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Natural language query filtration in the Conceptual Query Language

Authors: Shamkant B. Navathe; Hyeun-Suk Rhee; V. Owei;

Natural language query filtration in the Conceptual Query Language

Abstract

Natural language (NL) interfaces for database query formulation have always been recognized as a much needed enhancement for end-users. Poor performances with earlier NL systems had led to a lull in research in this field. However, latter-day experiments and systems appear to be sufficiently more promising to warrant continued and further research in this area. This paper proposes an experimental query interface that filters NL query statements for search predicates that are derived from constructs on conceptual schemas, thereby avoiding the computational difficulty with full-fledged NL parsing. A prototype of the Conceptual Query Language (CQL) exists as a front-end to an Oracle relational DBMS.

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    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Average
Average
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