An Architecture to Research Aggregated Vertical Web Search Results

Conventional search engines often present users with ranked lists of search results, necessitating manual sifting through documents to extract information. This approach restricts exploring web-based multimedia content, mainly using vertical search engines. Interacting with influences from various verticals can lead to a loss of exploration context, making it challenging to assemble relevant information and requiring extensive scrolling and clicking. To address these limitations, we propose an architecture for investigating vertical web search results, enabling a comprehensive exploration of aggregated multimedia documents. Our system employs advanced techniques, including clustering and summarization, to efficiently organize search results and enhance user interaction. It incorporates non-linear representations, such as tree maps and pie-chart visualizations, to offer an intuitive and interactive exploration experience. The designed Search User Interface (SUI) evaluates user behavior while interacting with multimedia documents and verticals. This enables seamless exploration across disjoint verticals, maximizing contextual understanding and cognitive engagement. The evaluation of our proposed system showcased promising results as it attained a B+ grade, placing it within the 80 to 84 percentile range, validating the effectiveness and efficiency of the proposed approach.