kLogNLP: Graph Kernel-based Relational Learning of Natural Language

被引：0

作者：

Verbeke, Mathias ^{[1
]}

Frasconi, Paolo ^{[2
]}

De Grave, Kurt ^{[1
]}

Costa, Fabrizio ^{[3
]}

De Raedt, Luc ^{[1
]}

机构：

[1] Katholieke Univ Leuven, Dept Comp Sci, Leuven, Belgium

[2] Univ Firenze, Dipartimento Sistemi & Informat, Florence, Italy

[3] Albert Ludwigs Univ, Inst Informat, Freiburg, Germany

来源：

PROCEEDINGS OF 52ND ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: SYSTEM DEMONSTRATIONS | 2014年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

kLog is a framework for kernel-based learning that has already proven successful in solving a number of relational tasks in natural language processing. In this paper, we present kLogNLP, a natural language processing module for kLog. This module enriches kLog with NLP-specific preprocessors, enabling the use of existing libraries and toolkits within an elegant and powerful declarative machine learning framework. The resulting relational model of the domain can be extended by specifying additional relational features in a declarative way using a logic programming language. This declarative approach offers a flexible way of experimentation and a way to insert domain knowledge.

引用

页码：85 / 90

页数：6

共 50 条

[31] SEMI-PARAMETRIC GRAPH KERNEL-BASED RECONSTRUCTION
Ioannidis, Vassilis N.
Nikolakopoulos, Athanasios N.
Giannakis, Georgios B.
[J]. 2017 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP 2017), 2017, : 588 - 592
[32] An Arabic natural language interface for querying relational databases based on natural language processing and graph theory methods
Bais H.
Machkour M.
Koutti L.
[J]. Bais, Hanane (baishanan@gmail.com), 2018, Inderscience Enterprises Ltd., 29, route de Pre-Bois, Case Postale 856, CH-1215 Geneva 15, CH-1215, Switzerland (10) : 155 - 165
[33] Learning rates for kernel-based expectile regression
Farooq, Muhammad
Steinwart, Ingo
[J]. MACHINE LEARNING, 2019, 108 (02) : 203 - 227
[34] Preimage Problem in Kernel-Based Machine Learning
Honeine, Paul
Richard, Cedric
[J]. IEEE SIGNAL PROCESSING MAGAZINE, 2011, 28 (02) : 77 - 88
[35] Kernel-based learning methods for preference aggregation
Waegeman, Willem
De Baets, Bernard
Boullart, Luc
[J]. 4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH, 2009, 7 (02): : 169 - 189
[36] Learning Rates of Kernel-Based Robust Classification
Wang, Shuhua
Sheng, Baohuai
[J]. ACTA MATHEMATICA SCIENTIA, 2022, 42 (03) : 1173 - 1190
[37] Biomedical literature mining: graph kernel-based learning for gene-gene interaction extraction
Hsieh, Ai-Ru
Tsai, Chen-Yu
[J]. EUROPEAN JOURNAL OF MEDICAL RESEARCH, 2024, 29 (01)
[38] Multitask Kernel-based Learning with Logic Constraints
Diligenti, Michelangelo
Gori, Marco
Maggini, Marco
Rigutini, Leonardo
[J]. ECAI 2010 - 19TH EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2010, 215 : 433 - 438
[39] Learning Rates of Kernel-Based Robust Classification
Shuhua Wang
Baohuai Sheng
[J]. Acta Mathematica Scientia, 2022, 42 : 1173 - 1190
[40] Learning rates for kernel-based expectile regression
Muhammad Farooq
Ingo Steinwart
[J]. Machine Learning, 2019, 108 : 203 - 227

← 1 2 3 4 5 →