scholarly journals A Large Scale System for Searching and Browsing Images from the World Wide Web

2006 ◽  
pp. 537-540 ◽  
Author(s):  
Alexei Yavlinsky ◽  
Daniel Heesch ◽  
Stefan Rüger
Keyword(s):  
World Wide Web ◽  
Large Scale ◽  
World Wide ◽  
Large Scale System ◽  
The World

Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations

1996 ◽  
Vol 60 (3) ◽  
pp. 50-68 ◽  
Author(s):  
Donna L. Hoffman ◽  
Thomas P. Novak
Keyword(s):  
World Wide Web ◽  
Large Scale ◽  
World Wide ◽  
Structural Model ◽  
The Internet ◽  
Research Issues ◽  
Computer Mediated ◽  
The World ◽  
Conceptual Foundations

The authors address the role of marketing in hypermedia computer-mediated environments (CMEs). Their approach considers hypermedia CMEs to be large-scale (i.e., national or global) networked environments, of which the World Wide Web on the Internet is the first and current global implementation. They introduce marketers to this revolutionary new medium, propose a structural model of consumer navigation behavior in a CME that incorporates the notion of flow, and examine a series of research issues and marketing implications that follow from the model.

Using the World-Wide Web to obtain large-scale word norms: 190,212 ratings on a set of 2,654 German nouns

2009 ◽  
Vol 41 (1) ◽  
pp. 13-19 ◽  
Author(s):  
Olaf Lahl ◽  
Anja S. Göritz ◽  
Reinhard Pietrowsky ◽  
Jessica Rosenberg
Keyword(s):  
World Wide Web ◽  
Large Scale ◽  
World Wide ◽  
Word Norms ◽  
The World

scholarly journals On the impact of publicly available news and information transfer to financial markets

2021 ◽  
Vol 8 (7) ◽  
pp. 202321
Author(s):  
Metod Jazbec ◽  
Barna Pàsztor ◽  
Felix Faltings ◽  
Nino Antulov-Fantulin ◽  
Petter N. Kolm
Keyword(s):  
World Wide Web ◽  
Financial Markets ◽  
Information Transfer ◽  
Large Scale ◽  
World Wide ◽  
Machine Learning Techniques ◽  
Economic Significance ◽  
The World ◽  
The Common ◽  
The Impact

We quantify the propagation and absorption of large-scale publicly available news articles from the World Wide Web to financial markets. To extract publicly available information, we use the news archives from the Common Crawl, a non-profit organization that crawls a large part of the web. We develop a processing pipeline to identify news articles associated with the constituent companies in the S&P 500 index, an equity market index that measures the stock performance of US companies. Using machine learning techniques, we extract sentiment scores from the Common Crawl News data and employ tools from information theory to quantify the information transfer from public news articles to the US stock market. Furthermore, we analyse and quantify the economic significance of the news-based information with a simple sentiment-based portfolio trading strategy. Our findings provide support for that information in publicly available news on the World Wide Web has a statistically and economically significant impact on events in financial markets.

LARGE-SCALE MINING, DISCOVERY AND VISUALIZATION OF WWW USER CLICKPATHS

2002 ◽  
Vol 02 (01) ◽  
pp. 21-48 ◽  
Author(s):  
BRENDAN KITTS ◽  
KEVIN HETHERINGTON-YOUNG ◽  
MARTIN VRIEZE
Keyword(s):  
Data Mining ◽  
World Wide Web ◽  
Computer Graphics ◽  
Association Rules ◽  
Large Scale ◽  
World Wide ◽  
Visual Representation ◽  
Graph Layout ◽  
The World ◽  
Commercial Sources

Analysis of user clickstreams on the World Wide Web is made challenging by the volume of data and the difficulty of visualizing millions of different navigation paths. We present a method for identifying user clickpaths which scales well on large amounts of data, and provides an intuitive and insightful visual representation of user activity. Our technique borrows from the data mining literature on association rules and the computer graphics literature on graph layout optimization. The method is demonstrated with data from two commercial sources and paints a fascinating picture of web activity.

Dancing Across the World Wide Web: Advocacy in the 21st Century

2009 ◽  
Author(s):  
Blair Williams Cronin ◽  
Ty Tedmon-Jones ◽  
Lora Wilson Mau
Keyword(s):  
World Wide Web ◽  
21St Century ◽  
World Wide ◽  
The World
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