Understanding user behavior in search systems is essential for improving retrieval effectiveness and user satisfaction. While prior research has extensively examined general-purpose web search engines, domain-specific contexts—such as sports information—remain comparatively underexplored. In this study, we analyze over 400,000 interaction log entries from a sports-oriented search engine collected over a two-week period. Our analysis combines classic query-level metrics (e.g., frequency distributions, query lengths) with a detailed examination of click behavior, including entropy-based intent variability and a custom query quality scoring model. Compared to established baselines from general and specialized search environments, we observe a high proportion of new and single-term queries, as well as a notable lack of representativeness among top queries. These findings reveal patterns shaped by the event-driven and entity-centric nature of sports content, offering actionable insights for the design of domain-specific retrieval systems.

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User Behavior in Sports Search: Entity-Centric Query and Click Log Analysis

  • João Damas,
  • Sérgio Nunes

摘要

Understanding user behavior in search systems is essential for improving retrieval effectiveness and user satisfaction. While prior research has extensively examined general-purpose web search engines, domain-specific contexts—such as sports information—remain comparatively underexplored. In this study, we analyze over 400,000 interaction log entries from a sports-oriented search engine collected over a two-week period. Our analysis combines classic query-level metrics (e.g., frequency distributions, query lengths) with a detailed examination of click behavior, including entropy-based intent variability and a custom query quality scoring model. Compared to established baselines from general and specialized search environments, we observe a high proportion of new and single-term queries, as well as a notable lack of representativeness among top queries. These findings reveal patterns shaped by the event-driven and entity-centric nature of sports content, offering actionable insights for the design of domain-specific retrieval systems.