Name
Title | ||
|---|---|---|
Cold-Start User-Based Weighted Collaborative Filtering for an Implicit Recommender System for Research Facilities |
Abstract | ||
|---|---|---|
The developed recommender system recommends research facilities at UNC-CH to researchers that are not necessarily at UNC and identified solely by their name and email-ID. The recommendations are ranked based on an analysis of the researcher's publication records as captured by Google Scholar. The researcher publications record is then compared to the publication records of the researcher at UNC-CH and their usage of the UNC core facilities. The proposed system is composed of two modules: (1) Publication Profile Construction (PPC) and (2) Recommendation Generation (RG). In the PPC, we perform the necessary web crawling and construction of the new researcher profile. We also identify the group of UNC researchers with most similar research publications using a variety of similarity measures. In RG, we incorporate the research facility usage data (implicit data) to compute the similarity between the facilities and the cross investigator list of researchers derived from the PPC. Based on these similarity scores, recommendations are suggested. Therefore, this is an example solution of the cold start problem of figuring out how to suggest recommendations for a new researcher, who has not yet used any research facilities. We use leave-one-out cross-validation to test our method. Essentially, we remove the UNC researcher from our database and treat data as test dataset and train the model on the remaining dataset. We verify whether the recommended facilities match their actual usage. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/CIC.2018.00070 | 2018 IEEE 4th International Conference on Collaboration and Internet Computing (CIC) |
Keywords | Field | DocType |
Recommender System,Collaborative filtering,Jaccard Similarity,Cold Start,Implicit feedback,Google Scholar | Recommender system,Computer vision,Collaborative filtering,Cold start,Ranking,Information retrieval,Computer science,Artificial intelligence,Usage data,Web crawler,Cold start (automotive) | Conference |
ISBN | Citations | PageRank |
978-1-5386-9503-6 | 0 | 0.34 |
References | Authors | |
11 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yogesh S. Kale | 1 | 0 | 0.68 |
| Samantha E. Petrie | 2 | 0 | 0.68 |
| Marwan Bikdash | 3 | 23 | 8.02 |
| Michael D. Topal | 4 | 0 | 0.68 |