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

3,117 篇 会议
142 册 图书
22 篇 期刊文献

馆藏范围

3,280 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

2,140 篇 工学
- 1,954 篇 计算机科学与技术...
- 1,096 篇 软件工程
- 404 篇 信息与通信工程
- 285 篇 电气工程
- 267 篇 生物工程
- 217 篇 控制科学与工程
- 172 篇 生物医学工程（可授...
- 79 篇 化学工程与技术
- 73 篇 光学工程
- 72 篇 机械工程
- 67 篇 仪器科学与技术
- 65 篇 电子科学与技术（可...
- 62 篇 安全科学与工程
- 55 篇 动力工程及工程热...
- 54 篇 网络空间安全
776 篇 理学
- 429 篇 数学
- 295 篇 生物学
- 151 篇 统计学（可授理学、...
- 148 篇 物理学
- 127 篇 系统科学
- 89 篇 化学
505 篇 管理学
- 306 篇 图书情报与档案管...
- 231 篇 管理科学与工程(可...
- 95 篇 工商管理
218 篇 医学
- 193 篇 临床医学
- 125 篇 基础医学(可授医学...
- 87 篇 药学(可授医学、理...
- 55 篇 公共卫生与预防医...
72 篇 法学
- 70 篇 社会学
51 篇 教育学
- 47 篇 教育学
35 篇 经济学
31 篇 农学
6 篇 艺术学
4 篇 军事学
1 篇 文学

主题

568 篇 data mining
543 篇 machine learning
242 篇 pattern recognit...
195 篇 deep learning
174 篇 feature extracti...
154 篇 artificial intel...
153 篇 support vector m...
113 篇 accuracy
113 篇 machine learning...
110 篇 training
93 篇 data models
80 篇 neural networks
78 篇 data mining and ...
65 篇 classification
62 篇 sentiment analys...
61 篇 classification a...
59 篇 big data
57 篇 predictive model...
50 篇 face recognition
48 篇 prediction algor...

机构

7 篇 maharishi school...
6 篇 guangdong univer...
5 篇 galgotias univer...
5 篇 centre of interd...
5 篇 pune
5 篇 chitkara univers...
5 篇 king fahd univer...
5 篇 uttaranchal univ...
5 篇 uttaranchal inst...
5 篇 institute of aut...
4 篇 indian institute...
4 篇 shanghai jiao to...
4 篇 chitkara univers...
4 篇 school of inform...
4 篇 indian statistic...
4 篇 south china univ...
4 篇 zhejiang univers...
4 篇 maharishi school...
4 篇 department of cs...
4 篇 university of ca...

作者

9 篇 de-shuang huang
7 篇 coenen frans
7 篇 venkatesh svetha
7 篇 petra perner
7 篇 tianrui li
6 篇 ryszard tadeusie...
6 篇 marcin korytkows...
6 篇 jacek m. zurada
6 篇 krasotkina olga
6 篇 lotfi a. zadeh
6 篇 mottl vadim
6 篇 leszek rutkowski
5 篇 vitoantonio bevi...
5 篇 sankar k. pal
4 篇 waiyamai kitsana
4 篇 sozo inoue
4 篇 sergei o. kuznet...
4 篇 duoqian miao
4 篇 shengli xie
4 篇 hepu deng

语言

2,835 篇 英文
436 篇 其他
45 篇 中文
1 篇 西班牙文
1 篇 土耳其文

检索条件"任意字段=3rd International Conference on Machine Learning and Data Mining in Pattern Recognition"

共 3281 条记录，以下是2331-2340 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：

NLP Based Sentiment Analysis on Twitter data Using Ensemble Classifiers 3

NLP Based Sentiment Analysis on Twitter Data Using Ensemble ...

