检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

48 篇 会议
1 册 图书
1 篇 期刊文献

馆藏范围

50 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

43 篇 工学
- 43 篇 计算机科学与技术...
- 17 篇 软件工程
- 5 篇 控制科学与工程
- 2 篇 电气工程
- 1 篇 机械工程
- 1 篇 信息与通信工程
- 1 篇 交通运输工程
- 1 篇 生物医学工程（可授...
7 篇 理学
- 5 篇 数学
- 2 篇 系统科学
- 2 篇 统计学（可授理学、...
4 篇 管理学
- 3 篇 管理科学与工程(可...
- 1 篇 工商管理
- 1 篇 图书情报与档案管...
1 篇 经济学
- 1 篇 应用经济学
1 篇 教育学
- 1 篇 教育学

主题

13 篇 logic programmin...
7 篇 inductive logic ...
6 篇 inductive logic ...
3 篇 learning systems
2 篇 efficiency
2 篇 learning algorit...
2 篇 data reduction
2 篇 ilp
2 篇 robustness
1 篇 fuzzy sets
1 篇 fuzzy logic
1 篇 fake news
1 篇 performance
1 篇 computer circuit...
1 篇 corpus-based acq...
1 篇 meta-reasoning
1 篇 cancer
1 篇 subsumption unde...
1 篇 protein-carbohyd...
1 篇 bottlenose dolph...

机构

2 篇 univ wisconsin d...
2 篇 department of co...
2 篇 univ wisconsin d...
1 篇 katholieke univ ...
1 篇 univ porto fac e...
1 篇 eurise universit...
1 篇 mahsa univ sauja...
1 篇 imu univ saveeth...
1 篇 wright state uni...
1 篇 northeastern uni...
1 篇 ntt commun sci l...
1 篇 inra ur1077 mig ...
1 篇 univ oxford comp...
1 篇 univ bari dipart...
1 篇 inria rennes cam...
1 篇 univ ferrara dip...
1 篇 liacc p-4150 opo...
1 篇 univ manchester ...
1 篇 katholieke univ ...
1 篇 univ wisconsin d...

作者

3 篇 camacho rui
3 篇 rocha ricardo
2 篇 basile teresa m....
2 篇 srinivasan a
2 篇 costa vitor sant...
2 篇 fonseca nuno a.
2 篇 ferilli stefano
2 篇 shavlik j
2 篇 davis jesse
2 篇 camacho r
2 篇 page david
2 篇 srinivasan ashwi...
2 篇 esposito florian...
1 篇 spallek rainer g...
1 篇 inoue k
1 篇 riguzzi f
1 篇 theofrastos mant...
1 篇 nicolini c.
1 篇 janssens g
1 篇 sasaki y

语言

50 篇 英文

检索条件"任意字段=14th International Conference ILP 2004: Inductive Logic Programming"

共 50 条记录，以下是1-10 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

inductive logic programming Based Bottlenose Delphin Optimization to Fake New Detection 14

Inductive Logic Programming Based Bottlenose Delphin Optimiz...

引用

14th Symposium on Computer Applications & Industrial Electronics (ISCAIE)

作者： thangarasu, Gunasekar Alla, Kesava Rao Kannan, K. Nattar IMU Univ Saveetha Inst Med & Tech Sci Saveetha Sch Engn Dept Digital Hlth & Hlth Informat Kuala Lumpur Malaysia MAHSA Univ Saujana Putra Selangor Malaysia Saveetha Inst Med & Tech Sci Saveetha Sch Engn Chennai Tamil Nadu India

ISBN: (纸本)9798350348798;9798350348804

the integration of inductive logic programming (ilp) and Bottlenose Dolphin Optimization (BDO) in this research addresses a pressing issue in today's information-saturated landscape: the proliferation of fake news. In an era where misleading information can spread rapidly, traditional methods often fall short in effectively identifying deceptive *** combat this challenge, our approach harnesses the synergies of ilp and BDO. ilp plays a crucial role in constructing logical rules that capture intricate relationships within news data. By doing so, it delves deep into the content, seeking out patterns and inconsistencies that may not be obvious at first glance. BDO, on the other hand, takes inspiration from the social behavior of bottlenose dolphins to optimize the process of generating these rules. Just as dolphins collaborate and communicate to solve complex problems, BDO helps refine the logical rules for better accuracy. Ultimately, this research underscores the potential of bio-inspired optimization, such as BDO, combined with the precision of logic programming (ilp) to strengthen the integrity of information dissemination platforms. In an age where the veracity of information is paramount, this innovative approach offers a promising solution to combat the spread of fake news and promote the dissemination of authentic, reliable information.

关键词： inductive logic programming Bottlenose Dolphin Optimization Fake News Detection Information Proliferation

来源：评论

学校读者我要写书评

暂无评论

inductive logic programming based Bottlenose Delphin Optimization to Fake new Detection

Inductive Logic Programming based Bottlenose Delphin Optimiz...

引用

international conference on Computer Applications and Industrial Electronics (ICCAIE)

作者： Gunasekar thangarasu Rao Alla Kesava K Nattar Kannan Department of Digital Health and Health Informatics Saveetha School of Engineering IMU Univeristy Saveetha Institute of Medical and Technical Sciences Chennai Malaysia MAHSA Univeristy Saujana Putra Selangor Malaysia Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

ISBN: (数字)9798350348798

ISBN: (纸本)9798350348804

the integration of inductive logic programming (ilp) and Bottlenose Dolphin Optimization (BDO) in this research addresses a pressing issue in today's information-saturated landscape: the proliferation of fake news. In an era where misleading information can spread rapidly, traditional methods often fall short in effectively identifying deceptive content. To combat this challenge, our approach harnesses the synergies of ilp and BDO. ilp plays a crucial role in constructing logical rules that capture intricate relationships within news data. By doing so, it delves deep into the content, seeking out patterns and inconsistencies that may not be obvious at first glance. BDO, on the other hand, takes inspiration from the social behavior of bottlenose dolphins to optimize the process of generating these rules. Just as dolphins collaborate and communicate to solve complex problems, BDO helps refine the logical rules for better accuracy. Ultimately, this research underscores the potential of bio-inspired optimization, such as BDO, combined with the precision of logic programming (ilp) to strengthen the integrity of information dissemination platforms. In an age where the veracity of information is paramount, this innovative approach offers a promising solution to combat the spread of fake news and promote the dissemination of authentic, reliable information.

关键词： Sentiment analysis Accuracy logic programming Pressing Robustness logic Fake news

来源：评论

学校读者我要写书评

暂无评论

inductive logic programming: 24th international conference, ilp 2014, Nancy, France, September 14-16, 2014, Revised Selected Papers

引用

2016年

作者： Jesse Davis Jan Ramon

ISBN: (纸本)9783319237077

this book constitutes the thoroughly refereed post-conference proceedings of the 24th international conference on inductive logic programming, ilp 2014, held in Nancy, France, in September 2014. the 14 revised papers presented were carefully reviewed and selected from 41 submissions. the papers focus on topics such as the inducing of logic programs, learning from data represented with logic, multi-relational machine learning, learning from graphs, and applications of these techniques to important problems in fields like bioinformatics, medicine, and text mining.

关键词：

来源：评论

学校读者我要写书评

暂无评论

LazyBum: Decision Tree Learning Using Lazy Propositionalization 1

引用

29th international conference on inductive logic programming

作者： Schouterden, Jonas Davis, Jesse Blockeel, Hendrik Katholieke Univ Leuven Dept Comp Sci Celestijnenlaan 200ABox 2402 B-3001 Leuven Belgium

ISBN: (数字)9783030492106

ISBN: (纸本)9783030492090;9783030492106

Propositionalization is the process of summarizing relational data into a tabular (attribute-value) format. the resulting table can next be used by any propositional learner. this approach makes it possible to apply a wide variety of learning methods to relational data. However, the transformation from relational to propositional format is generally not lossless: different relational structures may be mapped onto the same feature vector. At the same time, features may be introduced that are not needed for the learning task at hand. In general, it is hard to define a feature space that contains all and only those features that are needed for the learning task. this paper presents LazyBum, a system that can be considered a lazy version of the recently proposed OneBM method for propositionalization. LazyBum interleaves OneBM's feature construction method with a decision tree learner. this learner both uses and guides the propositionalization process. It indicates when and where to look for new features. this approach is similar to what has elsewhere been called dynamic propositionalization. In an experimental comparison with the original OneBM and with two other recently proposed propositionalization methods (nFOIL and MODL, which respectively perform dynamic and static propositionalization), LazyBum achieves a comparable accuracy with a lower execution time on most of the datasets.

关键词： LazyBum inductive logic programming Propositionalization

来源：评论

学校读者我要写书评

暂无评论

inductive logic programming: 24th international conference, ilp 2014 Nancy, France, September 14–16, 2014 Revised Selected Papers 24th

Inductive Logic Programming: 24th International Conference, ...

