Widen the peepholes! Entity-based auto-suggestion as a rich and yet immediate starting point for exploratory search

Abstract

Today's search engines provide instant keyword-based auto-suggestion and completion of the user's search queries. This paper presents a novel auto-suggestion interface for the Semantic Multimedia Explorer (SEMEX), a semantic search engine that supports entity-based exploratory video retrieval. In difference to traditional textbased retrieval, auto-suggestion and auto-completion of the user's query string is not based on plain text but on semantic entities grouped by meaningful categories. Suggested entities are ranked by plain edit-distance as well as by popularity while their representations are enabled for brushing and linking. The categories contribute to a quick comprehensibility of the suggested entities compared to other systems that constrain an actually significant and practical feature into static and narrow vertical listings. Thus, our approach is leading to better decision making from the very start of an exploratory search.