检索结果-内蒙古大学图书馆

The Bipartite Network Projection-recommended algorithm for Predicting Long Non-coding RNA-Protein Interactions

MOLECULAR THERAPY-NUCLEIC ACIDS 2018年 13卷 464-471页

作者： Zhao, Qi Yu, Haifan Ming, Zhong Hu, Huan Ren, Guofei Liu, Hongsheng Liaoning Univ Sch Math Shenyang 110036 Peoples R China Shenzhen Univ Natl Engn Lab Big Data Syst Comp Technol Shenzhen 518060 Peoples R China Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen 518060 Peoples R China Liaoning Univ Sch Life Sci Shenyang 110036 Peoples R China Liaoning Univ Sch Informat Shenyang 110036 Peoples R China Res Ctr Comp Simulating & Informat Proc Biomacrom Shenyang 110036 Peoples R China Engn Lab Mol Simulat & Designing Drug Mol Liaonin Shenyang 110036 Peoples R China

With the development of science and biotechnology, many evidences show that ncRNAs play an important role in the development of important biological processes, especially in chromatin modification, cell differentiation and proliferation, RNA progressing, human diseases, etc. Moreover, lncRNAs account for the majority of ncRNAs, and the functions of lncRNAs are expressed by the related RNA-binding proteins. It is well known that the experimental verification of lncRNA-protein relationships is a waste of time and expensive. So many time-saving and inexpensive computational methods are proposed to uncover potential lncRNA-protein interactions. In this work, we propose a novel computational method to predict the potential lncRNA-protein interactions with the bipartite network projection recommended algorithm (LPI-BNPRA). Our approach is a semi-supervised method based on the lncRNA similarity matrix, protein similarity matrix, and lncRNA-protein interaction matrix. Compared with three previous methods under the leave-one-out cross-validation, our model has a more high-confidence result with the AUC value of 0.8754 and the AUPR value of 0.6283. We also do case studies by the Mus musculus dataset to further reflect the reliability of our approach. This suggests that LPI-BNPRA will be a reliable computational method to uncover lncRNA-protein interactions in biomedical research.

关键词： lncRNA protein lncRNA-protein interaction prediction semi-supervised method recommended algorithm

来源：评论

学校读者我要写书评

暂无评论

Parallel Factorization Machine recommended algorithm Based on Map Reduce 10

Parallel Factorization Machine Recommended Algorithm Based o...

引用

10th International Conference on Semantics, Knowledge and Grids (SKG)

作者： Sun, Hanxiao Wang, Wenjie Shi, Zhongzhi Univ Chinese Acad Sci Sch Comp & Control Engn 19A Yuquan Rd Beijing 100049 Peoples R China Chinese Acad Sci Inst Comp Technol Key Lab Intelligent Informat Proc Beijing 100190 Peoples R China

ISBN: (纸本)9781479967155

Factorization Machines [1, 2] is a new factorization model that can combine the merits of SVM model with matrix factorization models. It can model all the interactive actions using factorized parameters. So it could mimic most other matrix factorization models by feature engineering. Due to the superior flexible, Factorization Machines has already been widely used in many recommended algorithm competitions and practical online recommended system. But, because of the prevalence of large dataset, there is a need to improve the scalability of computation in factorization machines model. In this paper, we propose a parallel algorithm can be used on Factorization Machines model. The experimental results show that the proposed algorithm has good speed-up and scalability on big dataset.

关键词： Factorization Machine Map Reduce Parallel recommended algorithm

来源：评论

学校读者我要写书评

暂无评论

Summary of research on recommendation system based on serendipity

引用

The Journal of China Universities of Posts and Telecommunications 2022年第4期29卷 89-105页

作者： Meng Wei Wang Liting LüMeng School of Information Science and Technology Beijing Forestry UniversityBeijing 100083China Engineering Research Center for Forestry-oriented Intelligent Information Processing National Forestry and Grassland AdministrationBeijing 100083China

Personalized recommender systems provide various personalized recommendations for different users through the analysis of their respective historical ***,the problem of the“filter bubble”which has to do with over-specialization ***(SRDP),one of the evaluation indicators,can provide users with unexpected and useful recommendations,and help to successfully mitigate the filter bubble problem,and enhance users’satisfaction levels and provide them with diverse *** SRDP is highly subjective and challenging to study,only a few studies have focused on it in recent *** this study,the research results on SRDP were summarized,the various definitions of SRDP and its applications were discussed,the specific SRDP calculation process from qualitative to quantitative perspectives was presented,the challenges and the development directions were outlined to provide a framework for further research.

