Abstract
The aim of LEARNER@ICTIR2017 is to investigate new solutions for LtR. In details, we identify some research areas related to LtR which are of actual interest and which have not been fully explored yet. We solicit the submission of position papers on novel LtR algorithms, on evaluation of LtR algorithms, on dataset creation and curation, and on domain specific applications of LtR. LEARNER@ICTIR2017 will be a gathering of academic people interested in IR, ML and related application areas. We believe that the proposed workshop is relevant to ICTIR since we look for novel contributions to LtR focused on foundational and conceptual aspects, which need to be properly framed and modeled.
| Original language | English |
|---|---|
| Title of host publication | ICTIR 2017 - Proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval |
| Number of pages | 2 |
| Publisher | Association for Computing Machinery, Inc. |
| Publication date | 1 Oct 2017 |
| Pages | 331-332 |
| ISBN (Electronic) | 9781450344906 |
| DOIs | |
| Publication status | Published - 1 Oct 2017 |
| Externally published | Yes |
| Event | 7th ACM SIGIR International Conference on the Theory of Information Retrieval, ICTIR 2017 - Amsterdam, Netherlands Duration: 1 Oct 2017 → 4 Oct 2017 |
Conference
| Conference | 7th ACM SIGIR International Conference on the Theory of Information Retrieval, ICTIR 2017 |
|---|---|
| Country/Territory | Netherlands |
| City | Amsterdam |
| Period | 01/10/2017 → 04/10/2017 |
| Sponsor | ACM Special Interest Group on Information Retrieval (SIGIR) |
Keywords
- Datasets
- Evaluation
- Learning to rank
- User behaviour