scholarly journals WEB SEMANTICS DATA

2013 ◽  
pp. 27-30
Author(s):  
M. MARKANDEYULU ◽  
CH. JAYARAJU
Keyword(s):  
Research Area ◽  
Wide Area ◽  
Data Semantics ◽  
New Challenges ◽  
Using Data ◽  
Novel Applications ◽  
The Web ◽  
Infor Mation

Data Semantics is a wide area that continuously faces new challenges arising from the invention of new infor- mation formats and novel applications. An area that is partic- ularly challenging with respect to identifying, representing and using data semantics is the Web. This paper attempts to characterize the nature and challenges of Data Semantics on the Web as an interesting research area to be covered by the Journal on Data Semantics.

Predictive Prefetching on the Web and Its Potential Impact in the Wide Area

2004 ◽  
Vol 7 (2) ◽  
pp. 143-179 ◽  
Author(s):  
Christos Bouras ◽  
Agisilaos Konidaris ◽  
Dionysios Kostoulas
Keyword(s):  
Wide Area ◽  
Potential Impact ◽  
The Web

Novel Trends in Clustering

2010 ◽  
pp. 185-211 ◽  
Author(s):  
Claudia Plant ◽  
Christian Böhm
Keyword(s):  
Knowledge Discovery ◽  
General Problem ◽  
Life Sciences ◽  
Research Area ◽  
Data Set ◽  
Correlation Clustering ◽  
Projected Clustering ◽  
Emerging Trends ◽  
Novel Approaches ◽  
The Web

Clustering or finding a natural grouping of a data set is essential for knowledge discovery in many applications. This chapter provides an overview on emerging trends within the vital research area of clustering including subspace and projected clustering, correlation clustering, semi-supervised clustering, spectral clustering and parameter-free clustering. To raise the awareness of the reader for the challenges associated with clustering, the chapter first provides a general problem specification and introduces basic clustering paradigms. The requirements from concrete example applications in life sciences and the web provide the motivation for the discussion of novel approaches to clustering. Thus, this chapter is intended to appeal to all those interested in the state-of-the art in clustering including basic researchers as well as practitioners.

scholarly journals Information collection for fraud detection in P2P financial market

2018 ◽  
Vol 189 ◽  
pp. 06006 ◽  
Author(s):  
Hao Wang ◽  
Zonghu Wang ◽  
Bin Zhang ◽  
Jun Zhou
Keyword(s):  
Financial Market ◽  
Financial Service ◽  
Information Collection ◽  
Sufficient Information ◽  
Process Data ◽  
Service Group ◽  
Internet Firms ◽  
Long Time ◽  
New Challenges ◽  
The Web

Fintech companies have been facing challenges from fraudulent behavior for a long time. Fraud rate in Chinese P2P financial market could go as high as 10%. It is crucial to collect sufficient information of the user as input to the anti-fraud process. Data collection framework for Fintech companies are different from conventional internet firms. With individual-based crawling request, we need to deal with new challenges negligible elsewhere. In this paper, we give an outline of how we collect data from the web to facilitate our anti-fraud process. We also overview the challenges and solutions to our problems. Our team at HC Financial Service Group is one of the few companies that are capable of developing full-fledged crawlers on our own.

Blended Education in Turbomachinery and Fluid Dynamics

2009 ◽  
Author(s):  
Jari L. H. Backman ◽  
Teemu Turunen-Saaresti ◽  
Ahti Jaatinen
Keyword(s):  
Fluid Dynamics ◽  
Blended Learning ◽  
Teaching Methodology ◽  
Traditional Teaching ◽  
Student Groups ◽  
Teaching Platform ◽  
Contact Hours ◽  
New Challenges ◽  
Blended Education ◽  
The Web

The paper deals with blended education in turbomachinery and fluid dynamics courses in Finland. The teaching methodology of these courses has been developed to comply with the new challenges of the education in technology. Presently six of the courses in the curriculum are following the schemes explained in this presentation. The courses are studied in the last year of the Bachelor level and in the Masters level quantifying from 2 to 4 ECTS credits. Students get all the material from the teaching platform in the web, which can be accessed freely anytime and practically from anywhere. Before attending the teaching events, the students go through the study material, perform several exercises and take a quiz, which can give them extra points for the exam tally. The contact teaching of the course is divided into four Learning Sessions of four hours. The first half is reserved to deepen the acquired knowledge, and performed in a way to attract a more interactive atmosphere. In the second half the students are divided to groups, where they solve more difficult study exercises compared to those they already have trained on. As the students are expected to study with the material of blended learning in advance, the percentage of the contact hours has to be lowered in comparison to the traditional teaching in order to maintain a balance with the credits in the course. However, with the acquired knowledge, the students are more interactive with the teachers and the teaching becomes more efficient. The students have given positive feedback on the courses. The instructors have found that the blended learning is not necessary an easier task, although there are less contact hours with the student. The efficiency of teaching has increased and the teaching is more rewarding. Both the students and the teachers found that blended education suited best for student groups around 10 students.

A Method of Web Information Automatic Extraction Based on XML

2010 ◽  
Vol 20-23 ◽  
pp. 178-183
Author(s):  
Jun Hua Gu ◽  
Jie Song ◽  
Na Zhang ◽  
Yan Liu Liu
Keyword(s):  
High Speed ◽  
Data Extraction ◽  
Rule Base ◽  
Accurate Information ◽  
Extraction Technology ◽  
Web Information ◽  
Xpath Expression ◽  
Data Translation ◽  
Using Data ◽  
The Web

With the increasingly high-speed of the internet as well as the increase in the amount of data it contains, users are finding it more and more difficult to gain useful information from the web. How to extract accurate information from the Web efficiently has become an urgent problem. Web information extraction technology has emerged to solve this kind of problem. The method of Web information auto-extraction based on XML is designed through standardizing the HTML document using data translation algorism, forming an extracting rule base by learning the XPath expression of samples, and using extraction rule base to realize auto-extraction of pages of same kind. The results show that this approach should lead to a higher recall ratio and precision ratio, and the result should have a self-description, making it convenient for founding data extraction system of each domain.

Resisting the Opportunity for Change

2017 ◽  
Vol 36 (4) ◽  
pp. 392-405 ◽  
Author(s):  
James N. Druckman ◽  
Martin J. Kifer ◽  
Michael Parkin
Keyword(s):  
The Political ◽  
Political Environment ◽  
2016 Election ◽  
Previous Election ◽  
Unique Nature ◽  
The Creation ◽  
Online Campaigning ◽  
Using Data ◽  
And Shifts ◽  
The Web

This article explores congressional campaigning on the web in 2016. What impact did the unique nature of the 2016 election have on those involved with the creation and maintenance of congressional campaign websites? Did it cause them to alter their approach to online campaigning? Using data from a survey of campaign insiders, we find that the factors that influence how congressional campaigns view and use their websites were largely impervious to the unique electoral environment. Results show that, consistent with previous election years, campaigns maintained a fairly uniform view of likely visitors and target audiences, and they tended to see their campaign websites as digital hubs, best used for capturing the campaign’s overall message. We also find that, as in other years, nonincumbents continued to use their websites to campaign more aggressively than incumbents. Overall, the results suggest that congressional campaigning on the web is primarily driven by stable factors that transcend technological advancements and shifts in the political environment.

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