The View Selection Problem is an optimization problem designed to enhance query performance through the pre-computation and storage of select views given resource constraints.
Similarly, in mapping XML into relations, we can consider some redundancies to enhance query performance and they can be grasped through the structural traits of DTD (or XML schema).
Examples of MIR applications with song lyrics are Music Mood Identification [1],[2], Music Genre [3] and Mood [4] Classification, Artist Similarity [5],[6], Artist Style Identification [7], Enhancing Query By Humming Systems [8],[9], Automatic Recognition of Lyrics in Singing [10], among others [11]-[13] [11]-[13]
Optimisation strategies and best practice translation rules were followed in order to enhance query performance of the web based GUI.
These include tools for creating ontology mappings, ontology views, detecting ontology changes and using ontologies in interfaces to enhance querying.
For the other 23 queries, q5 query did not produce any results: enhancing query using UMLS synonyms did not add any further results.
BeetleBase also provides several user tools including BLAST for sequence alignments and a BLAT/GMOD-integrated search engine to enhance querying abilities.
Stream Reasoning goes one step further by enhancing continuous queries with run-time reasoning support – that is, with capabilities to infer additional, implicit knowledge based on already given, explicit facts.
The inclusion of conceptual rules enhances the querying capability of the system and allows deductive queries involving complex rules and external functions, even over-the-internet queries.
To enhance the query and matching efficiency, the symbol can be matched with those sharing the same category.
A method with prototype tool is presented to enhance semantic query to software models and other artefacts.
