检索结果-内蒙古大学图书馆

2017 International Conference on computer, Electrical and Communication engineering, ICCECE 2017

作者： Chatterjee, Rudra Prasad Ray, Chhanda Bag, Rajib Department of Computer Science Engineering Supreme Knowledge Foundation Group of Institutions MankunduWest Bengal India Training Govt. of West Bengal State Council of Educational Research Kolkata India

ISBN: (纸本)9781538611760

The Web usage mining techniques are used to scrutinize the web usage patterns for a web site. Web page prediction plays a vital role by predicting next set of web pages that a user may visit based on the knowledge of the previously visited pages. Web page prediction is the focus of attention of many researchers in recent times and different web page prediction frameworks have been proposed. In this paper, a comparative analysis between two different approaches of web page prediction, namely, Latest Substring Association Rule mining (LSA) and Hidden Markov Model (HMM) has been represented. Web page prediction is implemented by using both the approaches and the experimental results are provided. Finally, an improved approach for web page prediction is proposed at the end of the paper. © 2017 IEEE.

关键词： Hidden Markov models

来源：评论

学校读者我要写书评

暂无评论

CosineRecom: A KNN-Based Movie Recommendation System Using Cosine Similarity 4

CosineRecom: A KNN-Based Movie Recommendation System Using C...

引用

4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： Singh, Mandeep Mishra, Prafull Aggarwal, Nitin Kumar, Vinay Sharma, Pramod Kumar Yadav, Ritesh Bennett University School of Computer Science Engineering and Technology Greater Noida India Raj Kumar Goel Institute of Technology Department of Computer Science & Engineering UP Ghaziabad India Mfps Supervisor Oracle Development Database Admin Data Science PA United States Kiet Group of Institutions Department of Csit UP Ghaziabad India Kiet Group of Institute Department of Applied Science UP Ghaziabad India Raj Kumar Goel Institute of Technology Department of Computer Science & Engineering Ghaziabad India

ISBN: (纸本)9798350364729

Information overload is a major problem for many people who use the internet. This is because there is so much information available that it can be hard to know where to start. Filtering tools, like the Recommender System, are needed to solve this problem. These tools give users access to relevant information and let them customise their search results based on their liking. The Collaborative Filtering Recommendation System finds the group of active users who are your closest neighbours. This study shows many ways to use the supervised machine learning algorithm (KNN) method for the Movie recommendation System with different similarity measures, such as the cosine metric, Squared Error Similarity, Linear Correlation Coefficient, and Baseline Predictor Correlation. For the movie recommender system, these many changes to the KNN algorithm were tested on real data from the given dataset and compared based on accuracy measures such as the number of matching pairs and different types of error like mean absolute error, squared mean error, and squared root mean error. By making changes to the web browser, this recommendation system processing tool could be used as a substitute in the real world. © 2024 IEEE.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

Using analytic hierarchy process to evaluate deep learning for infrared target recognition

引用

Multimedia Tools and Applications 2024年第38期83卷 86229-86245页

作者： Xu, Laixiang Cao, Bingxu Wei, Xinhong Li, Bei Su, Jingfeng Ning, Shiyuan Zhao, Junmin School of Computer and Data Science Henan University of Urban Construction Pingdingshan467036 China School of Information Engineering Luohe Vocational Technology College Henan University of Technology Luohe Institute of Technology Luohe462000 China School of Computer and Data Science Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Pingdingshan467036 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Henan University of Urban Construction Pingdingshan467036 China Department of Software Information China Electronics Technology Group Corporation 36-th Research Institute Jiaxing314033 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Research Center of Intelligent Campus Application Engineering of Henan Province Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Henan University of Urban Construction Pingdingshan467036 China

In order to promote the evaluation performance of deep learning infrared automatic target recognition (ATR) algorithms in the complex environment of air-to-air missile research, we proposed an analytic hierarchy process (AHP) evaluation system consisting of the target recognition ability, the generalization recognition ability, the anti-interference ability, the background suppression ability, and the cost metrics ability. According to detailed quantitative analysis and experimental results, we establish probability evaluation models and get their probability values. Compared with traditional evaluation systems, our proposed method implementation is showing high reliability. Similar superior performances are also achieved, such as quick, comprehensive, and scientific. Through the above research, the key technology of deep learning performance evaluation in automatic target recognition has been broken through, which provides some basis and guidance for the analysis of infrared imaging-guided weapon systems. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Infrared imaging

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Person and Vehicle Re-identification via Relative Hard Samples in Industrial Surveillance System 3

Unsupervised Person and Vehicle Re-identification via Relati...

