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

3,150 篇 会议
173 册 图书
27 篇 期刊文献

馆藏范围

3,349 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

2,240 篇 工学
- 2,038 篇 计算机科学与技术...
- 1,085 篇 软件工程
- 402 篇 信息与通信工程
- 356 篇 电气工程
- 249 篇 生物工程
- 169 篇 控制科学与工程
- 157 篇 生物医学工程（可授...
- 73 篇 光学工程
- 73 篇 化学工程与技术
- 68 篇 机械工程
- 62 篇 仪器科学与技术
- 59 篇 电子科学与技术（可...
- 58 篇 安全科学与工程
- 46 篇 交通运输工程
- 38 篇 材料科学与工程（可...
- 38 篇 动力工程及工程热...
717 篇 理学
- 377 篇 数学
- 272 篇 生物学
- 169 篇 物理学
- 147 篇 统计学（可授理学、...
- 104 篇 系统科学
- 69 篇 化学
459 篇 管理学
- 298 篇 图书情报与档案管...
- 199 篇 管理科学与工程(可...
- 95 篇 工商管理
300 篇 医学
- 273 篇 临床医学
- 125 篇 基础医学(可授医学...
- 70 篇 药学(可授医学、理...
- 53 篇 公共卫生与预防医...
64 篇 法学
- 57 篇 社会学
32 篇 经济学
31 篇 教育学
28 篇 农学
6 篇 艺术学
3 篇 军事学
1 篇 文学

主题

549 篇 data mining
549 篇 machine learning
291 篇 pattern recognit...
243 篇 deep learning
192 篇 feature extracti...
163 篇 support vector m...
156 篇 artificial intel...
127 篇 accuracy
123 篇 training
117 篇 machine learning...
100 篇 data models
93 篇 data mining and ...
75 篇 classification
73 篇 convolutional ne...
72 篇 neural networks
70 篇 predictive model...
69 篇 computational mo...
68 篇 big data
58 篇 sentiment analys...
55 篇 learning systems

机构

10 篇 chinese academy ...
9 篇 chitkara centre ...
8 篇 zhejiang univers...
7 篇 guangdong univer...
7 篇 centre of resear...
6 篇 central south un...
6 篇 unsw sydney
6 篇 college of compu...
5 篇 badji mokhtar un...
5 篇 indian institute...
5 篇 xi'an university...
5 篇 indian statistic...
5 篇 southwest jiaoto...
5 篇 kobe university ...
5 篇 southern univers...
4 篇 columbia univers...
4 篇 chitkara univers...
4 篇 shanghai jiao to...
4 篇 institute of big...
4 篇 centre for patte...

作者

12 篇 de-shuang huang
12 篇 venkatesh svetha
8 篇 petra perner
7 篇 phung dinh
7 篇 jacek m. zurada
7 篇 krasotkina olga
7 篇 mottl vadim
6 篇 zheng-guang wu
6 篇 ryszard tadeusie...
6 篇 marcin korytkows...
6 篇 hongyi li
6 篇 chaojie li
6 篇 biao luo
6 篇 lotfi a. zadeh
6 篇 kang-hyun jo
6 篇 leszek rutkowski
6 篇 long cheng
6 篇 zhongzhi shi
5 篇 zhang yan
5 篇 vitoantonio bevi...

语言

3,035 篇 英文
298 篇 其他
38 篇 中文

检索条件"任意字段=4th International Conference on Machine Learning and Data Mining in Pattern Recognition"

共 3350 条记录，以下是2561-2570 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：

Kernel-based learning to Rank with Syntactic and Semantic Structures 13

Kernel-based Learning to Rank with Syntactic and Semantic St...

