scholarly journals A strategy for data storage and the search for semi-structured data in the Web

Data Mining X ◽  
2009 ◽  
Author(s):  
C. A. S. A. do Nascimento ◽  
N. F. F. Ebecken ◽  
J. L. dos A. Rosa
Keyword(s):  
Data Storage ◽  
Structured Data ◽  
The Web

APLIKASI PENCARI INFORMASI PERMINTAAN LAYANAN WEB YANG ERROR MENGGUNAKAN ALGORITMA BOYER-MOORE

2016 ◽  
Vol 1 (1) ◽  
pp. 001
Author(s):  
Harry Setya Hadi
Keyword(s):  
Data Storage ◽  
Computer Network ◽  
Web Server ◽  
Access Methods ◽  
Ip Address ◽  
String Searching ◽  
Common Process ◽  
Web Server Logs ◽  
Different Parts ◽  
The Web

String searching is a common process in the processes that made the computer because the text is the main form of data storage. Boyer-Moore is the search string from right to left is considered the most efficient methods in practice, and matching string from the specified direction specifically an algorithm that has the best results theoretically. A system that is connected to a computer network that literally pick a web server that is accessed by multiple users in different parts of both good and bad aim. Any activity performed by the user, will be stored in Web server logs. With a log report contained in the web server can help a web server administrator to search the web request error. Web server log is a record of the activities of a web site that contains the data associated with the IP address, time of access, the page is opened, activities, and access methods. The amount of data contained in the resulting log is a log shed useful information.

APPLICATION OF OPEN WEB PATTERNS AND STRUCTURED DATA ON THE WEB TO GEOINFORMATICS

2018 ◽  
Author(s):  
Douglas Fils ◽  
◽  
Adam Shepherd ◽  
Eric Lingerfelt
Keyword(s):  
Structured Data ◽  
The Web

scholarly journals Improving the Quality of Linked Data Using Statistical Distributions

2018 ◽  
pp. 1638-1664 ◽  
Author(s):  
Heiko Paulheim ◽  
Christian Bizer
Keyword(s):  
Knowledge Base ◽  
Linked Data ◽  
Relational Databases ◽  
Knowledge Bases ◽  
Structured Data ◽  
Data Sources ◽  
Data Sets ◽  
Statistical Distributions ◽  
The Web

Linked Data on the Web is either created from structured data sources (such as relational databases), from semi-structured sources (such as Wikipedia), or from unstructured sources (such as text). In the latter two cases, the generated Linked Data will likely be noisy and incomplete. In this paper, we present two algorithms that exploit statistical distributions of properties and types for enhancing the quality of incomplete and noisy Linked Data sets: SDType adds missing type statements, and SDValidate identifies faulty statements. Neither of the algorithms uses external knowledge, i.e., they operate only on the data itself. We evaluate the algorithms on the DBpedia and NELL knowledge bases, showing that they are both accurate as well as scalable. Both algorithms have been used for building the DBpedia 3.9 release: With SDType, 3.4 million missing type statements have been added, while using SDValidate, 13,000 erroneous RDF statements have been removed from the knowledge base.

Towards Massive RDF Storage in NoSQL Databases

2019 ◽  
pp. 263-284 ◽  
Author(s):  
Zongmin Ma ◽  
Li Yan
Keyword(s):  
Data Storage ◽  
Large Scale ◽  
Future Research ◽  
Nosql Databases ◽  
Current State ◽  
Data Store ◽  
Rdf Data ◽  
Description Framework ◽  
Resource Description ◽  
The Web

The resource description framework (RDF) is a model for representing information resources on the web. With the widespread acceptance of RDF as the de-facto standard recommended by W3C (World Wide Web Consortium) for the representation and exchange of information on the web, a huge amount of RDF data is being proliferated and becoming available. So, RDF data management is of increasing importance and has attracted attention in the database community as well as the Semantic Web community. Currently, much work has been devoted to propose different solutions to store large-scale RDF data efficiently. In order to manage massive RDF data, NoSQL (not only SQL) databases have been used for scalable RDF data store. This chapter focuses on using various NoSQL databases to store massive RDF data. An up-to-date overview of the current state of the art in RDF data storage in NoSQL databases is provided. The chapter aims at suggestions for future research.

A Review of RDF Storage in NoSQL Databases

2016 ◽  
pp. 210-229 ◽  
Author(s):  
Zongmin Ma ◽  
Li Yan
Keyword(s):  
Data Storage ◽  
Large Scale ◽  
Future Research ◽  
Nosql Databases ◽  
Current State ◽  
Data Store ◽  
Rdf Data ◽  
Description Framework ◽  
Resource Description ◽  
The Web

The Resource Description Framework (RDF) is a model for representing information resources on the Web. With the widespread acceptance of RDF as the de-facto standard recommended by W3C (World Wide Web Consortium) for the representation and exchange of information on the Web, a huge amount of RDF data is being proliferated and becoming available. So RDF data management is of increasing importance, and has attracted attentions in the database community as well as the Semantic Web community. Currently much work has been devoted to propose different solutions to store large-scale RDF data efficiently. In order to manage massive RDF data, NoSQL (“not only SQL”) databases have been used for scalable RDF data store. This chapter focuses on using various NoSQL databases to store massive RDF data. An up-to-date overview of the current state of the art in RDF data storage in NoSQL databases is provided. The chapter aims at suggestions for future research.

scholarly journals Linked Data - The Story So Far

2009 ◽  
Vol 5 (3) ◽  
pp. 1-22 ◽  
Author(s):  
Christian Bizer ◽  
Tom Heath ◽  
Tim Berners-Lee
Keyword(s):  
Best Practices ◽  
Research Agenda ◽  
Linked Data ◽  
Structured Data ◽  
Data Space ◽  
Web Of Data ◽  
Technological Developments ◽  
Technical Principles ◽  
Global Data ◽  
The Web

The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward.

scholarly journals Research on Personalized and Secured E-Learning Systems using Data Mining Technique

2019 ◽  
Vol 8 (11S) ◽  
pp. 664-667
Keyword(s):  
Data Mining ◽  
Data Storage ◽  
Learning Systems ◽  
Large Set ◽  
Data Mining Technique ◽  
Large Space ◽  
Web Based ◽  
Web Based Learning ◽  
E Learning ◽  
The Web

Data mining is the concept for extracting the appropriate data from the large set of database. In today’s world it is widely used for many applications where learning applications is one of the major part. The e-Learning is the booming technology where anyone can learn everything from any part of the world. It is the digital way of learning the concepts and does not require the help of other persons to do so. It also requires the large space for data storage such as user information, course records and course details and so on. There are lot of learning applications available on the internet among which some might be subjected to frauds. So the security is the demanding thing every users looking for to protect their details. The users also seek for flexibility of using the applications. In perspective of distributed world, the complexity and interoperability of the data brings challenges in e-learning domain.Depends upon learner’s choice, the web based learning modules were developed for the students. Thus, a holistic approach is required for achieving the personalized content since the student groups are heterogeneous in nature. In addition to, the personalized content has to be protected in order to maintain the data integrity and privacy of the users. In this work, we survey about the present scenario of the web-based e-learning systems. Initially, we present the services oriented architecture of the e-learning systems and also clearly explain the different elearning layers.Then, we portray the existing studies processed in web based e-learning systems. Finally, we discuss about the challenges still persists in web-based learning systems. This paper will guide the upcoming researchers in e-learning fields.

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