检索结果-内蒙古大学图书馆

Extracting sequential frequent itemsets from probabilistic sequences database

International Journal of Information Technology (Singapore) 2023年第5期15卷 2509-2515页

作者： Seddiki, Imane Nouioua, Farid Barkat, Abdelbasset Computer Science Department Mouhamed El Bachir El Ibrahimi University Bordj Bou Arreridj El Anceur 34000 Algeria Computer Science Department Laboratory of Informatics and its Applications (LIAM) University of M’sila M’sila 28000 Algeria

computers now handle large amounts of data, leading to the emergence of data mining as a science to extract useful information from this data. Frequent itemset mining is a popular technique used to discover relationships between items in big data. However, in real-life scenarios, data may be incomplete or uncertain, posing a challenge for frequent itemset mining. This paper proposes a novel approach for mining sequential frequent itemsets from uncertain sequence databases. The approach comprises two main parts: extracting a set of probabilistic frequent itemsets, and filtering this set using the sequential information in the data. At the end of the paper, we provide a comparison with an existing method to further demonstrate the value of our approach. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer applications and Management.

关键词： Data mining Frequent Itemset Probabilistic database Sequences database Uncertain

来源：评论

学校读者我要写书评

暂无评论

A Systematic Literature Review of Web Search Personalization

引用

Recent Advances in computer science and Communications 2021年第7期14卷 2079-2086页

作者： Sharma, Sunny Rana, Vijay Department of Computer Applications Chandigarh University Punjab India Department of Computer Science and Applications Sant Baba Bhag Singh University Jalandhar India

The existing studies have already revealed that the information on the web is increasing rapidly. Ambiguous queries and users’ ability to express their intention through queries have been one of the key challenges in retrieving accurate search results from the search engine. This paper in response explored different methodologies proposed during 2005-2019 by the eminent researchers for obtaining better search results. Some of these methodologies are based on the users’ geographical location while others rely on re-ranking the web results and refinement of the users’ queries. Fellow researchers can use this literature to define the fundamental literature of their work. Furthermore, a brief case study of major search engines like Google, Yahoo, Bing, etc. along with the techniques used by these search engines for personalization is also discussed. Finally, the paper discusses some current issues and challenges related to personalization which further defines the future research directions. © 2021 Bentham science Publishers.

关键词： Search engines

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Study on Mobile Ad-hoc Routing Protocols: OLSR, AODV and DSDV 3

Comprehensive Study on Mobile Ad-hoc Routing Protocols: OLSR...

引用

3rd IEEE Global Conference for Advancement in Technology, GCAT 2022

作者： Jisha, R.C. Joseph, Jithin Basheer, Muhammed Nadeem Muhammed Amrita Vishwa Vidyapeetham Department of Computer Science and Applications Amritapuri India

ISBN: (数字)9781665468558

ISBN: (纸本)9781665468534

MANETs (Mobile Ad-hoc Networks) are distributed systems composed of wireless and mobile nodes that can organize themselves into ad-hoc network designs without the assistance of a central managing server. The nodes in a MANET move around in an arbitrary way, which is a part of constantly changing multi-hop technology. Because such networks can be set up in an instant anywhere and different types of routing algorithms are available for efficient communication. In the proposed work, we present a survey of simulation analysis based on the reactive and proactive Mobile ad-hoc network algorithms AODV, DSDV, and OLSR, respectively. The NS-3 simulator has been used to test the performance of these routing algorithms by measuring throughput, packet delivery ratio, number of packets missed, and other metrics. The result shows that AODV outperforms the other algorithms. © 2022 IEEE.

关键词： Mobile ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

EXAM: Explainable Models for Analyzing Malicious Android applications 1st

EXAM: Explainable Models for Analyzing Malicious Android App...