引用

3rd international conference on Signal Processing Communication and Networking

作者： Kanakaraj, Monisha Guddeti, Ram Mohana Reddy Natl Inst Technol Karnataka Dept Informat Technol Mangalore 575025 India

ISBN: (纸本)9781467368230

Most sentiment analysis systems use bag-of-words approach for mining sentiments from the online reviews and social media data. Rather considering the whole sentence/paragraph for analysis, the bag-of-words approach considers only individual words and their count as the feature vectors. This may mislead the classification algorithm especially when used for problems like sentiment classification. Traditional machine learning algorithms like Naive Bayes, Maximum Entropy, SVM etc. are widely used to solve the classification problems. These machine learning algorithms often suffer from biasness towards a particular class. In this paper, we propose Natural Language (NLP) based approach to enhance the sentiment classification by adding semantics in feature vectors and thereby using ensemble methods for classification. Adding semantically similar words and context-sense identities to the feature vectors will increase the accuracy of prediction. Experiments conducted demonstrate that the semantics based feature vector with ensemble classifier outperforms the traditional bag-of-words approach with single machine learning classifier by 3-5%.

关键词： Sentiment Analysis Ensemble classifier Social Network Analysis Semantic Word Sense Disambiguation

来源：评论

学校读者我要写书评

暂无评论

Local and Global Genetic Fuzzy pattern Classifiers 11th

Local and Global Genetic Fuzzy Pattern Classifiers

引用

11th international conference on machine learning and data mining (MLDM)

作者： Davidsen, Soren Atmakuri Sreedevi, E. Padmavathamma, M. Sri Venkateswara Univ Dept Comp Sci Tirupati 517502 Andhra Pradesh India

ISBN: (纸本)9783319210247;9783319210230

Fuzzy pattern classifiers are a recent type of classifiers making use of fuzzy membership functions and fuzzy aggregation rules, providing a simple yet robust classifier model. The fuzzy pattern classifier is parametric giving the choice of fuzzy membership function and fuzzy aggregation operator. Several methods for estimation of appropriate fuzzy membership functions and fuzzy aggregation operators have been suggested, but considering only fuzzy membership functions with symmetric shapes found by heuristically selecting a "middle" point from the learning examples. Here, an approach for learning the fuzzy membership functions and the fuzzy aggregation operator from data is proposed, using a genetic algorithm for search. The method is experimentally evaluated on a sample of several public datasets, and performance is found to be significantly better than existing fuzzy pattern classifier methods. This is despite the simplicity of the fuzzy pattern classifier model, which makes it interesting.

关键词： Approximate reasoning pattern recognition Fuzzy classifier Genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

引用

3rd international conference on Human-Agent Interaction, HAI 2015

作者： Choi, Hyunsoek Park, Hyeyoung School of Electrical Engineering and Computer Science Kyungpook National University 80 Daehakro Bukgu Daegu Korea Republic of

ISBN: (纸本)9781450335270

In order to make machines able to recognize various patterns, it is important to define an appropriate function for measuring similarities between different objects. Conventional similarity measures are devised mainly for 1D vector data, which may lead to loss of information of 2D matrix data. We cast the calculation of similarity between two matrices as a neural network problem, and design the architecture for learning a similarity measure. We provide experiments on real 2D matrix data in the face recognition and gesture recognition, where we show that the learning of a similarity measure leads to improvements in the performance of the recognition problem. Also we compare the performance of the proposed measure with conventional distance measures for 2D matrix data. © 2015 ACM.

关键词： Matrix algebra

来源：评论

学校读者我要写书评

暂无评论

data Analysis for Courses Registration 11th

Data Analysis for Courses Registration

引用

11th international conference on machine learning and data mining (MLDM)

作者： Alzahrani, Nada Alsulim, Rasha Alaseem, Nourah Badr, Ghada King Saud Univ Riyadh Saudi Arabia IRI City Sci Res & Technol Applicat Alex Egypt

ISBN: (纸本)9783319210247;9783319210230

data mining is a knowledge discovery process to extract the interesting previously unknown, potentially useful and non-trivial patterns from large repositories of data. There is currently increasing interest in data mining in educational systems, making it into a growing new research community. This paper applies a frequent patterns extraction approach to analyzing the distribution of courses in universities, where there are core and elective courses. The system analyzes the data that is stored in the department's database. The objective is to consider if allocation of courses is appropriate when they are more likely to be taken in the same semester by most students. A workflow is proposed;where the data is assumed to be collected over many semesters for already graduated students. A case study is presented and results are summarized. The results show the importance of the proposed system to analyze the courses registration in a given department.

关键词： data mining Courses registration Education Frequent patterns Apriori Frequent-pattern growth

来源：评论

学校读者我要写书评

暂无评论

Robust Principal Component Analysis of data with Missing Values 11th

Robust Principal Component Analysis of Data with Missing Val...

