تقرير
Unsupervised Search Algorithm Configuration using Query Performance Prediction
| العنوان: | Unsupervised Search Algorithm Configuration using Query Performance Prediction |
|---|---|
| المؤلفون: | Roitman, Haggai |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Information Retrieval, Computer Science - Computation and Language |
| الوصف: | Search engine configuration can be quite difficult for inexpert developers. Instead, an auto-configuration approach can be used to speed up development time. Yet, such an automatic process usually requires relevance labels to train a supervised model. In this work, we suggest a simple solution based on query performance prediction that requires no relevance labels but only a sample of queries in a given domain. Using two example usecases we demonstrate the merits of our solution. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2210.00767 |
| رقم الأكسشن: | edsarx.2210.00767 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |