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

71 篇 会议
7 册 图书
6 篇 期刊文献

馆藏范围

84 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

52 篇 工学
- 42 篇 计算机科学与技术...
- 26 篇 软件工程
- 10 篇 信息与通信工程
- 9 篇 电气工程
- 5 篇 仪器科学与技术
- 2 篇 机械工程
- 2 篇 控制科学与工程
- 2 篇 建筑学
- 2 篇 土木工程
- 1 篇 力学（可授工学、理...
- 1 篇 材料科学与工程（可...
- 1 篇 冶金工程
- 1 篇 动力工程及工程热...
- 1 篇 电子科学与技术（可...
- 1 篇 生物医学工程（可授...
- 1 篇 生物工程
24 篇 理学
- 20 篇 数学
- 2 篇 生物学
- 1 篇 地质学
- 1 篇 统计学（可授理学、...
6 篇 管理学
- 4 篇 图书情报与档案管...
- 2 篇 管理科学与工程(可...
- 1 篇 工商管理
1 篇 法学
- 1 篇 社会学

主题

29 篇 data structures
9 篇 data mining
5 篇 algorithm design...
4 篇 data mining and ...
4 篇 discrete mathema...
4 篇 feature extracti...
4 篇 clustering algor...
4 篇 prediction algor...
4 篇 artificial intel...
4 篇 algorithm analys...
3 篇 algorithms
3 篇 databases
3 篇 bioinformatics
3 篇 classification a...
3 篇 computational bi...
3 篇 data models
2 篇 parallel algorit...
2 篇 vm placement
2 篇 dictionary
2 篇 approximation al...

机构

4 篇 polytech univ de...
3 篇 california state...
2 篇 university of gr...
2 篇 mcgill univ mont...
2 篇 polytechnic univ...
2 篇 free univ brusse...
1 篇 university of ca...
1 篇 yahoo labs barce...
1 篇 sidney kimmel co...
1 篇 univ desarrollo ...
1 篇 department of co...
1 篇 faculty of infor...
1 篇 univ thessaly vo...
1 篇 sch comp sci & i...
1 篇 department of po...
1 篇 univ melbourne d...
1 篇 wilhelm-schickar...
1 篇 department of co...
1 篇 department of si...
1 篇 school of civil ...

作者

4 篇 iacono j
3 篇 tóth csaba d.
2 篇 ignacio rojas
2 篇 langerman s
2 篇 gonzalo joya
2 篇 gawrychowski paw...
2 篇 andreu catala
1 篇 khokhar ashfaq
1 篇 yu zheng
1 篇 vishwa s. parekh
1 篇 dusadee apichart...
1 篇 sacomoto gustavo
1 篇 salikhov kamil
1 篇 elena baralis
1 篇 luca cagliero
1 篇 gharbaoui molka
1 篇 michael a. jacob...
1 篇 qian weng
1 篇 hong edwin s.
1 篇 petri matthias

语言

83 篇 英文
1 篇 中文

检索条件"任意字段=13th International Symposium on Algorithms and Data Structures, WADS 2013"

共 84 条记录，以下是41-50 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：

Using cascading bloom filters to improve the memory usage for de Brujin graphs

Using cascading bloom filters to improve the memory usage fo...

引用

13th Workshop on algorithms in Bioinformatics, WABI 2013

作者： Salikhov, Kamil Sacomoto, Gustavo Kucherov, Gregory Lomonosov Moscow State University Moscow Russia INRIA Grenoble Rhône-Alpes France Laboratoire Biométrie et Biologie Evolutive Université Lyon 1 Lyon France Department of Computer Science Ben-Gurion University of the Negev Be'er Sheva Israel Laboratoire d'Informatique Gaspard Monge Université Paris-Est CNRS Marne-la-Vallée Paris France

ISBN: (纸本)9783642404528

De Brujin graphs are widely used in bioinformatics for processing next-generation sequencing (NGS) data. Due to the very large size of NGS datasets, it is essential to represent de Bruijn graphs compactly, and several approaches to this problem have been proposed recently. In this work, we show how to reduce the memory required by the algorithm of Chikhi and Rizk (WABI, 2012) that represents de Brujin graphs using Bloom filters. Our method requires 30% to 40% less memory with respect to their method, with insignificant impact to construction time. At the same time, our experiments showed a better query time compared to their method. this is, to our knowledge, the best practical representation for de Bruijn graphs. © 2013 Springer-Verlag.

