Name
Abstract | ||
|---|---|---|
One key challenge in talent search is how to translate complex criteria of a hiring position into a search query. This typically requires deep knowledge on which skills are typically needed for the position, what are their alternatives, which companies are likely to have such candidates, etc. However, listing examples of suitable candidates for a given position is a relatively easy job. Therefore, in order to help searchers overcome this challenge, we design a next generation of talent search paradigm at LinkedIn: Search by Ideal Candidates. This new system only needs the searcher to input one or several examples of suitable candidates for the position. The system will generate a query based on the input candidates and then retrieve and rank results based on the query as well as the input candidates. The query is also shown to the searcher to make the system transparent and to allow the searcher to interact with it. As the searcher modifies the initial query and makes it deviate from the ideal candidates, the search ranking function dynamically adjusts an refreshes the ranking results balancing between the roles of query and ideal candidates. As of writing this paper, the new system is being launched to our customers. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1145/2872518.2890549 | WWW (Companion Volume) |
DocType | Volume | Citations |
Conference | abs/1602.08186 | 10 |
PageRank | References | Authors |
0.75 | 4 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Viet Ha-thuc | 1 | 89 | 10.38 |
| Ye Xu | 2 | 275 | 14.97 |
| Satya Pradeep Kanduri | 3 | 10 | 0.75 |
| Xianren Wu | 4 | 152 | 13.20 |
| Vijay Dialani | 5 | 142 | 12.30 |
| Yan Yan | 6 | 691 | 31.13 |
| Abhishek Gupta | 7 | 30 | 2.74 |
| Shakti Sinha | 8 | 33 | 3.87 |