Sunday, October 26, 2014

 

 



Soy un nuevo usuario

Olvidé mi contraseña

Entrada usuarios

Lógica Matemáticas Astronomía y Astrofísica Física Química Ciencias de la Vida
Ciencias de la Tierra y Espacio Ciencias Agrarias Ciencias Médicas Ciencias Tecnológicas Antropología Demografía
Ciencias Económicas Geografía Historia Ciencias Jurídicas y Derecho Lingüística Pedagogía
Ciencia Política Psicología Artes y Letras Sociología Ética Filosofía
 

rss_1.0 Clasificación por Disciplina

Nomenclatura Unesco > (11) Lógica > (1104) Lógica inductiva
(1104.01) Inducción (1104.02) Intuicionismo
(1104.03) Probabilidad (1104.99) Otras (especificar)

Mostrando recursos 1 - 20 de 2,563

1. A pipelined data-parallel algorithm for ILP - fonseca, nuno a.; silva, fernando; costa, vitor santos; camacho, rui
The amount of data collected and stored in databases is growing considerably for almost all areas of human activity. Processing this amount of data is very expensive, both humanly and computationally. This justifies the increased interest both on the automatic discovery of useful knowledge from databases, and on using parallel processing for this task. Multi Relational Data Mining (MRDM) techniques, such as Inductive Logic Programming (ILP), can learn rules from relational databases consisting of multiple tables. However current ILP systems are designed to run in main memory and can have long running times. We propose a pipelined data-parallel algorithm for...

2. A pipelined data-parallel algorithm for ILP - fonseca, nuno a.; silva, fernando; costa, vitor santos; camacho, rui
The amount of data collected and stored in databases is growing considerably for almost all areas of human activity. Processing this amount of data is very expensive, both humanly and computationally. This justifies the increased interest both on the automatic discovery of useful knowledge from databases, and on using parallel processing for this task. Multi Relational Data Mining (MRDM) techniques, such as Inductive Logic Programming (ILP), can learn rules from relational databases consisting of multiple tables. However current ILP systems are designed to run in main memory and can have long running times. We propose a pipelined data-parallel algorithm for...

3. Strategies to parallelize ILP systems - Nuno A Fonseca; Fernado Silva; Rui Camacho
It is well known by Inductive Logic Programming (ILP) practionersthat ILP systems usually take a long time to nd valuable models(theories). The problem is specially critical for large datasets, preventingILP systems to scale up to larger applications. One approach to reducethe execution time has been the parallelization of ILP systems. In thispaper we overview the state-of-the-art on parallel ILP implementationsand present work on the evaluation of some major parallelization strategiesfor ILP. Conclusions about the applicability of each strategy arepresented.

4. Efficient Data Structures for Inductive Logic Programming - Nuno A Fonseca; Ricardo Rocha; Rui Camacho; Fernado Silva
This work aims at improving the scalability of memory usagein Inductive Logic Programming systems. In this context, we propose twoecient data structures: the Trie, used to represent lists and clauses;and the RL-Tree, a novel data structure used to represent the clausescoverage. We evaluate their performance in the April system using wellknown datasets. Initial results show a substantial reduction in memoryusage without incurring extra execution time overheads. Our proposal isapplicable in any ILP system.

5. From sequential to Parallel Inductive LogicProgramming - Rui Camacho
Inductive Logic Programming (ILP) has achieved considerablesuccess in a wide range of domains. It is recognized however thateciency is a major obstacle to the use of ILP systems in applicationsrequiring large amounts of data. In this paper we address the problem ofeciency in ILP in three steps: i) we survey speedup techniques proposedfor sequential execution of ILP systems; ii) we survey dierent ways ofparallelizing an ILP system and; ii) adapt and combine the sequentialexecution speedup techniques in the parallel implementations of an ILPsystem. We also propose a novel technique to partition the search spaceinto independent sub-spaces that may be adequately...

6. A commodity platform for Distributed Data Mining -- the HARVARD System - Ruy Ramos; Rui Camacho; Pedro Ferreira Do Souto
Systems performing Data Mining analysis are usually dedicated and expensive. They often require special purpose machines to run the data analysis tool. In this paper we propose an architecture for distributed Data Mining running on general purpose desktop computers. The proposed architecture was deployed in the HARVesting Architecture of idle machines foR Data mining (HARVARD) system.The Harvard system has the following features. Does not require specialpurpose or expensive machines as it runs in general purpose PCs. It isbased on distributed computing using a set of PCs connected in a network. In a Condor fashion it takes advantage of a distributed...

7. A system of logic, ratiocinative and inductive : being a connected view of the principles of evidence and the methods of scientific investigation / - Mill, John Stuart, 1806-1873.
Mode of access: Internet.

8. Logic, deductive and inductive, - Fowler, Thomas, 1832-1904.
Each part has special t.-p.

9. Logic, deductive and inductive. - Read, Carveth, 1848-
Mode of access: Internet.

10. Elementary lessons in logic; deductive and inductive. With copious questions and examples and a vocabulary of logical terms. - Jevons, William Stanley, 1835-1882.
Mode of access: Internet.

11. A system of logic, ratiocinative and inductive : being a connected view of the principles of evidence and the methods of scientific investigation / - Mill, John Stuart, 1806-1873.
Includes bibliographical references.

12. Sistema logiki / - Mill, John Stuart, 1806-1873.
Translation of: System of logic, ratiocinative and inductive.

13. Elementary lessons in logic : deductive and inductive : with copious questions and examples and a vocabulary of logical terms / - Jevons, William Stanley, 1835-1882.
Includes bibliographical references and index.

14. A system of logic, ratiocinative and inductive : being a connected view of the principles of evidence, and the methods of scientific investigation. - Mill, John Stuart, 1806-1873.
Includes bibliographical references.

15. A system of logic, ratiocinative and inductive : being a connected view of the principles of evidence and the methods of scientific investigation / - Mill, John Stuart, 1806-1873.
Mode of access: Internet.

16. A system of logic, ratiocinative and inductive : being a connected view of the principles of evidence and the methods of scientific investigation. - Mill, John Stuart, 1806-1873.
Mode of access: Internet.

17. A system of logic, ratiocinative and inductive : being a connected view of the principles of evidence and the methods of scientific investigation / - Mill, John Stuart, 1806-1873.
Mode of access: Internet.

18. Elementary lessons in logic; deductive and inductive. With copious questions and examples and a vocabulary of logical terms. - Jevons, William Stanley, 1835-1882.
Mode of access: Internet.

19. Elementary lessons in logic; deductive and inductive. With copious questions and examples and a vocabulary of logical terms. - Jevons, William Stanley, 1835-1882.
Mode of access: Internet.

20. Elementary lessons in logic : deductive and inductive : with copious questions and examples, and a vocabulary of logical terms / - Jevons, William Stanley, 1835-1882.
On spine: Lessons in logic.

Página de resultados:
 

Busque un recurso