This paper presents our work done by team RAND (University of Padua) on LongEval-Web Retrieval challenge, which investigates the robustness and stability of Web search engines in the context of evolving document collections. Our team began by analyzing the dataset and applying standard IR techniques to establish baseline performance. We then iteratively refined our approach by focusing on methods that demonstrated improved effectiveness in handling temporal changes across snapshots.
Team RAND at LongEval: Composable Information Retrieval with Semantic and Language-Aware Components
Ferro N.
2025
Abstract
This paper presents our work done by team RAND (University of Padua) on LongEval-Web Retrieval challenge, which investigates the robustness and stability of Web search engines in the context of evolving document collections. Our team began by analyzing the dataset and applying standard IR techniques to establish baseline performance. We then iteratively refined our approach by focusing on methods that demonstrated improved effectiveness in handling temporal changes across snapshots.
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