引用

3rd International Workshop on Intelligent Systems, IWIS 2023

作者： Tang, Qing Cao, Ge Jo, Kang-Hyun Jung, Hail Data Science Group INTERX Ulsan Korea Republic of University of Ulsan Department of Electrical Electronic and Computer Engineering Korea Republic of Seoul National University of Science and Technology Department of Business Administration Seoul Korea Republic of

ISBN: (纸本)9798350305043

Person and Vehicle Re-Identification (Re-ID) is a critical task in the realm of intelligent industrial surveillance systems. It aims to identify the same person or vehicle across different camera views or scenes, facilitating individual tracking across multiple cameras within industrial environments. Re-Id in an industrial environment can be more challenging than in a general environment due to its unique setting and limited annotated dataset. Hence, this paper focuses on addressing the fully unsupervised re-ID problem, aiming to develop a re-ID solution that can learn without the need for any human-annotated labeled data. Furthermore, recent studies have demonstrated the effectiveness of self-supervised Momentum Contrastive learning (MoCo) as an unsupervised object re-ID method. However, MoCo neglects the hard sample learning. Here, we introduced Relative Hard Samples (RHS) learning to ensure selection in an adaptive and stable way by considering the characteristics of each sample. Experimental results confirm the effectiveness of our proposed hard sample learning strategy RHS selection and RHS learning. Comprehensive experiments have been conducted on one vehicle re-ID dataset and two person re-ID datasets. © 2023 IEEE.

关键词： Vehicles

来源：评论

学校读者我要写书评

暂无评论

Diagrammatic proofs

Diagrammatic proofs

引用

16th International Joint Conference on Artificial Intelligence, IJCAI 1999

作者： Foo, Norman Y. Pagnucco, Maurice Nayak, Abhaya C. Department of Artificial Intelligence School of Computer Science and Engineering University of New South Wales NSW 2052 Australia Knowledge Systems Group School of MPCE Macquarie University NSW 2109 Australia

Diagrammatic reasoning comprises phenomena that range from the so-called "free-rides" (e.g. almost immediate understanding of visually perceived relationships) to conventions about tokens. Such reasoning must involve cognitive processes that are highly perceptual in content. In the domain of mathematical proofs where diagrams have had a long history, we have an opportunity to investigate in detail and in a controlled setting the various perceptual devices and cognitive processes that facilitate diagrammatically based arguments. This paper continues recent work by examining two kinds of diagrammatic proofs, called Categories 1 and 3 by Jamnik, et. al. 97], the first being one in which generalization of a diagram instance is implied, and the second being one in which an infinite completion is represented by an ellipsis. We provide explanations of why these proofs work, a semantics for ellipses, and conjectures about the underlying cognitive processes that seem to resonate with such proofs.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Two novel semantics of top-k queries processing in uncertain database

Two novel semantics of top-k queries processing in uncertain...

引用

10th IEEE International Conference on computer and Information Technology, CIT-2010, 7th IEEE International Conference on Embedded Software and Systems, ICESS-2010, 10th IEEE Int. Conf. Scalable Computing and Communications, ScalCom-2010

作者： Liu, Dexi Wan, Changxuan Xiong, N. Yang, Laurence T. Chen, Lei Jiangxi Key Laboratory of Data and Knowledge Engineering School of Information Technology Jiangxi University of Finance and Economics Nanchang China Department of Computer Science Georgia State University Atlanta GA United States Department of Computer Science St. Francis Xavier University Antigonish NS Canada Department of Computer Science HK University of Science and Technology Hong Kong Hong Kong

ISBN: (纸本)9780769541082

Top-k query is a powerful technique in uncertain databases because of the existence of exponential possible worlds, and it is necessary to combine score and confidence of tuples to derive top k answers. Different semantics, the combination methods of score and confidence, lead to different results. U-kRanks and Global Top-k are two semantics of Topk queries in uncertain database, which consider every alternative in x-tuple as single one and return the tuple which has the highest probability appearing at top k or a given rank. However, no matter which alternative (tuple) of an x-tuple appears in a possible world, it undoubtedly believes that this xtuple appears in the same possible world accordingly. Thus, instead of ranking every individual tuple, we define two novel Top-k queries semantics in uncertain database, Uncertain xkRanks queries (U-x-kRanks) and Global x-Top-k queries (Gx- Top-k), which return k entities according to the score and the confidence of alternatives in x-tuple, respectively. In order to reduce the search space, we present an efficient algorithm to process U-x-kRanks queries and G-x-Top-k queries. Comprehensive experiments on different data sets demonstrate the effectiveness of the proposed solutions. © 2010 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Learning platform: Emotional learning 10

