Wraplet: Wrapping Your Web Contents with a Lightweight Language

2007 ◽  
Author(s):  
Natsumi Sawa ◽  
Atsuyuki Morishima ◽  
Shigeo Sugimoto ◽  
Hiroyuki Kitagawa
Keyword(s):  
Web Contents

Pundit: augmenting web contents with semantics

2013 ◽  
Vol 28 (4) ◽  
pp. 640-659 ◽  
Author(s):  
M. Grassi ◽  
C. Morbidoni ◽  
M. Nucci ◽  
S. Fonda ◽  
F. Piazza
Keyword(s):  
Web Contents

Coarse-grain replica management strategies for dynamic replication of Web contents

2004 ◽  
Vol 45 (1) ◽  
pp. 19-34 ◽  
Author(s):  
Norihito Fujita ◽  
Yuichi Ishikawa ◽  
Atsushi Iwata ◽  
Rauf Izmailov
Keyword(s):  
Management Strategies ◽  
Coarse Grain ◽  
Dynamic Replication ◽  
Web Contents ◽  
Replica Management

Research on Efficient Spatial Keyword Queries Supporting Wildcard

2013 ◽  
Vol 427-429 ◽  
pp. 2554-2557
Author(s):  
Jin Kun Pan ◽  
Dong Sheng Li
Keyword(s):  
Bloom Filter ◽  
Location Based Services ◽  
High Time ◽  
Exact Match ◽  
Inverted File ◽  
Space Efficiency ◽  
Integrated Index ◽  
Web Contents ◽  
High Space ◽  
Realistic Scenes

With the popularity of location-based services, Web contents are being geo-tagged and spatial keyword queries that retrieve objects satisfying both spatial and keyword conditions are gaining in prevalence. The existing spatial keyword queries focus on exact match or prefix match of the keywords cannot satisfy the demand of wildcard based imprecise match in many realistic scenes. Aiming to solve this problem, two methods which are fit for different situation are put forward: the inverted file and R-tree integrated index which fits for the situation that requires high time efficiency and the Prefix Bloom Filter and R-tree integrated index which fits for the situation requiring high space efficiency. The effectiveness of the two indexes is valid through experiments.

Influence of COVID-19 Epidemic on Dark Web Contents

2021 ◽  
Author(s):  
Abdul Razaque ◽  
Bakhytzhan Valiyev ◽  
Bandar Alotaibi ◽  
Munif Alotaibi ◽  
Saule Amanzholova ◽  
...  
Keyword(s):  
Machine Learning ◽  
Technical Progress ◽  
Confidential Information ◽  
Web Contents ◽  
Global Events ◽  
Dark Web

The Dark Web is known as a place triggering a variety of criminal activities. Anonymization techniques enable illegal operations, leading to the loss of confidential information and its further use as bait, a trade product or even a crime tool. Despite technical progress, there is still not enough awareness of the Dark Web and its secret activity. In this study, we introduced the Dark Web Enhanced Analysis (DWEA), in order to analyze and gather information about the content accessed on the Dark Net based on data characteristics. The research was performed to identify how the Dark Web has been influenced by recent global events, such as the COVID-19 epidemic. The research included the usage of a crawler, which scans the network and collects data for further analysis with machine learning. The result of this work determines the influence of the COVID-19 epidemic on the Dark Net.

A Web Platform to Generate and Deliver Mobile Web Contents Without Programming Skills

2013 ◽  
pp. 869-881 ◽  
Author(s):  
David Martín ◽  
Ortzi Torices ◽  
Hugo Salas ◽  
Carlos Lamsfus ◽  
Aurkene Alzua-Sorzabal
Keyword(s):  
Mobile Web ◽  
Web Contents ◽  
Programming Skills ◽  
Web Platform

Extracting Information from Dark Web Contents/Logs

2019 ◽  
pp. 161-179
Author(s):  
Erdal Ozkaya ◽  
Rafiqul Islam
Keyword(s):  
Web Contents ◽  
Dark Web
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