引用

36th ACM SIGIR Annual international conference on Research and Development in Information Retrieval (SIGIR)

作者： Moschitti, Alessandro Qatar Fdn Qatar Comp Res Inst Doha Qatar Univ Trento DISI Trento Italy

ISBN: (纸本)9781450320344

In recent years, machine learning (ML) has been more and more used to solve complex tasks in different disciplines, ranging from data mining to Information Retrieval (IR) or Natural Language Processing (NLP). these tasks often require the processing of structured input. For example, NLP applications critically deal with syntactic and semantic structures. Modeling the latter in terms of feature vectors for ML algorithms requires large expertise, intuition and deep knowledge about the target linguistic phenomenon. Kernel Methods (KMs) are powerful ML techniques (see e.g., [5]), which can alleviate the data representation problem as they substitute scalar product between feature vectors with similarity functions (kernels) directly defined between training/test instances, e.g., syntactic trees, (thus features are not needed anymore). Additionally, kernel engineering, i.e., the composition or adaptation of several prototype kernels, facilitates the design of the similarity functions required for new tasks, e.g., [1, 2]. KMs can be very valuable for IR research, e.g., KMs allow us to easily exploit syntactic/semantic structures, e.g., dependency, constituency or shallow semantic structures, in learning to rank algorithms [3, 4]. In general, KMs can make easier the use of NLP techniques in IR tasks. this tutorial aims at introducing essential and simplified theory of Support Vector machines (SVMs) and KMs for the design of practical applications. It describes effective kernels for easily engineering automatic classifiers and learning to rank algorithms, also using structured data and semantic processing. Some examples are drawn from well-known tasks, i.e., Question Answering and Passage Reranking, Short and Long Text Categorization, Relation Extraction, Named Entity recognition, Co-Reference Resolution. Moreover, some practical demonstrations are given with SVM-Light-TK (tree kernel) toolkit. More in detail, best practices for successfully using KMs for IR and NLP are pres

关键词： Question Answering Kernel Methods Large-Scale learning Support Vector machines Structural Kernels

来源：评论

学校读者我要写书评

暂无评论

international Joint conference SOCO'13-CISIS'13-ICEUTE'13: Salamanca, Spain, September 11th-13th, 2013 Proceedings - Volume 239

引用

2013年

作者： Álvaro Herrero Bruno Baruque Fanny Klett Ajith Abraham Václav Snåšel André C P L F De Carvalho Pablo García Bringas Ivan Zelinka Héctor Quintián Emilio S Corchado

ISBN: (纸本)9783319018539

this volume of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2013, CISIS 2013 and ICEUTE 2013, all conferences held in the beautiful and historic city of Salamanca (Spain), in September *** computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze very complex issues and *** a through peer-review process, the 8th SOCO 2013 international Program Committee selected 40 papers which are published in these conference proceedings, and represents an acceptance rate of 41%. In this relevant edition a special emphasis was put on the organization of special sessions. Four special sessions were organized related to relevant topics as: Systems, Man, and Cybernetics, data mining for Industrial and Environmental Applications, Soft Computing Methods in Bioinformatics, and Soft Computing Methods, Modelling and Simulation in Electrical *** aim of the 6th CISIS 2013 conference is to offer a meeting opportunity for academic and industry-related researchers belonging to the various, vast communities of Computational Intelligence, Information Security, and data mining. the need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, is intended to be the catalyst and the aggregation stimulus for the overall *** a through peer-review process, the CISIS 2013 international Program Committee selected 23 papers which are published in these conference proceedings achieving an acceptance rate of 39%.In the case of 4th ICEUTE 2013, the international Program Committee selected 11 papers which are published in these conference *** selection of papers was extremely rigorous in order to maintain the high quality of the conference and we would like to thank the members of the Program Committees for their hard work in the reviewing process. this i

关键词：

来源：评论

学校读者我要写书评

暂无评论

Combining One-Class Classifiers for Imbalanced Classification of Breast thermogram Features

Combining One-Class Classifiers for Imbalanced Classificatio...

