Fast algorithms for finding nearest common ancestors
SIAM Journal on Computing
On finding lowest common ancestors: simplification and parallelization
SIAM Journal on Computing
XRANK: ranked keyword search over XML documents
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Adaptive Processing of Top-k Queries in XML
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Efficient keyword search for smallest LCAs in XML databases
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Structure and content scoring for XML
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Bidirectional expansion for keyword search on graph databases
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Finding and approximating top-k answers in keyword proximity search
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Multiway SLCA-based keyword search in XML data
Proceedings of the 16th international conference on World Wide Web
BLINKS: ranked keyword searches on graphs
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Identifying meaningful return information for XML keyword search
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
XSEarch: a semantic search engine for XML
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Effective keyword search for valuable lcas over xml documents
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
A multi-ranker model for adaptive XML searching
The VLDB Journal — The International Journal on Very Large Data Bases
TopX: efficient and versatile top-k query processing for semistructured data
The VLDB Journal — The International Journal on Very Large Data Bases
Efficient keyword search over virtual XML views
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Efficient LCA based keyword search in XML data
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Enabling Schema-Free XQuery with meaningful query focus
The VLDB Journal — The International Journal on Very Large Data Bases
Race: finding and ranking compact connected trees for keyword proximity search over xml documents
Proceedings of the 17th international conference on World Wide Web
Lowest common ancestors in trees and directed acyclic graphs
Journal of Algorithms
Mapping semantic knowledge for unsupervised text categorisation
ADC '13 Proceedings of the Twenty-Fourth Australasian Database Conference - Volume 137
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Keyword search is a natural and user-friendly mechanism for querying XML data in information systems and Web based applications. One of the key tasks is to identify and return meaningful fragments as results, due to the limited expressiveness and the ambiguity of keyword queries. In this paper, we first studied query keyword patterns in order to exploit the user's search intention behind the input keywords. The outcome of this task is that keywords in the query are classified as required information and search conditions (or predicates). In addition, unlike previous work that our work only returns desired fragments as results. Each returned result must satisfy the search conditions rather than simply contain all query keywords. To further prune irrelevant fragments we introduce a novel notion called Relevant Lowest Common Ancestor (RLCA) which effectively and precisely captures the meaningful and relevant fragments to the given keyword query. We conducted extensive experimental studies to prove the effectiveness of our approach.