BROAD: Diversified keyword search in databases

Abstract

Keyword search in databases has received a lot of attention in the database community as it is an effective approach for querying a database without knowing its underlying schema. However, keyword search queries often return too many re- sults. One standard solution is to rank results such that the "best" results appear first. Still, this approach can suffer from redundancy problem where many high ranking results are in fact coming from the same part of the database and results in other parts of the database are missed completely. In this demo, we propose the BROAD system which allows users to perform diverse, hierarchical browsing on keyword search results. Our system partitions the answer trees in the keyword search results by selecting k diverse representatives from the trees, separating the answer trees into k groups based on their similarity to the representatives and then recursively applying the partitioning for each group. By constructing summarized result for the answer trees in each of the k groups, we provide a way for users to quickly locate the results that they desire. © 2011 VLDB Endowment.