引用

4th international Workshop on Computational Intelligence in Medical Imaging (CIMI)

作者： Krawczyk, Barlosz Schaefer, Gerald Wozniak, Michai Wroclaw Univ Technol Dept Syst & Comp Networks PL-50370 Wroclaw Poland Univ Loughborough Dept Comp Sci Loughborough Leics England

ISBN: (纸本)9781467359191

thermography provides an interesting modality for diagnosing breast cancer as it is a non-contact, non-invasive and passive technique that is able to detect small tumors, which in turn can lead to earlier diagnosis. We perform computer-aided diagnosis of breast thermograms based on image features describing bilateral differences in regions of interest and a pattern classification approach that learns from previous examples. As is often the case in medical diagnosis, such training sets are imbalanced as typically (many) more benign cases get recorded compared to malignant cases. In this paper, we address this problem and perform classification using an ensemble of one-class classifiers. One-class classification uses samples from a single distribution to derive a decision boundary, and employing this method on the minority class can significantly boost its recognition rate and hence the sensitivity of our approach. We combine several one-class classifiers using a random subspace approach and a diversity measure to select members of the committee. We show that our proposed technique works well and leads to significantly improved performance compared to a single one-class predictor as well as compared to state-of-the-art classifier ensembles for imbalanced data.

关键词： medical imaging breast thermogram breast cancer machine learning one-class classification multiple classifier system imbalanced classification

来源：评论

学校读者我要写书评

暂无评论

Superpixel Clustering and Planar Fit Segmentation of 3D LIDAR Point Clouds

Superpixel Clustering and Planar Fit Segmentation of 3D LIDA...

引用

4th international conference on Computing for Geospatial Research and Application (COM.Geo)

作者： Mahmoudabadi, Hamid Shoaf, Timothy Olsen, Michael J. Oregon State Univ Sch Civil & Construct Engn Corvallis OR 97330 USA Oregon State Univ Dept Elect Engn & Comp Sci Corvallis OR 97330 USA

ISBN: (纸本)9780769550121

Terrestrial laser scanning (TLS, also called ground-based Light Detection and Ranging, LIDAR) is an effective data acquisition method capable of high precision, detailed 3D models for surveying natural environments. However, despite the high density, and quality, of the data itself, the data acquired contains no direct intelligence necessary for further modeling and analysis - merely the 3D geometry (XYZ), 3-component color (RGB), and laser return signal strength (I) for each point. One common task for LIDAR data processing is the selection of an appropriate methodology for the extraction of geometric features from the irregularly distributed point clouds. Such recognition schemes must accomplish both segmentation and classification. Planar (or other geometrically primitive) feature extraction is a common method for point cloud segmentation;however, current algorithms are computationally expensive and often do not utilize color or intensity information. In this paper we present an efficient algorithm, that takes advantage of both colorimetric and geometric data as input and consists of three principal steps to accomplish a more flexible form of feature extraction. First, we employ a Simple Linear Iterative Clustering (SLIC) superpixel algorithm for clustering and dividing the colorimetric data. Second, we use a plane-fitting technique on each significantly smaller cluster to produce a set of normal vectors corresponding to each superpixel. Last, we utilize a Least Squares Multi-class Support Vector machine (LSMSVM) to classify each cluster as either "ground", "wall", or "natural feature". Despite the challenging problems presented by the occlusion of features during data acquisition, our method effectively generates accurate (> 85%) segmentation results by utilizing the color space information, in addition to the standard geometry, during segmentation.

关键词： LIDAR Laser Point Cloud Superpixel machine learning Clustering SVM

来源：评论

学校读者我要写书评

暂无评论

Color image segmentation based-on SVM using mixed features and combined kernel

Color image segmentation based-on SVM using mixed features a...

