检索结果-内蒙古大学图书馆

The impact of enriched linguistic annotation on the performance of extracting relation triples

5th International Conference on Intelligent Text Processing and Computational Linguistics

作者： Kim, SH Lewis, P Martinez, K Univ Southampton Dept Elect & Comp Sci MultiMedia Grp Southampton SO9 5NH Hants England

ISBN: (纸本)3540210067

A relation extraction system recognises pre-defined relation types between two identified entities from natural language documents. it is important for a task of automatically locating missing instances in knowledge base where the instance is represented as a triple ('entity - relation - entity'). A relation entry specifies a set of rules associated with the syntactic and semantic conditions under which appropriate relations would be extracted. Manually creating such rules requires knowledge from information experts and moreover, it is a time-consuming and error-prone task when the input sentences have little consistency in terms of structures and vocabularies. In this paper, we present an approach for applying a symbolic learning algorithm to sentences in order to automatically induce the extraction rules which then successfully classify a new sentence. The proposed approach takes into account semantic attributes (e.g., semantically close words and named-entities) in generalising common patterns among the sentences which enable the system to cope better with syntactically different but semantically similar sentences. Not only does this increase the number of relations extracted, but it also improves the accuracy in extracting relations by adding features which might not be discovered only with syntactic analysis. Experimental results show that this approach is effective on the sentences of the Web documents obtaining 17% higher precision and 34% higher recall values.

关键词： relation extraction information extraction inductive logic programming

来源：评论

学校读者我要写书评

暂无评论

Query transformations for improving the efficiency of ILP systems

Query transformations for improving the efficiency of ILP sy...

引用

10th International Conference on inductive logic programming (ILP2000)

作者： Costa, VS Srinivasan, A Camacho, R Blockeel, H Demoen, B Janssens, G Struyf, J Vandecasteele, H Van Laer, W UFRJ COPPE Sistemas Rio De Janeiro Brazil Univ Porto LIACC Oporto Portugal Univ Oxford Comp Lab Oxford England Univ Porto FEUP Oporto Portugal Katholieke Univ Leuven Dept Comp Sci B-3001 Louvain Belgium PharmaDM B-3001 Heverlee Belgium Katholieke Univ Leuven Dept Comp Sci B-3001 Louvain Belgium

Relatively simple transformations can speed up the execution of queries for data mining considerably. While some ILP systems use such transformations, relatively little is known about them or how they relate to each other. This paper describes a number of such transformations. Not all of them are novel, but there have been no studies comparing their efficacy. The main contributions of the paper are: (a) it clarifies the relationship between the transformations;(b) it contains an empirical study of what can be gained by applying the transformations;and (c) it provides some guidance on the kinds of problems that are likely to benefit from the transformations.

关键词： inductive logic programming program analysis

来源：评论

学校读者我要写书评

暂无评论

IndLog - Induction in logic 1

引用

9th European Conference on logics in Artificial Intelligence (JELIA 04)

作者： Camacho, R LIACC P-4150 Oporto Portugal FEUP P-4200465 Oporto Portugal

ISBN: (数字)9783540302278

ISBN: (纸本)3540232427

IndLog is a general purpose Prolog-based inductive logic programming (ILP) system. It is theoretically based on the Mode Directed Inverse Entailment and has several distinguishing features that makes it adequate for a wide range of applications. To search efficiently through large hypothesis spaces, IndLog uses original features like lazy evaluation of examples and Language Level Search. IndLog is applicable in numerical domains using the lazy evaluation of literals technique and Model Validation and Model Selection statistical-based techniques. IndLog has a MPI/LAM interface that enables its use in parallel or distributed environments, essential for Multi-relational Data Mining applications. Parallelism may be used in three flavours: splitting of the data among the computation nodes;parallelising the search through the hypothesis space and;using the different computation nodes to do theory-level search. IndLog has been applied successfully to major ILP literature datasets from the Life Sciences, Engineering, Reverse Engineering, Economics, Time-Series modelling to name a few.