引用

24th international conference on inductive logic programming, ilp 2014

作者： Davis, Jesse Ramon, Jan Department of Computer Science KU Leuven Leuven Belgium

来源：评论

学校读者我要写书评

暂无评论

25th international conference on inductive logic programming, ilp 2015

引用

25th international conference on inductive logic programming, ilp 2015

ISBN: (纸本)9783319405650

the proceedings contain 14 papers. the special focus in this conference is on inductive logic programming. the topics include: Relational kernel-based grasping with numerical features;complex aggregates within random forests;distributed parameter learning for probabilistic ontologies;meta-interpretive learning of data transformation programs;statistical relational learning with soft quantifiers;ontology learning from interpretations in lightweight description logics;constructing markov logic networks from first-order default rules;a note on mining all graphs;processing markov logic networks with GPUs;using ilp to identify pathway activation patterns in systems biology;an algebraic prolog for kernel programming;an exercise in declarative modeling for relational query mining;learning inference by induction and identification of transition models of biological systems in the presence of transition noise.

关键词：

来源：评论

学校读者我要写书评

暂无评论

inductive logic programming meets relational databases: Efficient learning of markov logic networks 1

引用

26th international conference on inductive logic programming, ilp 2016

作者： Malec, Marcin Khot, Tushar Nagy, James Blask, Erik Natarajan, Sriraam Indiana University Bloomington BloomingtonIN United States Allen Institute of AI Seattle United States Air Force Research Laboratory Riverside United States

ISBN: (数字)9783319633428

ISBN: (纸本)9783319633411

Statistical Relational Learning (SRL) approaches have been developed to learn in presence of noisy relational data by combining probability theory with first order logic. While powerful, most learning approaches for these models do not scale well to large datasets. While advances have been made on using relational databases with SRL models [14], they have not been extended to handle the complex model learning (structure learning task). We present a scalable structure learning approach that combines the benefits of relational databases with search strategies that employ rich inductive bias from inductive logic programming. We empirically show the benefits of our approach on boosted structure learning for Markov logic Networks. © Springer international Publishing AG 2017.

关键词： Markov processes

来源：评论

学校读者我要写书评

暂无评论

24th international conference on inductive logic programming, ilp 2014

24th International Conference on Inductive Logic Programming...

引用

24th international conference on inductive logic programming, ilp 2014

ISBN: (纸本)9783319237077

the proceedings contain 14 papers. the special focus in this conference is on inductive logic programming. the topics include: Reframing on relational data;inductive learning using constraint-driven bias;nonmonotonic learning in large biological networks;construction of complex aggregates with random restart hill-climbing;logical minimisation of meta-rules within meta-interpretive learning;goal and plan recognition via parse trees using prefix and infix probability computation;effectively creating weakly labeled training examples via approximate domain knowledge;learning prime implicant conditions from interpretation transition;statistical relational learning for handwriting recognition;the most probable explanation for probabilistic logic programs with annotated disjunctions;towards machine learning of predictive models from ecological data;pagerank, proPPR, and stochastic logic programs;complex aggregates over clusters of elements and on the complexity of frequent subtree mining in very simple structures.

关键词：

来源：评论

学校读者我要写书评

暂无评论

SkILL - a Stochastic inductive logic Learner 14

SkILL - a Stochastic Inductive Logic Learner

引用

IEEE 14th international conference on Machine Learning and Applications ICMLA

作者： Corte-Real, Joana Mantadelis, theofrastos Dutra, Ines Rocha, Ricardo Burnside, Elizabeth Univ Porto CRACS Rua Campo Alegre P-4169007 Oporto Portugal Univ Porto INESC TEC P-4169007 Oporto Portugal Univ Wisconsin Dept Radiol Madison WI 53706 USA

ISBN: (纸本)9781509002870

Probabilistic inductive logic programming (Pilp) is a relatively unexplored area of Statistical Relational Learning which extends classic inductive logic programming (ilp). Within this scope, we introduce SkILL, a Stochastic inductive logic Learner, which takes probabilistic annotated data and produces First Order logic (FOL) theories. Data in several domains such as medicine and bioinformatics have an inherent degree of uncertainty, and because SkILL can handle this type of data, the models produced for these areas are closer to reality. SkILL can then use probabilistic data to extract non-trivial knowledge from databases, and also address efficiency issues by introducing an efficient search strategy for finding hypotheses in Pilp environments. SkILL's capabilities are demonstrated using a real world medical dataset in the breast cancer domain.

关键词： Probabilistic inductive logic programming Statistical relational learning

来源：评论

学校读者我要写书评

暂无评论

SkILL - A Stochastic inductive logic Learner

SkILL - A Stochastic Inductive Logic Learner

引用

international conference on Machine Learning and Applications (ICMLA)

作者： Joana Côrte-Real theofrastos Mantadelis Inês Dutra Ricardo Roha Elizabeth Burnside CRACS & INESC TEC University of Porto Rua do Campo Alegre Porto Portugal Universidade do Porto Porto Porto PT Department of Radiology University of Wisconsin WI USA

关键词： Probabilistic logic Measurement Cancer logic programming Sociology Statistics

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共5页 << < 1 2 3 4 5 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：