引用

4th international conference on Intelligence Science and Big data Engineering, IScIDE 2013

作者： Li, Lei Shi, Dong Yan Xu, Jun The Science in NUPT China Pattern Recognition and Intelligent System China Control Theory and Control Engineering China

ISBN: (纸本)9783642420566

Image segmentation occupies the important position in image processing, so both high-efficiency and accurate segmentation are of great importance to image's subsequent research. In this paper, taking the color and texture features into account, the color features are combined with RGB and HSV color space features, and the texture features are made up with the mean value and standard deviation. Considering the advantages of support vector machine (SVM) in classification, we convert the segmentation problem into a classification problem, and we can get the satisfied segmentation result. Genetic Algorithms (GA) is used for the optimization of the parameters in SVM's kernel which is combined with polynomial (poly) and radial basis function (rbf) kernel reasonably by mercer theorem. the experimental results show that we can segment various kinds of color images effectively. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Time-lag Method for Detecting Following and Leadership Behavior of Pedestrians from Mobile Sensing data

Time-lag Method for Detecting Following and Leadership Behav...

引用

11th Annual IEEE international conference on Pervasive Computing and Communications (PerCom)

作者： Kjaergaard, Mikkel Baun Blunck, Henrik Wustenberg, Markus Gronbaek, Kaj Wirz, Martin Roggen, Daniel Troester, Gerhard Aarhus Univ Dept Comp Sci DK-8000 Aarhus C Denmark Swiss Fed Inst Technol Wearable Comp Lab Zurich Switzerland

ISBN: (纸本)9781467345750;9781467345736

the vast availability of mobile phones with built-in movement and location sensors enable the collection of detailed information about human movement even indoors. As mobility is a key element of many processes and activities, an interesting class of information to extract is movement patterns that quantify how humans move, interact and group. In this paper we propose methods for detecting two common pedestrian movement patterns, namely individual following relations and group leadership. the proposed methods for identifying following patterns employ machine learning on features derived using similarity analysis on time lagged sequences of WiFi measurements containing either raw signal strength values or derived locations. To detect leadership we combine the individual following relations into directed graphs and detect leadership within groups by graph link analysis. Methods for detecting these movement patterns open up new possibilities in - amongst others - computational social science, reality mining, marketing research and location-based gaming. We provide evaluation results that show error rates down to 7%, improving over state of the art methods with up to eleven percentage points for following patterns and up to twenty percentage points for leadership patterns. Our method is, contrary to state of the art, also applicable in challenging indoor environments, e. g., multi-story buildings. this implies that even quite small samples allow us to detect information such as how events and campaigns in multistory shopping malls may trigger following in small groups, or which group members typically take the lead when triggered by e. g. commercials, or how rescue or police forces act during training exercises.

关键词： pattern recognition crowd behavior sensing mobile sensing signal strength-based methods

来源：评论

学校读者我要写书评

暂无评论

Software defect prediction using supervised learning algorithm and unsupervised learning algorithm

Software defect prediction using supervised learning algorit...

引用

Confluence 2013: the Next Generation Information Technology Summit (4th international conference)

作者： Anuradha Chug Shafali Dhall USICT GGSIPU New Delhi

Software defect prediction has recently attracted attention of many software quality researchers. One of the major areas in current project management software is to effectively utilize resources to make meaningful impact on time and cost. A pragmatic assessment of metrics is essential in order to comprehend the quality of software and to ensure corrective measures. Software defect prediction methods are majorly used to study the impact areas in software using different techniques which comprises of neural network (NN) techniques, clustering techniques, statistical method and machine learning methods. these techniques of data mining are applied in building software defect prediction models which improve the software quality. the aim of this paper is to propose various classification and clustering methods with an objective to predict software defect. To predict software defect we analyzed classification and clustering techniques. the performance of three data mining classifier algorithms named J48, Random Forest, and Naive Bayesian Classifier (NBC) are evaluated based on various criteria like ROC, Precision, MAE, RAE etc. Clustering technique is then applied on the data set using k-means, Hierarchical Clustering and Make Density Based Clustering algorithm. Evaluation of results for clustering is based on criteria like Time Taken, Cluster Instance, Number of Iterations, Incorrectly Clustered Instance and Log Likelihood etc. A thorough exploration of ten real time defect datasets of NASA[1] software project, followed by various applications on them finally results in defect prediction.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Distributed privacy-preserving P2P data mining via Probabilistic Neural Network Committee machines

Distributed privacy-preserving P2P data mining via Probabili...