关键词： inductive logic programming

来源：评论

学校读者我要写书评

暂无评论

Reducing register pressure through LAER algorithm 04

Reducing register pressure through LAER algorithm

引用

Australasian Computer Science Conference

作者： Gao Song Chinese Academy of Sciences Beijing P.R. China

When modern processors keep increasing the instruction window size and the issue width to exploit more instruction-level parallelism (ILP), the demand of larger physical register file is also on the increase. As a result, register file access time represents one of the critical delays and can easily become a bottleneck. In this paper, we first discuss the possibilities of reducing register pressure by shortening the lifetime of physical registers, and evaluate several possible register renaming approaches. We then propose an efficient dynamic register renaming algorithm named LAER (Late Allocation and Early Release), which can be implemented through a two-level register file organization. In LAER renaming scheme, physical register allocations are delayed until the instructions are ready to be executed, and the physical registers in the first level are released once they become non-active, with the values backupped in the second level. We show that LAER algorithm can significantly reduce the register pressure with minimal cost of space and logic complexity, which means the same amount of ILP exploited with smaller physical register file, thus shorter register file access time and higher clock speed, or the same size of physical register file to achieve much higher performance.

关键词： superscalar processors register file Registers superscalar processor Storage access times inductive logic programming Register renaming physical clock frequency File systems

来源：评论

学校读者我要写书评

暂无评论

inductive logic programming: From logic of discovery to machine learning

引用

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2000年第1期E83D卷 10-18页

作者： Arimura, H Yamamoto, A Japan Sci & Technol Corp Tokyo Japan Hokkaido Univ Fac Technol Sapporo Hokkaido 0600812 Japan Hokkaido Univ Meme Media Lab Sapporo Hokkaido 0600812 Japan

inductive logic programming (ILP) is a study of machine learning systems that use clausal theories in first-order logic as a representation language. In this paper, we survey theoretical foundations of ILP from the viewpoints of logic of Discovery and Machine Learning, and try to unify these two views with the support of the modern theory of logic programming. Firstly, we define several hypothesis construction methods in ILP and give their proof-theoretic foundations by treating then as a procedure which complete incomplete proofs. Next, we discuss the design of individual learning algorithms using these hypothesis construction methods. We review known results on learning logic programs in computational learning theory, and show that these algorithms are instances of a generic learning strategy with proof completion methods.

关键词： logic of discovery inductive logic programming Machine Learning

来源：评论

学校读者我要写书评

暂无评论

Predicate ranking algorithms and their application in an inductive logic programming system

Predicate ranking algorithms and their application in an ind...

引用

51st National Aerospace and Electronics Conference (NAECON 2000)

作者： Yeleswarapu, M Seitzer, J Univ Dayton Dayton OH 45469 USA

ISBN: (纸本)0780362624

inductive logic programming (ILP) is a form of machine learning that induces rules from data using the language and syntax of logic programming. A rule construction algorithm forms rules that summarize data sets. These rules can be used in a large spectrum of data mining activities. In ILP, the rules are constructed with a target predicate as the consequent, or head, of the rule, and with high-ranking literals forming the antecedent, or body, of the rule. The predicate rankings are obtained by applying predicate ranking algorithms to a domain (background) knowledge base. In this work, we present three new predicate ranking algorithms for the inductive logic programming system, INDED (pronounced "indeed"). The algorithms use a grouping technique employing basic set theoretic operations to generate the rankings. We also present results of applying the ranking algorithms to several problem domains, some of which are universal like the classical genealogy problem, and others, not so common. In particular, diagnosis is the main thread of many of our experiments. Here, although our experimentation relates to medical diagnosis in diabetes and Lyme disease, many of the same techniques and methodologies can be applied to other forms of diagnosis including system failure, sensor detection, and trouble-shooting.

