XRANK: ranked keyword search over XML documents
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Efficient keyword search for smallest LCAs in XML databases
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Retrieving meaningful relaxed tightest fragments for XML keyword search
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Hash-Search: An Efficient SLCA-Based Keyword Search Algorithm on XML Documents
DASFAA '09 Proceedings of the 14th International Conference on Database Systems for Advanced Applications
Editorial: BioDB: An ontology-enhanced information system for heterogeneous biological information
Data & Knowledge Engineering
Distributed SLCA-based XML keyword search by map-reduce
DASFAA'10 Proceedings of the 15th international conference on Database systems for advanced applications
| Hi-index | 0.00 |
Keyword search in XML documents based on the notion of lowest common ancestors (LCAs) and modifications of it has recently gained research interest [2, 3, 4]. In this paper we propose an efficient algorithm called Indexed Stack to find answers to keyword queries based on XRank's semantics to LCA [2]. The complexity of the Indexed Stack algorithm is O(kd|S1|\log|S|) where k is the number of keywords in the query, d is the depth of the tree and |S1 | (|S|) is the occurrence of the least (most) frequent keyword in the query. In comparison, the best worst case complexity of the core algorithms in [2] is O(kd|S|). We analytically and experimentally evaluate the Indexed Stack algorithm and the two core algorithms in [2]. The results show that the Indexed Stack algorithm outperforms in terms of both CPU and I/O costs other algorithms by orders of magnitude when the query contains at least one low frequency keyword along with high frequency keywords.