Learning platform: Emotional learning

引用

10th Iberian Conference on Information Systems and Technologies, CISTI 2015

作者： Faria, Ana Raquel Almeida, Ana Martins, Constantino Gonçalves, Ramiro Computer Science Department GECAD-Knowledge Engineering and Decision Support Group Institute of Engineering Polytechnic of Porto Porto Portugal Universidade de Trás-os-Montes e Alto Douro Vila Real Portugal

ISBN: (纸本)9789899843455

The purpose of this paper is to propose new model for emotional interaction that uses learning styles and student emotional state to adapt the user interface and learning path. This aims to reduce the difficulty and emotional stain that students encounter while interacting with learning platforms. To this end will be used techniques of Affective computer that can capture the student emotional state and base on that change the course parameters (flow, organization or difficulty) or even an emotional interaction in order to recapture the student attention. © 2015 AISTI.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Resource association discovery in semantic Web

Resource association discovery in semantic Web

引用

IEEE International Conference on E-Commerce Technology for Dynamic E-Business

作者： Liang Bangyong Tang Jie Li Juanzi Wang Kehong Knowledge Engineering Group Department of Computer Science and Technology Tsinghua University China

Resources on the Web have direct and hidden relations. Direct relations mean the visible link between two resources like hyperlinks. Direct relations are easy to discover while hidden relations are not. Current discovery methods are mostly based on the text learning and user feedback methods. The text contents are not fit for inference and they are also lack of semantics. The Web pages are annotated with ontologies in semantic Web. The annotations are useful for inference. We propose a framework for resource association discovery in semantic Web. The framework uses the annotation for inference and the annotation hierarchy can be solved by mapping different ontologies. The experiment shows the satisfied results. Finally, the conclusion and future work are discussed

关键词： Semantic Web Ontologies Web pages Relational databases knowledge engineering computer science Feedback Keyboards Mice Collaboration

来源：评论

学校读者我要写书评

暂无评论

An Effective Classification Algorithm for Heart Disease Prediction with Genetic Algorithm for Feature Selection 1

An Effective Classification Algorithm for Heart Disease Pred...

引用

1st Mohammad Ali Jinnah University International Conference on Computing, MAJICC 2021

作者： Kanwal, Samina Rashid, Junaid Nisar, Muhammad Wasif Kim, Jungeun Hussain, Amir COMSATS University Islamabad Department of Computer Science Wah Campus Pakistan Kongju National University Department of Computer Science and Engineering Korea Republic of Edinburgh Napier University Data Science and Cyber Analytics Research Group EdinburghEHI 4DY United Kingdom

ISBN: (纸本)9781665424134

Heart disease is the world's leading cause of increasing death rates. Although there is a lot of research in the medical sector, an efficient and reliable model to predict this disease at an early stage is still required. So, early diagnosis of heart disease is the most promising strategy for effective treatment. In this paper, we utilize the Genetic algorithm (GA) to select attributes, which are used as input for the machine learning algorithms Deep Learning(DL), Support Vector Machine (SVM), Neural network (NN), Naive Bayes (NB), and Logistic regression (LR). The two datasets of heart disease are used for model implementation. The results evaluation is measured using accuracy, precision, and f-measure. The proposed model achieves the 92% result in the term of accuracy. In terms of precision, 96% result is achieved. © 2021 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Robust Visual Odometry Using Semantic Information in Complex Dynamic Scenes 5th

Robust Visual Odometry Using Semantic Information in Complex...

引用

5th International Conference on Cognitive Systems and Signal Processing, ICCSIP 2020

作者： Wang, Hao Wang, Le Fang, Baofu Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei University of Technology Hefei Anhui230009 China Department of Computer Science and Technology Hefei University of Technology Hefei Anhui230009 China

ISBN: (纸本)9789811623356

Traditional vision-based simultaneous localization and mapping (SLAM) technology cannot obtain the semantic information of the surrounding environment, which will cause the robot to fail to complete intelligent grasping, human-computer interaction, and other advanced decision tasks. There are many challenges to solve this problem, such as obtaining less semantic information of the environment with low precision and being unable to deal with dynamic objects in a real environment quickly and effectively. In this paper, a robust visual odometry using semantic information in complex dynamic scenes was designed. Specifically, we present a refined instance segmentation method based on the contextual information of the frame to improve the accuracy of segmentation. On this basis, a feature detection and elimination algorithm for dynamic objects based on instance-level semantic information is proposed to improve the localization accuracy of camera pose. We extensively evaluate our system on the public TUM data set and compare it with ORB-SLAM2 and other methods. Experiments show that our methods greatly improve the localization accuracy of the camera pose and the robustness of the system, which verifies that our system is effective in complex dynamic scenes. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Cameras

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：