引用

1st International Conference on Advancements in Smart Computing and Information Security, ASCIS 2022

作者： Asmitha, K.A. Vinod, P. Rehiman, K. A. Rafidha Verma, Raman Prakash Kumar, Rajkishor Kumari, Surbhi Kumar, Nishchaya Department Computer Applications Cochin University of Science and Technology Kochi India

ISBN: (纸本)9783031230943

The open source nature and high performance have made Android smartphones popular world wide. On the other hand, the ease of usage and popularity has prompted malware creation. The proposed method presents a lightweight solution capable of detecting unknown malware on Android smartphones based on static analysis of *** files. Here we extract three different kinds of features i.e. permissions, activities and receivers, in order to evaluate if individual features are effective in detecting malware. Experiments suggest that our proposed deep learnig detection method is able to identify Android malware with an overall classification accuracy of 97.35% using boolean representation of the feature vector table. Comparative analysis of individual features recommends that the deep learning model resulted in better detection rate with permission feature. We also performed obfuscation of selected *** files and found that the detection rate of our trained model is about 100%. Moreover, we also show how explainability helps the analyst to assess different models. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Static analysis

来源：评论

学校读者我要写书评

暂无评论

Can A Recommendation System Manage the Labour Market?

Can A Recommendation System Manage the Labour Market?

引用

2022 International Joint Conference on Information and Communication Engineering, JCICE 2022

作者： Kahlawi, Adham Giambona, Francesca Buzzigoli, Lucia Grassini, Laura Martelli, Cristina University of Florence Department of Statistics Computer Science Applications Florence Italy

ISBN: (纸本)9781665460675

The labour market is a dynamic domain, which creates a permanent need for companies and workers to keep pace with the skills required by the labour market. Meanwhile, it creates a continuous problem in linking between offer and demand. In light of this, this work seeks to take advantage of job advertisements published by companies to understand the supply and demand in the labour market, in terms of skills, by applying a recommendation system. Besides, this recommendation system could be used by companies or by workers;finally, to support the matching between offer and demand in the labour market. © 2022 IEEE.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Predictive Analytics of Road Accidents Using Machine Learning 2

Predictive Analytics of Road Accidents Using Machine Learnin...

引用

2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022

作者： Kaliraja, C. Chitradevi, D. Rajan, Anju Hindustan Institute of Technology & Science Department of Computer Applications Chennai India

ISBN: (纸本)9781665437899

In today's world of transportation, road accidents are one of the most common problems. The world health organization has released a list of the top ten causes of human death, sadly, traffic accidents are in ninth place. Even in the automobile industry, many inventories make and produce safety features however, traffic accidents are inevitable. In this paper, the machine learning concept is applied to predict the severity of the accident and analyze factors like the number of accidents by year, Number of accidents by state, Accidents on the day of the week, road accidents by state day and hours, accidents ratio between rural and urban areas, Age people involved in the accidents, most dangerous time to drive, with the help of current dataset. This will be effective in improving safety measures and reducing traffic accidents. © 2022 IEEE.

关键词： Predictive analytics

来源：评论

学校读者我要写书评

暂无评论

Document Clustering Using Keyword Extraction 3

Document Clustering Using Keyword Extraction

引用

3rd IEEE Global Conference for Advancement in Technology, GCAT 2022

作者： Ramachandran, Raji Mohan, Manjusha K Sara, Subin K Amrita Vishwa Vidyapeetham Department of Computer Science and Applications Amritapuri India

ISBN: (数字)9781665468558

ISBN: (纸本)9781665468534

Increase in the number of research documents on a daily basis, we find difficulty in identifying proper documents as per our requirements. This paper discusses an effective method in document clustering using automatic keyword extraction. Keyword is the smallest unit that can convey the meaning of an entire page, it helps a user in deciding whether or not to read or skip an article. In this work, we compare different methods of keyword extraction and choose the best method of keyword extraction based on accuracy and precision. The proposed approach takes extracted keywords as input and constructs a variety of different clusters using Euclidean distance measure to group the document together. As a result, a user can conduct a keyword search and obtain the results within seconds. The use of keyword clusters reduces noise in data and consequently enhances cluster quality. © 2022 IEEE.

