XKeyword provides efficient keyword proximity queries on large XML graph databases. A query is simply a list of keywords and does not require any schema or query language knowledge for its formulation. XKeyword is built on a relational database...

Abstract—Recent works have shown the benefits of keyword proximity search in querying XML documents in addition to text documents. For example, given query keywords over Shakespeare’s plays in XML, the user might be interested in knowing how the keywords cooccur. In this paper, we focus on XML

ding to their size. Trees of smaller sizes denote higher association between the keywords, which is generally true for reasonable schema designs. For example, consider the keyword query "Yannis, Vasilis" on the Permission to copy without fee all or part of this material is granted

Keyword search in XML documents based on the notion of lowest common ancestors (LCAs) and modifications of it has recently gained research interest [10, 14, 22]. In this pa-per we propose an efficient algorithm called Indexed Stack to find answers to keyword queries based on XRank’s se

Various approaches for keyword proximity search have been implemented in relational databases, XML and the Web. Yet, in all of them, an answer is a Q-fragment, namely, a subtree T of the given data graph G, such that T contains all the keywords of the query Q and has no proper subtree

In the text retrieval area including XML and Region Al-gebra, many researchers pursued models for specifying what kinds of information should appear in specified structural positions and linear positions (Chinenyanga

In this paper, we study the problem of keyword proximity search over XML documents and leverage the efficiency and effectiveness. We take the disjunctive semantics among input keywords into consideration and identify meaningful compact connected trees as the answers of keyword proximity queries. We

Recently, there has been extensive research that generated a wealth of new XML full-text query languages, ranging from simple Boolean search to combining sophisticated proximity and order predicates on keywords. While computing least common ancestors of query terms was proposed for efficient

... mix of structured and unstructured (text) data. Although current XML query languages such as XPath and XQuery can express rich queries over structured data, they can only express very rudimentary queries over text data. We thus propose TeXQuery, which is a powerful full-text search extension

Keyword search is a user-friendly way to query XML databases. Most previous efforts in this area focus on keyword proximity search in XML based on either tree data model or graph (or digraph) data model. Tree data model for XML is generally simple and efficient for keyword proximity search. However