An open-source framework for ExpFinder integrating $N$-gram Vector Space Model and $μ$CO-HITS
This work addresses expert finding for academic and research collaborations, but it appears incremental as it combines existing techniques.
The authors tackled the problem of expert finding by developing ExpFinder, an ensemble model that integrates an N-gram vector space model and a graph-based model, which significantly outperforms other expert finding models.
Finding experts drives successful collaborations and high-quality product development in academic and research domains. To contribute to the expert finding research community, we have developed ExpFinder which is a novel ensemble model for expert finding by integrating an $N$-gram vector space model ($n$VSM) and a graph-based model ($μ$CO-HITS). This paper provides descriptions of ExpFinder's architecture, key components, functionalities, and illustrative examples. ExpFinder is an effective and competitive model for expert finding, significantly outperforming a number of expert finding models.