Designing Functional Dependencies for XML

Lee, Mong Li; Ling, Tok Wang; Low, Wai Lup

doi:10.1007/3-540-45876-x_10

Cited by 79 publications

(29 citation statements)

References 10 publications

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“…The set of maximal tree tuples is denoted by tuples D (T ). Now we say that We conclude this section by pointing out that other proposals for XFDs exist in the literature [16,20,28]. In particular, the language introduced in [28] is similar to the one presented in this paper.…”

Section: Functional Dependencies For Xmlmentioning

confidence: 58%

Normalization theory for XML

Arenas

2006

SIGMOD Rec.

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Section: Functional Dependencies For Xmlmentioning

confidence: 58%

Normalization theory for XML

Arenas

2006

SIGMOD Rec.

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“…, R k , we use their Cartesian product R 1 × · · · × R k . For example, if we have R 1 = //employee list and R 2 = //employee/name, their instances for the XML data in Figure 6 are R 1 = {(2)} and R 2 = {(4, 6), (7,9), (11,13)}. Consequently, the instance of their Cartesian product R 1 × R 2 is: (2,7,9), (2, 11, 13)}.…”

Section: D 33 [An Instance Of a Relationmentioning

confidence: 99%

“…FDs and keys have been well studied to find ways of reducing data redundancy and avoiding update anomalies [17]. In recent years, these concepts have been applied to XML in the form of XML keys [7] and XML FDs [3,13,24,28]. These approaches are based on paths; given sets X and Y of paths, an FD for XML is defined as X → Y.…”

Section: Related Workmentioning

confidence: 99%

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Relational-style XML query

Saito

Morishita

2008

Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data

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We study the problem of querying relational data embedded in XML. Relational data can be represented by various tree structures in XML. However, current XML query methods, such as XPath and XQuery, demand explicit path expressions, and thus it is quite difficult for users to produce correct XML queries in the presence of structural variations.To solve this problem, we introduce a novel query method that automatically discovers various XML structures derived from relational data. A challenge in implementing our method is to reduce the cost of enumerating all possible tree structures that match the query. We show that the notion of functional dependencies has an important role in generating efficient query schedules that avoid irrelevant tree structures.Our proposed method, the relational-style XML query, has several advantages over traditional XML data management. These include removing the burden of designing strict tree-pattern schemas, enhancing the descriptions of relational data with XML's rich semantics, and taking advantage of schema evolution capability of XML. In addition, the independence of query statements from the underlying XML structure is advantageous for integrating XML data from several sources. We present extensive experimental results that confirm the scalability and tolerance of our query method for various sizes of XML data containing structural variations.

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“…The concept of "virtual attribute dependencies" resembles that of "functional dependencies" (FDs) in relational databases [23]. In the context of PERF, we define "virtual attribute dependencies" as rules for determining additional attribute values from an external biological database, given attribute values provided with the original mention.…”

Section: Virtual Attribute Dependencies (Vads)mentioning

confidence: 99%

An Entity Resolution Framework for Deduplicating Proteins

Lochovsky

Topaloglou

Lecture Notes in Computer Science

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Abstract. An important prerequisite to successfully integrating protein data is detecting duplicate records spread across different databases. In this paper, we describe a new framework for protein entity resolution, called PERF, which deduplicates protein mentions using a wide range of protein attributes. A mention refers to any recorded information about a protein, whether it is derived from a database, a high-throughput study, or literature text mining, among others. PERF can be easily extended to deduplicate protein-protein interactions (PPIs) as well. This framework translates mentions into instances of a reference schema to facilitate mention comparisons. PERF also uses "virtual attribute dependencies" to "enhance" mentions with additional attribute values. PERF computes a likelihood measure based upon the textual value similarity of mention attributes. A prototype implementation of the framework was tested, and these tests indicate that PERF can clearly separate duplicate mentions from non-duplicate mentions.

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Designing Functional Dependencies for XML

Cited by 79 publications

References 10 publications

Normalization theory for XML

Normalization theory for XML

Relational-style XML query

An Entity Resolution Framework for Deduplicating Proteins

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