Control flow compilation is a hybrid between classical WAM compilation and meta-call, limited to the compilation of non-recursive clause bodies. This approach is used successfully for the execution of dynamically generated queries in an inductive logic programming setting (ILP). Control flow compilation reduces compilation times up to an order of magnitude, without slowing down execution. A lazy variant of control flow compilation is also presented. By compiling code by need, it removes the overhead of compiling unreached code (a frequent phenomenon in practical ILP settings), and thus reduces the size of the compiled code. Both dynamic compilation approaches have been implemented and were combined with query packs, an efficient ILP executi...
Query optimization is used frequently in relational database management systems. Most existing techn...
Because query execution is the most crucial part of Inductive Logic Programming (ILP) algorithms, a ...
65 pagesQuery compilation and adaptive query processing aim to improve the runtime and robustness of...
Learning algorithms such as decision tree learners dynamically generate a huge amount of large queri...
Compiling queries to machine code is arguably the most efficient way for executing queries. One ofte...
In Inductive Logic Programming (ILP), several techniques have been introduced to improve the efficie...
In Inductive Logic Programming (ILP), several techniques have been introduced to improve the efficie...
In Inductive Logic Programming (ILP), several techniques have been introduced to improve the ecienc...
Inductive logic programming systems usually send large numbers of queries to a database. The lattice...
Inductive logic programming systems usually send large numbers of queries to a database. The lattice...
Inductive logic programming, or relational learning, is a powerful paradigm for machine learning or ...
Although compiling queries to efficient machine code has become a common approach for query executio...
Abstract. Logic programming systems often need to deal with large but otherwise regular predicates, ...
Inductive logic programming, or relational learning, is a powerful paradigm for machine learning or ...
Database query engines use pull-based or push-based approaches to avoid the materialization of data ...
Query optimization is used frequently in relational database management systems. Most existing techn...
Because query execution is the most crucial part of Inductive Logic Programming (ILP) algorithms, a ...
65 pagesQuery compilation and adaptive query processing aim to improve the runtime and robustness of...
Learning algorithms such as decision tree learners dynamically generate a huge amount of large queri...
Compiling queries to machine code is arguably the most efficient way for executing queries. One ofte...
In Inductive Logic Programming (ILP), several techniques have been introduced to improve the efficie...
In Inductive Logic Programming (ILP), several techniques have been introduced to improve the efficie...
In Inductive Logic Programming (ILP), several techniques have been introduced to improve the ecienc...
Inductive logic programming systems usually send large numbers of queries to a database. The lattice...
Inductive logic programming systems usually send large numbers of queries to a database. The lattice...
Inductive logic programming, or relational learning, is a powerful paradigm for machine learning or ...
Although compiling queries to efficient machine code has become a common approach for query executio...
Abstract. Logic programming systems often need to deal with large but otherwise regular predicates, ...
Inductive logic programming, or relational learning, is a powerful paradigm for machine learning or ...
Database query engines use pull-based or push-based approaches to avoid the materialization of data ...
Query optimization is used frequently in relational database management systems. Most existing techn...
Because query execution is the most crucial part of Inductive Logic Programming (ILP) algorithms, a ...
65 pagesQuery compilation and adaptive query processing aim to improve the runtime and robustness of...