引用

11th international conference on machine learning and data mining (MLDM)

作者： Karkkainen, Tommi Saarela, Mirka Univ Jyvaskyla Dept Math Informat Technol Jyvaskyla 40014 Finland

ISBN: (纸本)9783319210247;9783319210230

Principal component analysis is one of the most popular machine learning and data mining techniques. Having its origins in statistics, principal component analysis is used in numerous applications. However, there seems to be not much systematic testing and assessment of principal component analysis for cases with erroneous and incomplete data. The purpose of this article is to propose multiple robust approaches for carrying out principal component analysis and, especially, to estimate the relative importances of the principal components to explain the data variability. Computational experiments are first focused on carefully designed simulated tests where the ground truth is known and can be used to assess the accuracy of the results of the different methods. In addition, a practical application and evaluation of the methods for an educational data set is given.

关键词： PCA Missing data Robust statistics

来源：评论

学校读者我要写书评

暂无评论

Distributed forests for MapReduce-based machine learning 3

Distributed forests for MapReduce-based machine learning

引用

3rd IAPR Asian conference on pattern recognition, ACPR 2015

作者： Wakayama, Ryoji Murata, Ryuei Kimura, Akisato Yamashita, Takayoshi Yamauchi, Yuji Fujiyoshi, Hironobu Chubu University Japan NTT Communication Science Laboratories Japan

ISBN: (纸本)9781479961009

This paper proposes a novel method for training random forests with big data on MapReduce clusters. Random forests are well suited for parallel distributed systems, since they are composed of multiple decision trees and every decision tree can be independently trained by ensemble learning methods. However, naive implementation of random forests on distributed systems easily overfits the training data, yielding poor classification performances. This is because each cluster node can have access to only a small fraction of the training data. The proposed method tackles this problem by introducing the following three steps. (1) "Shared forests" are built in advance on the master node and shared with all the cluster nodes. (2) With the help of transfer learning, the shared forests are adapted to the training data placed on each cluster node. (3) The adapted forests on every cluster node are returned to the master node, and irrelevant trees yielding poor classification performances are removed to form the final forests. Experimental results show that our proposed method for MapReduce clusters can quickly learn random forests without any sacrifice of classification performance. © 2015 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Bug Report, Feature Request, or Simply Praise? On Automatically Classifying App Reviews 23

Bug Report, Feature Request, or Simply Praise? On Automatica...

引用

IEEE 23rd international Requirements Engineering conference (RE)

作者： Maalej, Walid Nabil, Hadeer Univ Hamburg Hamburg Germany

ISBN: (纸本)9781467369053

App stores like Google Play and Apple AppStore have over 3 Million apps covering nearly every kind of software and service. Billions of users regularly download, use, and review these apps. Recent studies have shown that reviews written by the users represent a rich source of information for the app vendors and the developers, as they include information about bugs, ideas for new features, or documentation of released features. This paper introduces several probabilistic techniques to classify app reviews into four types: bug reports, feature requests, user experiences, and ratings. For this we use review metadata such as the star rating and the tense, as well as, text classification, natural language processing, and sentiment analysis techniques. We conducted a series of experiments to compare the accuracy of the techniques and compared them with simple string matching. We found that metadata alone results in a poor classification accuracy. When combined with natural language processing, the classification precision got between 70-95% while the recall between 80-90%. Multiple binary classifiers outperformed single multiclass classifiers. Our results impact the design of review analytics tools which help app vendors, developers, and users to deal with the large amount of reviews, filter critical reviews, and assign them to the appropriate stakeholders.

关键词： data mining natural language processing pattern classification probability software reviews string matching text analysis App stores Apple AppStore Google Play app reviews classification bug report feature requests multiclass classifiers multiple binary classifiers review analytics tool design review metadata sentiment analysis techniques several probabilistic techniques star rating text classification user experiences Accuracy Computer crashes Google machine learning algorithms Metadata Natural language processing Training Natural Language Processing String matching Software reviews Computer crashes Text categorization Metadata machine learning algorithms text processing pattern recognition binary sorter data mining

来源：评论

学校读者我要写书评

暂无评论

3rd international Workshop on New Frontiers in mining Complex patterns, NFMCP 2014 held in Conjunction with European conference on machine learning and Principles and Practice of Knowledge Discovery in databases, ECML-PKDD 2014

3rd International Workshop on New Frontiers in Mining Comple...

