Search Result Prefetching on Desktop and Mobile

Abstract

Search result examination is an important part of searching. High page load latency for landing pages (clicked search results) can reduce the efficiency of the search process. Proactively prefetching landing pages in advance of clickthrough can save searchers valuable time. However, prefetching consumes resources (primarily bandwidth and battery) that are wasted unless the prefetched results are requested by searchers. Balancing the costs in prefetching particular results against the benefits in reduced latency to searchers represents the search result prefetching challenge. In this article, we introduce this challenge and present methods to address it in both desktop and mobile settings. Our methods leverage searchers’ cursor movements (on desktop) and viewport-based viewing behavior (on mobile) on search engine result pages (SERPs) in real time to dynamically estimate the result that searchers will request next. We demonstrate through large-scale log analysis that our approach significantly outperforms three strong baselines that prefetch results based on (i) the search engine result ranking (prefetch top-ranked results), (ii) past SERP clicks from all searchers for the query (prefetch popular results), or (iii) past SERP clicks from the current searcher for the query (prefetch results that the searcher prefers). Our promising findings have implications for the design of search support in desktop and mobile settings that makes the search process more efficient.