Advanced Topics in Mobile Communications (AToMIC) (Summer 2016): Difference between revisions

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AToMIC course in summer semester 2016 will be focused on social networks and mobile big data.


Lecturer: Prof. Xiaoming Fu
== Details ==
{{CourseDetails
|credits=5 ECTS
|module=M.Inf.223: Seminar Telematik III ''-or-'' M.Inf.224: Seminar Computernetzewerke II (old Regulations) ''-or-'' 3.10: Advanced Topics in Internet Research (II)(ITIS); M.Inf.1223 (new Regulations)
|lecturer=[http://www.net.informatik.uni-goettingen.de/people/xiaoming_fu Prof. Dr. Xiaoming Fu]
|ta=[http://www.net.informatik.uni-goettingen.de/people/tao_zhao Tao Zhao, MSc.], [http://www.net.informatik.uni-goettingen.de/people/hong_huang Ms. Hong Huang]
|time=TBA
|place=TBA
|univz=[https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=157922&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung]
}}


Teaching assistants: Tao Zhao, Hong Huang
==Course Overview==
People move and stay in different locations in different time. Human mobility has a lot of impact on the social group formation and dynamics, interaction, and other activities. AToMIC course in summer semester 2016 will be focused on social networks on mobile big data. It will start with introduction to related methods and theories, together with real dataset demonstration. Students are expected to be organized in groups, running some tools on selected datasets, and present some scientific work on related topics.


Session 1 (15.04): Introduction, mobile Internet big data; literatures


Session 2 (22.04): Big data methods (machine learning, data mining, semantic and structural analysis)
==Requirements==


Session 3 (29.04): Data samples
==Presentation Schedule==
TBD


Session 4 (06.05): Social network theory
==Schedule==
{| {{Prettytable|width=}}
|-
|{{Hl2}} |'''Date'''
|{{Hl2}} |'''Topic'''
|{{Hl2}} |'''Slides'''
|-
| align="right" | 15.04.2016
| Introduction, mobile big data; literatures
|
|-
| align="right" | 22.04.2016
| Big data methods (machine learning, data mining, semantic and structural analysis)
|
|-
| align="right" | 29.04.2016
| Data samples
|
|-
| align="right" | 06.05.2016
| Social network theory
|
|-
| align="right" | 13.05.2016
| Interdisciplinary methods
|
|-
| align="right" | 20.05.2016
|cancelled due to business trips
|
|-
| align="right" | 27.05.2016
| cancelled due to business trips
|
|-
| align="right" | 03.06.2016
| Mining opinion leaders and structure hole spanners
|
|-
| align="right" |  10.06.2016
| cancelled due to business trips
|
|-
| align="right" |  17.06.2016
| cancelled due to business trips
|
|-
| align="right" |  25.06.2016
| Practical session
|
|-
| align="right" |  01.07.2016
| Final presentations (1)
|
|-
| align="right" |  08.07.2016
| Final presentations (2)
|
|-
| align="right" |  15.07.2016
| cancelled due to business trip
|
|-
|}


Session 5 (13.05): Interdisciplinary methods
==Final Presentations & Report==


20.05 & 27.05: cancelled due to business trips


Session 6 (03.06): Practical session (1)
[[Category:Courses]]
 
10.06 & 17.06: cancelled due to business trips
 
Session 7 (25.06): Practical session (2)
 
Session 8 (01.07): Final presentations (1)
 
Session 9 (08.07): Final presentations (2)
 
15.07: cancelled due to business trip

Latest revision as of 15:01, 6 April 2016

Details

Workload/ECTS Credits: 5 ECTS
Module: M.Inf.223: Seminar Telematik III -or- M.Inf.224: Seminar Computernetzewerke II (old Regulations) -or- 3.10: Advanced Topics in Internet Research (II)(ITIS); M.Inf.1223 (new Regulations)
Lecturer: Prof. Dr. Xiaoming Fu
Teaching assistant: Tao Zhao, MSc., Ms. Hong Huang
Time: TBA
Place: TBA
UniVZ [1]


Course Overview

People move and stay in different locations in different time. Human mobility has a lot of impact on the social group formation and dynamics, interaction, and other activities. AToMIC course in summer semester 2016 will be focused on social networks on mobile big data. It will start with introduction to related methods and theories, together with real dataset demonstration. Students are expected to be organized in groups, running some tools on selected datasets, and present some scientific work on related topics.


Requirements

Presentation Schedule

TBD

Schedule

Date Topic Slides
15.04.2016 Introduction, mobile big data; literatures
22.04.2016 Big data methods (machine learning, data mining, semantic and structural analysis)
29.04.2016 Data samples
06.05.2016 Social network theory
13.05.2016 Interdisciplinary methods
20.05.2016 cancelled due to business trips
27.05.2016 cancelled due to business trips
03.06.2016 Mining opinion leaders and structure hole spanners
10.06.2016 cancelled due to business trips
17.06.2016 cancelled due to business trips
25.06.2016 Practical session
01.07.2016 Final presentations (1)
08.07.2016 Final presentations (2)
15.07.2016 cancelled due to business trip

Final Presentations & Report

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