologies for these systems and explored new approaches to increase user engagement, which is the source of knowledge in local communities
 == Motivation ==
-Social computing systems can serve as a tool for revitalizing and strengthening local communities - in particular by supporting online community information commons for enriching and actively disseminating information about local events, activities, and organizations. While existing social linking systems can allow people to follow or meet each other, they tend to do so in decontextualized virtual spaces and as a result are seen by many as a threat to local communities. In contrast, a social information system that provides a community information commons for collecting, organizing and exploring information about local events and organizations, has the potential to increase individuals’ awareness and connection with their community. However, creating an effective community information commons is challenging.
-First, information about local events, activities and organizations is often fragmented, incomplete, and difficult to find. While existing channels work well for organizations able to devote resources to formal marketing and advertising, a sustainable community information commons must allow a more diverse set of community members to participate in collection and organization information in a decentralized fashion. Social computing technologies and techniques have the potential to provide a platform through which the small efforts of individuals, both within a community and beyond, can be mobilized to increase the quality of information available about local events, activities, and organizations.  However, in spite of their potential, engaging users in social computing systems can be challenging. Users are eager to contribute for their own good (i.e., list an item to sell on Craigslist), but very hesitant to do it for a community good. Local community information systems must pursue different engagement strategies if they are to provide a useful, organized source of information about local events and activities.
-At the same time, any system that is even moderately successful at aggregating information about community events has to be personalized. No one is interested all events and organizations. Even in a small community, the ability to focus in items of interest within a larger information stream is necessary. A viable community information commons must support personalized information access, enabling individuals to increase the likelihood of seeing personally interesting materials and decrease the distraction of irrelevant events.
-The goal of this project is to investigate the nature of community information commons and develop social computing technologies and techniques to increase the impact and viability of these critical socio-technical systems.
 == Systems ==
-* [[Grapevine]] [[Grapevine|more]]
+* [[Grapevine]] - an interactive recommender system to help students in finding research advisors
 == Team ==
-* '''PIs:'''  [[User:Peterb|Peter Brusilovsky]]:
+* '''PIs:'''  [[User:Peterb|Peter Brusilovsky]], Eliza Beth Littleton, Dmitriy Babichenko
 * Behnam Rahdari: The main developer of Grapevine system
@@ Line 28: / Line 19: @@
 == 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 ([https://doi.org/10.1145%2F3372923.3404797 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 ([https://doi.org/10.1002/pra2.271 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. ([https://ceur-ws.org/Vol-2948/short3.pdf 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. ([https://doi.org/10.1145%2F3460231.3478879 paper])

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