Finding hot query patterns over an XQuery stream

2004 ◽  
Vol 13 (4) ◽  
pp. 318-332 ◽  
Author(s):  
Liang Huai Yang ◽  
Mong Li Lee ◽  
Wynne Hsu
Keyword(s):  
Query Patterns

Migrating a complex classification scheme to the semantic web: expressing the Integrative Levels Classification using SKOS RDF

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ceri Binding ◽  
Claudio Gnoli ◽  
Douglas Tudhope
Keyword(s):  
Knowledge Organization ◽  
Content Type ◽  
Classification Schemes ◽  
Facet Structure ◽  
Simple Knowledge Organization System ◽  
Trade Offs ◽  
Knowledge Organization System ◽  
Faceted Classification ◽  
Integrative Levels ◽  
Query Patterns

PurposeThe Integrative Levels Classification (ILC) is a comprehensive “freely faceted” knowledge organization system not previously expressed as SKOS (Simple Knowledge Organization System). This paper reports and reflects on work converting the ILC to SKOS representation.Design/methodology/approachThe design of the ILC representation and the various steps in the conversion to SKOS are described and located within the context of previous work considering the representation of complex classification schemes in SKOS. Various issues and trade-offs emerging from the conversion are discussed. The conversion implementation employed the STELETO transformation tool.FindingsThe ILC conversion captures some of the ILC facet structure by a limited extension beyond the SKOS standard. SPARQL examples illustrate how this extension could be used to create faceted, compound descriptors when indexing or cataloguing. Basic query patterns are provided that might underpin search systems. Possible routes for reducing complexity are discussed.Originality/valueComplex classification schemes, such as the ILC, have features which are not straight forward to represent in SKOS and which extend beyond the functionality of the SKOS standard. The ILC's facet indicators are modelled as rdf:Property sub-hierarchies that accompany the SKOS RDF statements. The ILC's top-level fundamental facet relationships are modelled by extensions of the associative relationship – specialised sub-properties of skos:related. An approach for representing faceted compound descriptions in ILC and other faceted classification schemes is proposed.

Modeling and Language Support for the Pattern Management

2017 ◽  
pp. 86-106 ◽  
Author(s):  
Zdenka Telnarova
Keyword(s):  
Query Language ◽  
General Pattern ◽  
Specific Pattern ◽  
Data Type ◽  
Abstract Data Type ◽  
Crucial Issue ◽  
Simple Scheme ◽  
Language Support ◽  
Abstract Data ◽  
Query Patterns

Patterns are mentioned usually in the extraction context. Little stress is posed in their representation and management. This chapter is focused on the representation of the patterns, manipulation with patterns and query patterns. Crucial issue can be seen in systematic approach to pattern management and specific pattern query language which takes into consideration semantics of patterns. In the background we discuss two different approaches to the pattern store and manipulation (based on inductive database and PANDA project). General pattern model is illustrated using abstract data type implemented in Oracle. In the following chapters the introduction to querying patterns and simple scheme of the architecture PBMS is shown.

Incremental Mining of Frequent Query Patterns from XML Queries for Caching

2006 ◽  
Author(s):  
Guoliang Li ◽  
Jianhua Feng ◽  
Jianyong Wang ◽  
Yong Zhang ◽  
Lizhu Zhou
Keyword(s):  
Incremental Mining ◽  
Query Patterns

Heuristics for selecting robust database structures with dynamic query patterns

2006 ◽  
Vol 168 (1) ◽  
pp. 200-220 ◽  
Author(s):  
Andrew N.K. Chen ◽  
Paulo B. Goes ◽  
Alok Gupta ◽  
James R. Marsden
Keyword(s):  
Query Patterns ◽  
Dynamic Query

Database design in the modern organization—identifying robust structures under changing query patterns and arrival rate conditions

2004 ◽  
Vol 37 (3) ◽  
pp. 435-447 ◽  
Author(s):  
Andrew N.K. Chen ◽  
Paulo B. Goes ◽  
Alok Gupta ◽  
James R. Marsden
Keyword(s):  
Arrival Rate ◽  
Database Design ◽  
Query Patterns
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