引用

3rd international Workshop on New Frontiers in mining Complex patterns, NFMCP 2014 held in Conjunction with European conference on machine learning and Principles and Practice of Knowledge Discovery in databases, ECML-PKDD 2014

ISBN: (纸本)9783319178752

The proceedings contain 13 papers. The special focus in this conference is on New Frontiers in mining Complex patterns. The topics include: Semi-supervised learning for multi-target regression;evaluation of different data-derived label hierarchies in multi label classification;predicting negative side effects of surgeries through clustering;parallel multicut segmentation via dual decomposition;learning from imbalanced data using ensemble methods and cluster-based undersampling;prequential AUC for classifier evaluation and drift detection in evolving data streams;mining positional data streams;visualization for streaming telecommunications networks;temporal dependency detection between interval-based event sequences;discovering behavioural patterns in knowledge-intensive collaborative processes;learning complex activity preconditions in process mining;location prediction of mobile phone users using apriori-based sequence mining with multiple support thresholds and pitch-related identification of instruments in classical music recordings.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Revised Frequent pattern Model for Crime Situation recognition Based on Floor-Ceil Quartile Function 3

A Revised Frequent Pattern Model for Crime Situation Recogni...

引用

3rd international conference on Information Technology and Quantitative Management (ITQM)

作者： Isafiade, Omowunmi Bagula, Antoine Berman, Sonia Univ Cape Town Dept Comp Sci ZA-7701 Rondebosch South Africa Univ Western Cape Dept Comp Sci ZA-7535 Bellville South Africa

Identifying related offences in a criminal investigation is an important goal for crime analysts. This can deliver evidence that can assist in apprehension of suspects and better attribution of past crimes. The use of pattern based approaches has the potential to assist crime experts in discovering new patterns of criminal activity. Hence, research in this area continues. This paper revisits frequent pattern growth models for crime pattern mining. Frequent pattern (FP) based approaches, such as the FP-Growth model, have been identified to be more effective than techniques proposed in the past, such as Apriori. Therefore, this research proposes a descriptive statistical approach, based on a quartile (floor-ceil) function, for the minimum support threshold (MST) choice selection, which is a major decision step in the pruning phase of the Traditional FP-Growth (TFPG) model. Our revised frequent pattern growth (RFPG) model further proposes a pattern-pattern (P-p) paradigm to identify tuples of subtle crime pattern(s) sequences or recurring trends in criminal activity. We present empirical results in order to guide intended audience about future decisions or research regarding this model. Results indicate that RFPG is more promising than TFPG and will always ensure the utilisation of a reasonable percentage of the crime dataset, in order to produce more reliable and sufficiently informative patterns or trends. (C) 2015 Published by Elsevier B.V.

关键词： Crime mining Frequent pattern Crime situation recognition FP-Growth MST

来源：评论

学校读者我要写书评

暂无评论

Hybrid Approach for Inductive Semi Supervised learning Using Label Propagation and Support Vector machine 11th

Hybrid Approach for Inductive Semi Supervised Learning Using...

引用

11th international conference on machine learning and data mining (MLDM)

作者： Govada, Aruna Joshi, Pravin Mittal, Sahil Sahay, Sanjay K. BITS Pilani Zuarinagar 403726 Goa India

ISBN: (纸本)9783319210247;9783319210230

Semi supervised learning methods have gained importance in today's world because of large expenses and time involved in labeling the unlabeled data by human experts. The proposed hybrid approach uses SVM and Label Propagation to label the unlabeled data. In the process, at each step SVM is trained to minimize the error and thus improve the prediction quality. Experiments are conducted by using SVM and logistic regression(Logreg). Results prove that SVM performs tremendously better than Logreg. The approach is tested using 12 datasets of different sizes ranging from the order of 1000s to the order of 10000s. Results show that the proposed approach outperforms Label Propagation by a large margin with F-measure of almost twice on average. The parallel version of the proposed approach is also designed and implemented, the analysis shows that the training time decreases significantly when parallel version is used.

关键词： Semi-supervised learning data mining Support vector machine Label propagation

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329页 << < 230 231 232 233 234 235 236 237 238 239 > >>

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：