检索结果-南通市图书馆

A tetrahedral data model for unstructured data management

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2010年第8期53卷 1497-1510页

作者： LI Wei & LANG Bo State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China State Key Laboratory of Software Development Environment Beihang University Beijing China

This paper proposes a tetrahedral data model for unstructured data management. The model defines the four components of unstructured data including: basic attributes, semantic characteristics, low-level features and raw data on its four facets, and the relations between these components. The internal implementation structure of the model and the data query language are designed and briefly introduced. This model provides a unified, integrated and associated description for different kinds of unstructured data, and supports intelligent data services such as associated retrieval and data mining. An example is given to demonstrate how to use the model for describing and manipulating data from a sample video base.

关键词： unstructured data data model query language associated retrieval intelligent services

Analysis and Optimization of Information Retrieval Algorithms for unstructured data

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Analysis and Optimization of Information Retrieval Algorithm...

Handling Big data in Relational database Management Systems

作者： Kunying Li Dexin Qiao Xiaolian Li Yu Ding Computer Application Technology Department PetroChina Research Institute of Petroleum Exploration ＆ Development

The Internet has diversified in the form of an explosion in recent years.It has spawned countless forms of Internet branching,and at the same time brought information to the PB level,and massive data is also called big data.More than 85% of the collected data is composed by unstructured and semi-structured data;in order to solve the data group management in the contract system of a large-scale energy enterprise,it aims to realize the interconnection of upstream business data,technology interoperability,research collaboration,and promote the demand for intelligent and massive unstructured data retrieval.This paper proposes a non-institutional data retrieval optimization algorithm based on periodic data heat and category labels.The algorithm is implemented by correlating the user’s retrieval behavior in the cycle and combining the defined file category tags.The experimental results show that the method not only can effectively filter and sort unstructured data,but also it can provide strong support for subsequent big data analysis and edge calculation.

关键词： Information Retrieval unstructured data user behavior file category optimize algorithm

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第9期72卷 5149-5164页

作者： Kamal ElDahshan Eman Selim Ahmed Ismail Ebada Mohamed Abouhawwash Yunyoung Nam Gamal Behery Faculty of Science Al-Azhar UniversityCairoEgypt Faculty of Computer and Artificial Intelligence Damietta UniversityEgypt Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea

Currently, relational database management systems (RDBMSs)face different challenges in application development due to the massive growthof unstructured and semi-structured data. This introduced new DBMS categories, known as not only structured query language (NoSQL) DBMSs, whichdo not adhere to the relational model. The migration from relational databasesto NoSQL databases is challenging due to the data complexity. This study aimsto enhance the storage performance of RDBMSs in handling a variety of data.The paper presents two approaches. The first approach proposes a convenientrepresentation of unstructured data storage. Several extensive experimentswere implemented to assess the efficiency of this approach that could resultin substantial improvements in the RDBMSs storage. The second approachproposes using the JavaScript Object Notation (JSON) format to representmultivalued attributes and many to many (M:N) relationships in relationaldatabases to create a flexible schema and store semi-structured data. Theresults indicate that the proposed approaches outperform similar approachesand improve data storage performance, which helps preserve software stabilityin huge organizations by improving existing software packages whose replacement may be highly costly.

关键词： Big data RDBMS NoSQL DBMSs MongoDB MySQL unstructured data semi-structured data

Rethinking big data in a networked world

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Computer Science 2016年第6期10卷 965-967页

作者： Lionel M. NI Haoyu TAN Jiang XIAO Department of Computer and Information Science University of Macao Macao China Fok Ying Tung Graduate School Hong Kong University of Science and Technology Hong Kong China

Since the early 21st century, big data has drawn much attention from both academia and industry. In the last decade of collecting massive data, seeking innovative applications, and developing powerful technologies, the major focus of the research and engineering in big data has shifted substantially in many aspects. It is time to rethink about this fuzzy term to make clear the upcoming opportunities and the most urgent challenges.

关键词： Cloud Computing Deep Neural Network unstructured data Social data Natural Language Processing Technique

Research of united model of knowledge discovery state space and its application

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2005年第4期16卷 875-880页

作者： You Fucheng Song Wei Yang Bingru Computer Dept. of Beijing Inst. of Graphic Communication Beijing 102600 P. R. China School of Information Engineering Beijing Univ. of Science and Technology Beijing 100083 P. R. China

There are both associations and differences between structured and unstructured data mining. How to unite them together to be a united theoretical framework and to guide the research of knowledge discovery and data mining has become an urgent problem to be solved. On the base of analysis and study of existing research results, the united model of knowledge discovery state space （UMKDSS） is presented, and the structured data mining and the complex type data mining are associated together. UMKDSS can provide theoretical guidance for complex type data mining. An application example of UMKDSS is given at last.

关键词： knowledge discovery unstructured data knowledge template.

Research Article Understanding the role of streamers in livestreaming commerce:a vocal–visual perspective

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Journal of Management Analytics 2023年第2期10卷 247-269页

作者： Wei Gao Ning Jiang Feng Gu College of Economics and Management Southwest UniversityChongqingPeople’s Republic of China Antai College of Economics and Management Shanghai Jiao Tong UniversityShanghaiPeople’s Republic of China

Despite streamers having earned widespread attention,no studies have explored the relationship between streamers and customer engagement from a vocal–visual perspective in the livestreaming commerce context.Drawing on the elaboration likelihood model,we examine how streamers’speech rate and facial attractiveness influence customer engagement using 434 pieces of unstructured livestreaming video data extracted from Taobao.The findings show that speech rate is positively related to customer engagement behaviors.Facial attractiveness has a significant positive effect on the number of comments and viewers obtained,but it has no impact on the number of likes received in a livestream.Speech rate and facial attractiveness demonstrate a significant interaction effect,increasing customer engagement behaviors.Additionally,the numbers of comments and viewers obtained are positively related to sales performance.These results offer new insights into the vital role of streamers and provide practical implications for improving customer engagement in livestreaming commerce.

关键词： speech rate facial attractiveness customer engagement unstructured data livestreaming commerce

Analytics,challenges and applications in big data environment:a survey

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Management Analytics 2016年第3期3卷 206-239页

作者： Mininath R.Bendre Vijaya R.Thool Department of Information Technology SGGSIE&TVishnupuriNandedIndia Department of Instrumentation Engineering SGGSIE&TVishnupuriNandedIndia

Big data refer to the massive amounts and varieties of information in the structured and unstructured form,generated by social networking sites,biomedical equipment,financial companies,internet and websites,scientific sensors,agriculture engineering sources,and so on.This huge amount of data cannot be processed using traditional data processing systems and technologies.Big data analytics is a process of examining information and patterns from huge data.Hence,the process needs a system architecture for data collection,transmission,storage,processing and analysis,and visualization mechanisms.In this paper,we review the background and futuristic aspects of big data.We first introduce the history,background and related technologies of big data.We focus on big data system architecture,phases and classes of big data analytics.Then we present an open source big data framework to address some of the big data challenges.Finally,we discuss different applications of big data with some examples.

关键词： unstructured data big data big data analytics cloud computing apache hadoop

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

基于映像机制的非结构化数据保真存储方法

基于映像机制的非结构化数据保真存储方法