关键词： data structures

来源：评论

学校读者我要写书评

暂无评论

PL-tree: An efficient indexing method for high-dimensional data

PL-tree: An efficient indexing method for high-dimensional d...

引用

13th international symposium on Spatial and Temporal databases, SSTD 2013

作者： Wang, Jie Lu, Jian Fang, Zheng Ge, Tingjian Chen, Cindy Department of Computer Science University of Massachusetts Lowell Olsen Hall 198 Riverside St. Lowell MA 01854 United States

ISBN: (纸本)9783642402340

the quest for processing data in high-dimensional space has resulted in a number of innovative indexing mechanisms. Choosing an appropriate indexing method for a given set of data requires careful consideration of data properties, data construction methods, and query types. We present a new indexing method to support efficient point queries, range queries, and k-nearest neighbor queries. Our method indexes objects dynamically using algebraic techniques, and it can substantially reduce the negative impacts of the "curse of dimensionality". In particular, our method partitions the data space recursively into hypercubes of certain capacity and labels each hypercube using the Cantor pairing function, so that all objects in the same hypercube have the same label. the bijective property and the computational efficiency of the Cantor pairing function make it possible to efficiently map between high-dimensional vectors and scalar labels. the partitioning and labeling process splits a subspace if the data items contained in it exceed its capacity. From the data structure point of view, our method constructs a tree where each parent node contains a number of labels and child pointers, and we call it a PL-tree. We compare our method with popular indexing algorithms including R*-tree, X-tree, quad-tree, and iDistance. Our numerical results show that the dynamic PL-tree indexing significantly outperforms the existing indexing mechanisms. © 2013 Springer-Verlag.

关键词： Geometry

来源：评论

学校读者我要写书评

暂无评论

A new algorithm relief hybrid (HRelief) for biological motifs selection

A new algorithm relief hybrid (HRelief) for biological motif...

引用

IEEE symposium on Bioinformatics and Bioengineering (BIBE)

作者： Faouzi Mhamdi Hanen Mhamdi Research Laboratory of Technologies of Information and Communication & Electrical Engineering ESSTT University Tunis TUNISIA

Feature selection plays a crucial role in the automatic learning field, since the non relevant and /or redundant ones can influence the strength of discrimination of a learning algorithm. In fact, select a minimum set of informative and relevant features can increase the performance of algorithms and the precision of prediction, minimize the time of data treatment, facilitates their visualization as well as their analysis. In this paper, we present a series of adaptations of algorithms for the motifs selection of Relief filtering algorithm. In the first two adaptation ways (HRelief1 and HRelief2) we transformed Relief in hybrid algorithms by using a classifier to evaluate the subset of the features generated. the third way of adaptation (HRelief3) helps in treating the problem of redundancy of features. Based on the experimentations done so far, these improvements resulted in an interesting outcome that encourages us to go into the depth of this orientation field.

关键词： Proteins Error analysis Feature extraction data mining Prediction algorithms Complexity theory

来源：评论

学校读者我要写书评

暂无评论

Decision tree induction to prediction of prognosis in severe traumatic brain injury of Brazilian patients from Florianopolis city

Decision tree induction to prediction of prognosis in severe...

引用

IEEE symposium on Bioinformatics and Bioengineering (BIBE)

作者： Merisandra C. M. Garcia Evandro T. Martins Fernando M. Azevedo Electrical Engineering Department Extreme South University of Santa Florianopolis Criciuma SC Brazil Intensive Care Unit Governador Celso Ramos Hospital Florianopolis SC Brazil

the data mining consists in identification of characteristics and relationships between data, aiming the transformation of these into useful knowledge. the obtainment of knowledge occurs trough tasks, methods and algorithms that have specific purposes, and that are applied according to the goals of analysis. the analysis showed in this article consists in application of data mining by task of classification by the method of decision tree induction by the C4.5 algorithm for the prediction of prognosis in severe traumatic brain injury. the traumatic brain injury is a public health problem, constituting in one of the main causes of morbidity and mortality. In the development were performed the steps of preprocessing, the application of data mining and the evaluation of generated model, obtaining the accuracy of 87%.

