International Journal of Emerging Trends & Technology in Computer Science
A Motivation for Recent Innovation & Research
ISSN 2278-6856
www.ijettcs.org
Call for Paper, Published Articles, Indexing Infromation
Title: |
Efficient Mining of User-Aware Sequential Topic and Event Patterns in Time Series Data
|
Author Name: |
P.Manvitha, G. Sunil Vijaya Kumar |
Abstract: |
Abstract
Recently, micro-blogs such as Twitter are attracting more and
more attentions all over the world. Micro blog messages are
real-time, spontaneous reports of what the users are feeling,
thinking and doing, so reflect users’ characteristics and
statuses. However, the real intentions of users for publishing
these messages are hard to reveal directly from individual
messages but both content information and temporal relations
of messages are required for analysis, especially for abnormal
behaviors without prior knowledge.
If illegal behaviors are involved, detecting and monitoring them
is particularly significant for social security surveillance. We
can verify the activities of students to analyze the growth and
the economy level to understand the behavior of student. For
example, a student may opt for part time while studying to
manage his economy needs this prevent the students financial
problems and helps for better studies. Below are the various
activities of student those are used for analysis.
(1).Higher Education (2).Training (3).Joblessness
(4).Employment (5).Further education (6).School.
In this paper, we are proposing a system , an efficient mining
of User-Aware Sequential Topic and Events Pattern for time
series data The proposed system will be used for time series data
sets directly connected to source micro-blog applications (like
twitter and Facebook) so it fetches the real time streaming time
series data It will be optimized for large data sets with parallel
processing The proposed system will be used to get the event
level information that can be used for identifying the abnormal
events those are performed illegally
Keywords: Web mining, sequential patterns, document
streams, rare events, pattern-growth, dynamic
programming |
Cite this article: |
P.Manvitha, G. Sunil Vijaya Kumar , "
Efficient Mining of User-Aware Sequential Topic and Event Patterns in Time Series Data " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS),
Volume 6, Issue 4, July - August 2017 , pp.
201-211 , ISSN 2278-6856.
|