Click-Through Rate Analysis for Understanding User Behavior in Information Retrieval

Improving user satisfaction and personalization in information retrieval is an ongoing challenge. This research delves into user behavior analysis using click-through data, providing a deeper understanding of user intent beyond initial interactions. This article utilizes click-through analysis to uncover user preferences, resulting in search results that align more closely with user intent. These insights contribute to more refined search experiences, enhancing user satisfaction and personalization across digital platforms. The experimental outcomes demonstrate the effectiveness of the proposed approach for capturing user preferences and tailoring search results accordingly.