تقرير
Analysis of E-commerce Ranking Signals via Signal Temporal Logic
| العنوان: | Analysis of E-commerce Ranking Signals via Signal Temporal Logic |
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| المؤلفون: | Dreossi, Tommaso, Ballardin, Giorgio, Gupta, Parth, Bakus, Jan, Lin, Yu-Hsiang, Salaka, Vamsi |
| المصدر: | EPTCS 331, 2021, pp. 33-42 |
| سنة النشر: | 2021 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Logic in Computer Science, Computer Science - Formal Languages and Automata Theory, Computer Science - Information Retrieval, Computer Science - Machine Learning |
| الوصف: | The timed position of documents retrieved by learning to rank models can be seen as signals. Signals carry useful information such as drop or rise of documents over time or user behaviors. In this work, we propose to use the logic formalism called Signal Temporal Logic (STL) to characterize document behaviors in ranking accordingly to the specified formulas. Our analysis shows that interesting document behaviors can be easily formalized and detected thanks to STL formulas. We validate our idea on a dataset of 100K product signals. Through the presented framework, we uncover interesting patterns, such as cold start, warm start, spikes, and inspect how they affect our learning to ranks models. Comment: In Proceedings SNR 2020, arXiv:2101.05256 |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.4204/EPTCS.331.3 |
| الوصول الحر: | http://arxiv.org/abs/2101.05415Test |
| رقم الانضمام: | edsarx.2101.05415 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.4204/EPTCS.331.3 |
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