In addition, it provides a proposal for specifying FSM schema and introduce a query language adapted to FSM-based databases.
In this paper we introduce a query processing mechanism called an eddy, which continuously reorders operators in a query plan as it runs.
To this end, we present a language for the definition of mappings between the multidimensional schemata of peers and we introduce a query reformulation framework that relies on the translation of mappings, queries, and multidimensional schemata onto the relational level.
In this paper, we introduce a query construction service suitable for large-scale web search engines that is based on Linked Open Data – LOD [9].
In this paper, we introduce a query construction service that resides on top of large-scale web search engines and aims at assisting information seekers formulate queries that are expressive of their search intentions.
In this paper, we focus on the occasions when large-scale web search engines find it difficult to cope with specific information-seeking behaviors and we accordingly introduce a query construction service that is targeted towards the solution of this problem.
Qian et al. [22] introduced a pairwise query algorithm for gene expression data based on a Smith-Waterman type local alignment algorithm [23].
Dhollander et al. [24] introduced a model-based query-driven module discovery tool QDB, but it is aimed at performing informed bi-clustering instead of pattern matching, and it does not take into account the complex correlation patterns such as inverse patterns.
In this section, we introduce a declarative query language called logic, designed specifically for this text.
In this paper we introduce a novel query capacity constraint MaxBRNN, which can solve the facility location selection problem efficiently.
In this paper we introduce a formal query model comprising four atomic operations over object-structured datasets: keyword search, object focus, path traversal, and facet specification.