关键词： data mining Classification algorithms databases Algorithm design and analysis Decision trees Brain injuries data models

来源：评论

学校读者我要写书评

暂无评论

Subgraph Enumeration in Dynamic Graphs

Subgraph Enumeration in Dynamic Graphs

引用

IEEE international Conference on data Mining (ICDM)

作者： Abhijin Adiga Anil Kumar S. Vullikanti Dante Wiggins Virginia Bioinformatics Institute Virginia Tech Department of Computer Science Virginia Tech

ISBN: (纸本)9781479913282

A fundamental problem in many applications involving social and biological networks is to identify and count the number of embeddings of a given small sub graph in a large graph. Often, they involve dynamic graphs, in which the graph changes incrementally (e.g., by edge addition/deletion). We study the Dynamic Sub graph Enumeration (DSE) Problem, where the goal is to maintain a dynamic data structure to solve the sub graph enumeration problem efficiently when the graph changes incrementally. We develop a new data structure that combines two techniques: (i) the color-coding technique of Alon et al., 2008, for enumerating trees, and (ii) a dynamic data structure for maintaining the h-index of the graph (developed by Eppstein and Spiro, 2009). We derive worst case bounds for the update time in terms of the h-index of the graph and the maximum degree. We also study the empirical performance of our algorithm in a large set of real networks, and find significant improvement over the static methods.

关键词： data structures Heuristic algorithms Approximation algorithms Approximation methods Color Algorithm design and analysis Silicon

来源：评论

学校读者我要写书评

暂无评论

Bayesian Discovery of Multiple Bayesian Networks via Transfer Learning

Bayesian Discovery of Multiple Bayesian Networks via Transfe...

引用

IEEE international Conference on data Mining (ICDM)

作者： Diane Oyen Terran Lane Department of Computer Science University of New Mexico Albuquerque NM USA Google Inc Cambridge MA USA

ISBN: (纸本)9781479913282

Bayesian network structure learning algorithms with limited data are being used in domains such as systems biology and neuroscience to gain insight into the underlying processes that produce observed data. Learning reliable networks from limited data is difficult, therefore transfer learning can improve the robustness of learned networks by leveraging data from related tasks. Existing transfer learning algorithms for Bayesian network structure learning give a single maximum a posteriori estimate of network models. Yet, many other models may be equally likely, and so a more informative result is provided by Bayesian structure discovery. Bayesian structure discovery algorithms estimate posterior probabilities of structural features, such as edges. We present transfer learning for Bayesian structure discovery which allows us to explore the shared and unique structural features among related tasks. Efficient computation requires that our transfer learning objective factors into local calculations, which we prove is given by a broad class of transfer biases. theoretically, we show the efficiency of our approach. Empirically, we show that compared to single task learning, transfer learning is better able to positively identify true edges. We apply the method to whole-brain neuroimaging data.

关键词： Bayes methods data models Robustness Periodic structures Approximation methods Joints Approximation algorithms

来源：评论

学校读者我要写书评

暂无评论

Cartification: A Neighborhood Preserving Transformation for Mining High Dimensional data

Cartification: A Neighborhood Preserving Transformation for ...