关键词： serendipity recommended algorithm recommended diversity filter bubbles evaluation indicators

来源：评论

学校读者我要写书评

暂无评论

Prediction of Student's Grade by Combining Educational Knowledge Graph and Collaborative Filtering

引用

IEEE ACCESS 2024年 12卷 68382-68392页

作者： Zhang, Yiwen Mariano, Vladimir Y. Bringula, Rex P. Natl Univ Coll Comp & Informat Technol Manila 1008 Philippines Anhui Xinhua Univ Big Data & Artificial Intelligence Coll Hefei 230088 Peoples R China Univ East Coll Comp Studies & Syst Manila 1008 Philippines

Traditional collaborative filtering-based grade prediction methods overly rely on students' historical grades and overlook the content correlation between courses, resulting in lower accuracy in predicting student grades. This paper proposes a grade prediction method that combines the educational domain knowledge graph with collaborative filtering, gathering course semantic information and constructing a course knowledge graph as auxiliary information for grade prediction. Through experimentation, it has been demonstrated that the integration of the educational knowledge graph and collaborative filtering in the grade prediction method uncovers more semantic relationships between courses, thereby improving the accuracy of predicting grades for related courses. The Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) metrics show a decrease when compared to collaborative filtering and K-means algorithms. The method in this paper allows for more personalized learning and recommendation in the knowledge-rich field of education with semantic richness.

关键词： Knowledge graphs Collaborative filtering Vectors Semantics Prediction algorithms Recommender systems Collaboration Filtering Grade predicted knowledge graph collaborative filtering recommended algorithm

来源：评论

学校读者我要写书评

暂无评论

The Research of Recommendation System Based on Hadoop Cloud Platform 9

The Research of Recommendation System Based on Hadoop Cloud ...

引用

9th IEEE International Conference on Computer Science and Education (ICCSE)

作者： Wang, Chunzhi Zheng, Zhou Yang, Zhuang Hubei Univ Technol Sch Comp Sci Wuhan 430068 Peoples R China

ISBN: (纸本)9781479929511

this paper integrates hadoop with recommendation system. Recommendation system is a system which makes predictions of user preferences. In this paper, we introduces a improved hybrid recommended algorithm and combine MapReduce programming which is used on Hadoop plaform. Through practice, the improved algorithm can accurately acquiring user preferences, provide the user with recommendation when the user browses the web page. Finally, Hadoop can meet the demand of massive data processing, and achieve a highly performance system by making use of the data reprocessing method.

关键词： Hadoop Cloud computing recommended algorithm Hybrid algorithm

来源：评论

学校读者我要写书评

暂无评论

Research on Recommendation Methods Based on Sentiment Analysis and BTM Topic Modeling 18

Research on Recommendation Methods Based on Sentiment Analys...

引用

2nd International Conference on Computer Science and Artificial Intelligence (CSAI) / 10th International Conference on Information and Multimedia Technology (ICIMT)

作者： Min, Daozhen Huang, Lei Beijing JiaoTong Univ Sch Econ & Management Beijing 100044 Peoples R China

ISBN: (纸本)9781450366069

With the rapid development of the Internet and e-commerce, the importance of recommendation algorithms has become increasingly prominent. Data sparsity and scoring dependence are problems with most current recommended algorithms. In this paper, we propose the recommendation model of SABTMCF (sentiment analysis and BTM collaborative filtering). Based on the traditional collaborative filtering algorithm, the sentiment analysis and BTM topic model are used to mine the review data to obtain the user's real potential emotional emotions and different attributes of the product. The scoring matrix of the theme can alleviate the above two problems, and then calculate the similarity of the user's emotional preferences to construct the recommendation model. The paper uses Dangdang's comment data set as experimental data, and the results show that the SABTMCF algorithm can improve the data sparse problem to a certain extent and has better recommendation accuracy.

关键词： recommended algorithm sentiment analysis BTM

来源：评论

学校读者我要写书评

暂无评论

An Estimating algorithm for English Levels of Student and Difficulties of Test Question 3

An Estimating Algorithm for English Levels of Student and Di...

