Answering keyword queries on XML data has been extensively studied. Current XML keyword search solutions primarily focus on single query setting where queries are answered individually. In many applications for searching information such as jobs and publications, an application server often receives a large number of keyword queries in a short period of time and many of them may share common keywords. Therefore, answering keyword queries in batches will significantly enhance the performance of these applications. In this paper, we investigate efficient approaches for computing multiple XML keyword queries. We first propose an approach that maximizes the sharing among keyword queries. We then consider useful data information and propose two data-aware algorithms: a short eager algorithm and a log based optimal algorithm. We evaluate the proposed algorithms on real and synthetic datasets and the experimental results demonstrate their efficiencies. © 2013 Springer-Verlag.
|Title of host publication||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Number of pages||14|
|Publication status||Published - 2013|
|Event||Web Information Systems Engineering – WISE 2013: 14th International Conference - Nanjing, China|
Duration: 13 Oct 2013 → 15 Oct 2013
|Conference||Web Information Systems Engineering – WISE 2013|
|Period||13/10/13 → 15/10/13|