引用

IEEE international Conference on data Mining (ICDM)

作者： Emin Aksehirli Bart Goethals Emmanuel Müller Jilles Vreeken University of Antwerp Belgium Karlsruhe Institute of Technology Germany

ISBN: (纸本)9781479913282

the analysis of high dimensional data comes with many intrinsic challenges. In particular, cluster structures become increasingly hard to detect when the data includes dimensions irrelevant to the individual clusters. With increasing dimensionality, distances between pairs of objects become very similar, and hence, meaningless for knowledge discovery. In this paper we propose Cartification, a new transformation to circumvent this problem. We transform each object into an item set, which represents the neighborhood of the object. We do this for multiple views on the data, resulting in multiple neighborhoods per object. this transformation enables us to preserve the essential pair wise-similarities of objects over multiple views, and hence, to improve knowledge discovery in high dimensional data. Our experiments show that frequent item set mining on the certified data outperforms competing clustering approaches on the original data space, including traditional clustering, random projections, principle component analysis, subspace clustering, and clustering ensemble.

关键词： Itemsets Clustering algorithms data mining Algorithm design and analysis Noise measurement Noise

来源：评论

学校读者我要写书评

暂无评论

Compression-Based Graph Mining Exploiting Structure Primitives

Compression-Based Graph Mining Exploiting Structure Primitiv...

引用

IEEE international Conference on data Mining (ICDM)

作者： Jing Feng Xiao He Nina Hubig Christian Böhm Claudia Plant University of Munich Technische Universität München

How can we retrieve information from sparse graphs? Traditional graph mining approaches focus on discovering dense patterns inside complex networks, for example modularity-based or cut-based methods. However, most real world data sets are very sparse. Nevertheless, traditional approaches tend to omit interesting sparse patterns like stars. In this paper, we propose a novel graph mining technique modeling the transitivity and the hub ness of a graph using structure primitives. We exploit these structure primitives for effective graph compression using the Minimum Description Length Principle. the compression rate is an unbiased measure for the transitivity or hub ness and therefore provides interesting insights into the structure of even very sparse graphs. Since real graphs can be composed of sub graphs of different structures, we propose a novel algorithm CXprime (Compression-based exploiting Primitives) for clustering graphs using our coding scheme as an objective function. In contrast to traditional graph clustering methods, our algorithm automatically recognizes different types of sub graphs without requiring the user to specify input parameters. Additionally we propose a novel link prediction algorithm based on the detected substructures, which increases the quality of former methods. Extensive experiments evaluate our algorithms on synthetic and real data.

关键词： Encoding Entropy Clustering algorithms data mining Communities Receivers Prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

Some results on topological colored motifs in metabolic networks

Some results on topological colored motifs in metabolic netw...

引用

IEEE symposium on Bioinformatics and Bioengineering (BIBE)

作者： Elói Araújo Marco A. Stefanes Faculdade de Computação Universidade Federal de Mato Grosso do Sul Brazil

In this work, we address the topological colored motif search problem in metabolic networks. this problem is a concern in biology, which seeks to describe the functions and the evolution of metabolism. Recently, several variations of this problem have been studied. Here, we present some hardness results for finding motifs. Furthermore, we describe the first polynomial algorithm for the case in which the motif is a colorful tree. We also detail a data structure that allows finding all of these types of motifs in a metabolic network.

关键词： Color Biochemistry Search problems Image color analysis Polynomials data structures

来源：评论

学校读者我要写书评

暂无评论

An approach to constructing reversible multi-qubit benchmarks with provably minimal implementations

An approach to constructing reversible multi-qubit benchmark...

引用

IEEE Conference on Nanotechnology

作者： Jerzy Jegier Paweł Kerntopf Marek Szyprowski Orange Labs Poland Warsaw Poland Department of Electronics and Information Technology University of Lódzź Lódz Poland

this paper reports on a method of the construction of new difficult benchmarks for reversible logic synthesis. It is shown how to extrapolate 3- and 4-variable reversible functions implemented by gate count minimal circuits having regular structure. In this way sequences of reversible functions of an arbitrary number of variables have been constructed for which we have built minimal circuits implementing them. For two example sequences of functions we applied the synthesis tool Revkit trying different synthesis algorithms. the outcome shows a large gap between the circuits synthesized by the tool and the ones proved minimal by construction.

关键词： Logic gates Benchmark testing Boolean functions Vectors Libraries data structures Cost function

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9页 << < 1 2 3 4 5 6 7 8 9 > >>

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：