引用

3rd International Conference on Computer Science and Network Technology (ICCSNT)

作者： Zhou, Ya Li, He Huang, Guimin Zeng, Xiaolan Zeng, Xiangyan Guilin Univ Elect Technol Res Ctr Data Sci & Social Comp Guilin Peoples R China

ISBN: (纸本)9781479905614

In view of the problem that currently the students choose online test questions blindly, the establishment of the item recommendation system is necessary. According to the student's level, an estimating algorithm is used to sort items and recommend the question which is in the front of the sort to the student. According to the study of student over a certain period of time and all the answers to the questions of a certain passage that students have given, a multiple attribute decision model based on positive and negative ideal point is established. The model can adjust the level of the student and the difficulty of test question adaptively and ensure that the system will recommend the most suitable test questions.

关键词： estimating algorithm recommended algorithm self-adapting algorithm grey multiple attribute

来源：评论

学校读者我要写书评

暂无评论

An Improved Recommendation algorithm for Micro-blog Network Advertisement 17

An Improved Recommendation Algorithm for Micro-blog Network ...

引用

17th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)

作者： Yang, Yanxia Wuhan Univ Sci & Technol City Coll Fac Informat Engn Wuhan Hubei Peoples R China

ISBN: (纸本)9781538674451

In this paper, a layered hybrid network advertisement recommendation algorithm which is based on the micro-blog platform is proposed and implemented. In this algorithm, two kinds of recommendation algorithms are combined in a stacked way, and on the basis of results of classification recommendation algorithm, recommendation is conducted by employing the algorithm based on user clustering. The experiment proves that the algorithm can solve the data sparsity problem and optimize the recommendation results.

关键词： Micro-blog Marketing recommended algorithm Collaborative Filtering Naive Bayesian Classification

来源：评论

学校读者我要写书评

暂无评论

The Application of Recommendation algorithm in Digital Economy 3

The Application of Recommendation Algorithm in Digital Econo...

引用

3rd IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Tan, Jing Gu, Yao School of Management Wanjiang University of Technology Anhui Ma'anshan China

ISBN: (纸本)9798350317022

In the digital technology market, the main strategic actions of enterprises are often determined by data and algorithms, which is different from the traditional market. With the continuous improvement of data collection and processing technology, the amount of data continues to increase, and the environment for data collection, transmission, development and use has become more complex and diverse. An algorithm is a specific calculation process in which the input is converted into the output through a series of calculation steps. In recent years, recommendation algorithm, as one of the more important applications of algorithm recommendation, has become one of the trends of Internet development. The personal information security algorithm, data privacy vulnerabilities, media trends and information dissemination trends related to a large number of information flows from different platforms and institutions are important issues. Whether platforms and institutions must take measures to assume certain social responsibilities and ensure that the transformation from enterprise interests to user interests brings significant benefits, so as to play a more active role in society or the country. © 2023 IEEE.

关键词： application research digital economy recommended algorithm

来源：评论

学校读者我要写书评

暂无评论

A new approach for CCSDS image compression recommendation for multicomponent images to China-Brasil earth resources satellite

A new approach for CCSDS image compression recommendation fo...

引用

IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015

作者： Prata, Oscavo G. Pinho, Marcelo S. Instituto Tecnológico de Aeronáutica Sao José dos Campos SP Brazil

ISBN: (纸本)9781479979295

This paper presents a method for improving the performance of the compression algorithm recommended by CCSDS, operating with mutlicomponent images on lossy mode. The proposed method uses: KLT as the transform coding, an algorithm for distribute maximum bit rate between image components to maximize the PSNR, and a transport mechanism for transform coding coefficients. To evaluate the performance of the proposed method, images captured by the CCD camera of CBERS-2B were used. It was observed that the proposed method presents gains that can be of the order of 5 [dB] compared to the recommended algorithm being used to encode each image component independently. Furthermore, the results obtained demonstrate that the use of a fixed operator results in a performance close to that achieved by a computed transformation operator for each picture to be coded, for rates between 2 and 4 bit per pixel. © 2015 IEEE.

关键词： CCD image sensors image coding CBERS-2B CCD camera China-Brasil Earth resource satellite computed transformation operator image compression algorithm lossy mode multicomponent images recommended algorithm transform coding coefficients Discrete wavelet transforms Image coding Redundancy Satellites Standards Transform coding CCSDS Image Compression Karhunen-Loéve Transform Multicomponent Image consultative committee for space data systems image coding transform coding image compression algorithm Data compression Image compression CCD image sensors discrete wavelet transform satellites redundancy Karhunen-Loeve transform Compression algorithms

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：