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Journal ArticleDOI

The Lorel Query Language for Semistructured Data

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TLDR
The main novelties of the Lorel language are the extensive use of coercion to relieve the user from the strict typing of OQL, which is inappropriate for semistructured data; and powerful path expressions, which permit a flexible form of declarative navigational access and are particularly suitable when the details of the structure are not known to the user.
Abstract
language, designed for querying semistructured data. Semistructured data is becoming more and more prevalent, e.g., in structured documents such as HTML and when performing simple integration of data from multiple sources. Traditional data models and query languages are inappropriate, since semistructured data often is irregular: some data is missing, similar concepts are represented using different types, heterogeneous sets are present, or object structure is not fully known. Lorel is a user-friendly language in the SQL/OQL style for querying such data effectively. For wide applicability, the simple object model underlying Lorel can be viewed as an extension of the ODMG data model and the Lorel language as an extension of OQL. The main novelties of the Lorel language are: (i) the extensive use of coercion to relieve the user from the strict typing of OQL, which is inappropriate for semistructured data; and (ii) powerful path expressions, which permit a flexible form of declarative navigational access and are particularly suitable when the details of the structure are not known to the user. Lorel also includes a declarative update language. Lorel is implemented as the query language of the Lore prototype database management system at Stanford. Information about Lore can be found at http://www-db.stanford.edu/lore. In addition to presenting the Lorel language in full, this paper briefly describes the Lore system and query processor. We also briefly discuss a second implementation of Lorel on top of a conventional object-oriented database management system, the O2 system.

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XCSL: XML constraint specification language

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Book ChapterDOI

Object Database Support for Digital Libraries

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Book

Algorithmic Learning Theory: 12th International Conference, ALT 2001, Washington, DC, USA, November 25-28, 2001. Proceedings.

TL;DR: This work focuses on the development of efficient learning of Semi-structured Data from Queries in Elementary Formal Systems and on the comparison of Inductive Inference Criteria for Uniform Learning of Finite Classes.
Book ChapterDOI

System of information retrieval in XML documents

Saliha Smadhi
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Journal ArticleDOI

INode*: an effective approach for storing XML using relational database

TL;DR: This paper presents a new model-mapping method called INode*.
References
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Journal ArticleDOI

Query evaluation techniques for large databases

TL;DR: This survey describes a wide array of practical query evaluation techniques for both relational and postrelational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set-matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.
Book

The object database standard: ODMG 2.0

TL;DR: With this book, standards are defined for object management systems and this will be the foundational book for object-oriented database product.
Proceedings ArticleDOI

Object exchange across heterogeneous information sources

TL;DR: An object-based information exchange model and a corresponding query language are defined that are well suited for integration of diverse information sources and used to integrate heterogeneous bibliographic information sources.
Book ChapterDOI

Querying Semi-Structured Data

TL;DR: The main purpose of the paper is to isolate the essential aspects of semistructured data, and survey some proposals of models and query languages for semi-structured data.
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