关键词： diagnosis inductive logic programming predicate ranking

来源：评论

学校读者我要写书评

暂无评论

Hypothesis finding based on upward refinement of residue hypotheses

引用

THEORETICAL COMPUTER SCIENCE 2003年第1期298卷 5-19页

作者： Yamamoto, A Hokkaido Univ Fac Technol & Meme Media Lab Kita Ku Sapporo Hokkaido 0608628 Japan

For given logical formulae B and E such that B K E, hypothesis finding means the generation of a formula H such that Bboolean ANDH satisfies E. Hypothesis finding constitutes a basic technique for fields of inference, like inductive inference and knowledge discovery. In order to put various hypothesis finding methods proposed previously on one general ground, we use upward refinement and residue hypotheses. We show that their combination is a complete method for solving any hypothesis finding problem in clausal logic. We extend the relative subsumption relation, and show that some hypothesis finding methods previously presented can be regarded as finding hypotheses which subsume examples relative to a given background theory. Noting that the weakening rule may make hypothesis finding difficult to solve, we propose restricting this rule either to the inverse of resolution or to that of subsumption. We also note that this work is related to relevant logic. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： abductive inference inductive inference inductive logic programming clausal logic hypothesis finding

来源：评论

学校读者我要写书评

暂无评论

inductive logic programming for corpus-based acquisition of semantic lexicons 00

Inductive logic programming for corpus-based acquisition of ...

引用

Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7

作者： Pascale Sébillot Pierrette Bouillon Cécile Fabre IRISA - Campus de Beaulieu - Rennes cedex - France TIM/ISSCO - ETI - Université de Genève Geneva - Switzerland ERSS - Université de Toulouse II Toulouse cedex - France

In this paper, we propose an inductive logic programming learning method which aims at automatically extracting special Noun-Verb (N-V) pairs from a corpus in order to build up semantic lexicons based on Pustejovsky's Generative Lexicon (GL) principles (Pustejovsky, 1995). In one of the components of this lexical model, called the qualia structure, words are described in terms of semantic roles. For example, the telic role indicates the purpose or function of an item (cut for knife), the agentive role its creation mode (build for house), etc. The qualia structure of a noun is mainly made up of verbal associations, encoding relational information. The inductive logic programming learning method that we have developed enables us to automatically extract from a corpus N-V pairs whose elements are linked by one of the semantic relations defined in the qualia structure in GL, and to distinguish them, in terms of surrounding categorial context from N-V pairs also present in sentences of the corpus but not relevant. This method has been theoretically and empirically validated, on a technical corpus. The N-V pairs that have been extracted will further be used in information retrieval applications for index expansion.

关键词： generative lexicon inductive logic programming information indexing lexicon learning

来源：评论

学校读者我要写书评

暂无评论

The automatic discovery of structural principles describing protein fold space

引用

JOURNAL OF MOLECULAR BIOLOGY 2003年第4期330卷 839-850页

作者： Cootes, AP Muggleton, SH Sternberg, MJE Univ London Imperial Coll Sci Technol & Med Dept Comp London SW7 2AZ England Canc Res UK Biomol Modelling Lab London WC2A 3PX England Univ London Imperial Coll Sci Technol & Med Dept Biol Sci London SW7 2AZ England Univ York Dept Comp Sci York YO1 5DD N Yorkshire England

The study of protein structure has been driven largely by the careful inspection of experimental data by human experts. However, the rapid determination of protein structures from structural-genomics projects will make it increasingly difficult to analyse (and determine the principles responsible for) the distribution of proteins in fold space by inspection alone. Here, we demonstrate a machine-learning strategy that automatically determines the structural principles describing 45 folds. The rules learnt were shown to be both statistically significant and meaningful to protein experts. With the increasing emphasis on high-throughput experimental initiatives, machine-learning and other automated methods of analysis will become increasingly important for many biological problems. (C) 2003 Elsevier Ltd. All rights reserved.

关键词： protein structure machine learning inductive logic programming fold space

来源：评论

学校读者我要写书评

暂无评论

Enriching relational learning with fuzzy predicates

引用

7th European Conference on Principles and Practice of Knowledge Discovery in Databases

作者： Prade, H Richard, G Serrurier, M Univ Toulouse 3 IRIT F-31062 Toulouse France

ISBN: (纸本)3540200851

The interest of introducing fuzzy predicates when learning rules is twofold. When dealing with numerical data, it enables us to avoid arbitrary discretization. Moreover, it enlarges the expressive power of what is learned by considering different types of fuzzy rules, which may describe gradual behaviors of related attributes or uncertainty pervading conclusions. This paper describes different types of first-order fuzzy rules and a method for learning each type. Finally, we discuss the interest of each type of rules on a benchmark example.

关键词： inductive logic programming relational learning fuzzy rule confidence degree

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：