关键词： Search engines

来源：评论

学校读者我要写书评

暂无评论

An Efficient Boruta-Based Feature Selection and Classification of Gene Expression Data 3

An Efficient Boruta-Based Feature Selection and Classificati...

引用

3rd IEEE Global Conference for Advancement in Technology, GCAT 2022

作者： Kavitha, K.R. Sajith, Sreelakshmi Variar, Namitha H Amrita Vishwa Vidyapeetham Department of Computer Science and Applications Amritapuri India

ISBN: (数字)9781665468558

ISBN: (纸本)9781665468534

Gene expression data is biological data on the quantities of various transcription factors and other chemicals inside a cell at any particular time. It comes from a study of DNA microarrays. The amount of many chemical components' approaches shown by gene expression data reveals a range of facts about the cell's health. The difficulty with gene expression data is that it contains noise, missing values, and has an extremely high dimensionality since each gene in an organism's genome has a value in the thousands, despite the fact that the number of samples is considerably fewer. This leads to mistakes in the computational analysis due to the curse of dimensionality. We have utilised the feature selection approach to fix these issues. It is used to choose the most appropriate genes for the subject being studied from the large number of genes whose values are provided. Our idea is to use the Boruta feature selection algorithm, a random forest wrapper class approach, to select a collection of features from many samples produced by gene expression profiles. © 2022 IEEE.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Empirical Evaluation of Approximation Algorithm for Sorting by Prefix-block Interchanges 3

Empirical Evaluation of Approximation Algorithm for Sorting ...

引用

3rd IEEE Global Conference for Advancement in Technology, GCAT 2022

作者： Narayanan, R Soorya Rahul Krishnan, R. Amrita Vishwa Vidyapeetham Department of Computer Science and Applications Amritapuri India

ISBN: (数字)9781665468558

ISBN: (纸本)9781665468534

Sorting by prefix block interchange is a combina-torial optimization problem having its origin in comparative genomics. The problem is to sort a given permutation with the minimum number of prefix block interchanges. A prefix block interchange is a rearrangement operation that interchanges a block of permutation from the prefix with another disjoint block. In comparative genomics, a permutation is used to model the arrangement of genes in genomes, and a rearrangement operation like prefix block interchanges models global genomic mutations. The problem of sorting permutations by prefix block interchanges is used to compute the evolutionary distance between related species. The computational complexity of the problem is unknown and some approximation algorithms are existent. In this article, we perform an empirical study of the 2-approximation algorithm for sorting by prefix block interchange problem, designed by Antony Labarre. © 2022 IEEE.

关键词： Approximation algorithms

来源：评论

学校读者我要写书评

暂无评论

Comparative Study of Classification Algorithms for Weed detection 3

Comparative Study of Classification Algorithms for Weed dete...

引用

3rd IEEE Global Conference for Advancement in Technology, GCAT 2022

作者： Geethalekshmy, V. Keerthana, P Gowri Nair, Parvathy N Amrita Vishwa Vidyapeetham Department of Computer Science and Applications Amritapuri India

ISBN: (数字)9781665468558

ISBN: (纸本)9781665468534

Weed identification techniques that are effective can lower the cost of weed control while also improving crop quality and output. Herbicides are currently the most frequent method of weed management. In order to deal with the issues of weed man-agement in agriculture, accurate crop and weed discrimination is essential. This work deals with the performance comparison of different classification algorithms namely Convolutional Neural Network(CNN), Graph Convolutional Networks(GCN), k-Nearest Neighbor(k-NN), and Support Vector Machine(SVM). Feature extraction algorithms, Local Directional Pattern(LDP) and Local Directional Relation Pattern(LDRP) are used alongside SVM and kNN. For data expansion, Generative Adversarial Network(GAN) was used, which generates synthetic samples of images from the dataset. The result of the study shows that CNN gives the maximum accuracy of 90.58% in 'Crop and weed detection' dataset when compared with other classification models used for investigation in our paper. © 2022 IEEE.

关键词： Support vector machines

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：