引用

international conference on Information, Intelligence, Systems and Applications

作者： Yiannis Kokkinos Konstantinos Margaritis Parallel and Distributed Processing Laboratory Department of Applied Informatics University of Macedonia

ISBN: (纸本)9781479907694

this work describes a probabilistic neural network (PNN) committee machine for Peer-to-Peer data mining. the pattern neurons of the PNN committee are composed of locally trained class-specialized regularization network Peer classifiers. the training takes into account the asynchronous distributed and privacy-preserving requirements that can be met in P2P systems. the Peer classifiers are first trained in parallel based on their local data. While no local data exchange is possible among them, the peers can exchange their classifiers in the form of binaries, or agents. then an asynchronous distributed computing P2P cycle is executed to construct a mutual validation matrix. the train set of one Peer becomes the validation set of the other and only average rates are returned back. From this matrix we demonstrate that it is possible to perform weight based ensemble selection of best peer members for every class and in this way to find class-specialized Peer modules for the committee machine.

关键词： Neural Networks Peer-to-Peer data mining Privacy-preserving Distributed computing Committee machines

来源：评论

学校读者我要写书评

暂无评论

recognition of sleep dependent memory consolidation with multi-modal sensor data

Recognition of sleep dependent memory consolidation with mul...

引用

international Workshop on Wearable and Implantable Body Sensor Networks (BSN)

作者： Akane Sano Rosalind W. Picard Media Laboratory Massachusetts Institute of Technology Cambridge MA USA

ISBN: (纸本)9781479903313

this paper presents the possibility of recognizing sleep dependent memory consolidation using multi-modal sensor data. We collected visual discrimination task (VDT) performance before and after sleep at laboratory, hospital and home for N=24 participants while recording EEG (electroencepharogram), EDA (electrodermal activity) and ACC (accelerometer) or actigraphy data during sleep. We extracted features and applied machine learning techniques (discriminant analysis, support vector machine and k-nearest neighbor) from the sleep data to classify whether the participants showed improvement in the memory task. Our results showed 60–70% accuracy in a binary classification of task performance using EDA or EDA+ACC features, which provided an improvement over the more traditional use of sleep stages (the percentages of slow wave sleep (SWS) in the 1 st quarter and rapid eye movement (REM) in the 4th quarter of the night) to predict VDT improvement.

关键词： Sleep Accuracy Electroencephalography Hospitals Laboratories Temperature measurement Standards

来源：评论

学校读者我要写书评

暂无评论

AI*IA 2013: Advances in Artificial Intelligence: XIIIth international conference of the Italian Association for Artificial Intelligence, Turin, Italy, December 4-6, 2013. Proceedings 1

引用

丛书名： Lecture Notes in Computer Science

2013年

作者： Mario Alviano, Carmine Dodaro, Francesco Ricca (auth.), Matteo Baldoni, Cristina Baroglio, Guido Boella, Roberto Micalizio (eds.)

ISBN: (数字)9783319035246

ISBN: (纸本)9783319035239;9783319035246

this book constitutes the refereed proceedings of the 13th international conference of the Italian Association for Artificial Intelligence, AI*IA 2013, held in Turin, Italy, in December 2013. the 45 revised full papers were carefully reviewed and selected from 86 submissions. the conference covers broadly the many aspects of theoretical and applied Artificial Intelligence as follows: knowledge representation and reasoning, machine learning, natural language processing, planning, distributed AI: robotics and MAS, recommender systems and semantic Web and AI applications.

关键词：人工智能l。机器人学；数据采矿和知识发现；数理逻辑和正式语言；由抽象设备的计算；用户接口和人的计算机相互作用；模式识别

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335页 << < 253 254 255 256 257 258 259 260 261 262 > >>

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：