The widespread adoption of XML holds the promise that document structure can be exploited to specify precise database queries. However, users may have only a limited knowledge of the XML structure, and may be unable to produce a correct XQuery expression, especially in the context of a heterogeneous information collection. The default is to use keyword-based search and we are all too familiar with how difficult it is to obtain precise answers by these means. We seek to address these problems by introducing the notion of Meaningful Query Focus (MQF) for finding related nodes within an XML document. MQF enables users to take full advantage of the preciseness and efficiency of XQuery without requiring (perfect) knowledge of the document structure. Such a Schema-Free XQuery is potentially of value not just to casual users with partial knowledge of schema, but also to experts working in data integration or data evolution. In such a context, a schema-free query, once written, can be applied universally to multiple data sources that supply similar content under different schemas, and applied “forever” as these schemas evolve. Our experimental evaluation found that it is possible to express a wide variety of queries in a schema-free manner and efficiently retrieve correct results over a broad diversity of schemas. Furthermore, the evaluation of a schema-free query is not expensive: using a novel stack-based algorithm we developed for computing MQF, the overhead is from 1 to 4 times the execution time of an equivalent schema-aware query. The evaluation cost of schema-free queries can be further reduced by as much as 68% using a selectivity-based algorithm we develop to enable the integration of MQF operation into the query pipeline.
The VLDB Journal – Springer Journals
Published: May 1, 2008
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera