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APWeb 2014
The 16th Asia-Pacific Web Conference
(APWeb)
5-7 Sept 2014, Changsha, China
1
Statistics



Participants: 200
Research Paper
 134 submissions (217, 54, 25%)
 34 accepted ( full research papers )
 23 accepted ( short …)
Area Distributions
 Social Network (31%)
Graphs (27%)
 Data Mining (17%)
Cloud (10%)
 Text, web data (7%)
Other (8%)
KEG seminar
2
Conference Program
16.11.2006
KEG seminar
3
Conference Program
16.11.2006
KEG seminar
4
DSL (Distinguished Lecture Series) 1

Steven Euijiong Whang (Google)

Data Analytics: Integration, Privacy, and Knowledge

Entity Resolution (ER)

Match; Merge; Chain

Data privacy ( information leakage )

Knowledge

A new ontology (called Biperpedia) being developed at Google
Research that is specialized for search applications.
16.11.2006
KEG seminar
5
DSL 2

Fabian M. Suchanek (Telecom ParisTech University)

A Hitchhiker's guide to Ontology

Ontology; YAGO

YAGO 2 + time and space information

Alignment of knowledge bases

Rule mining (semantic correlations)

Provenance of ontological data
16.11.2006
KEG seminar
6
DSL 3

Dr. Nan Tang (Qatar Computing Research Institute, Doha, Qatar)

Big Data Cleaning

Different aspects of data cleaning

Error detection

Data repairing
16.11.2006
KEG seminar
7
DSL 4

Dr. Xiaokui Xiao (Nanyang Technological University, Singapore)

Private Data Release via Wavelets and Bayesian Networks

The privacy of the individual data

Privelet, utilizes wavelet transforms (any range-count query)

PrivBayes, employs Bayesian networks
16.11.2006
KEG seminar
8
Tutorial

Xin Luna Dong (Google)

From Data Fusion to Knowledge Fusion

The Sonya project
1.
Knowledge Extraction

use 15 extractors to periodically extract knowledge from 1B+
Webpages.

only about 30% of the extracted triples are correct.
16.11.2006
KEG seminar
9
Tutorial
2.
Adapt data fusion techniques to solve the knowledge fusion

leveraging the collective wisdom from different extractors and from
different Web sources

compute well-calibrated probabilities for the truthfulness of each
triple
16.11.2006
KEG seminar
10
Keynote talk 1

Prof. Fang Binxin, Beijing University of Posts and Telecommunications

New Progress in Online Social Network Analysis

结构
1.
动态社区发现
2.
网络平均路径长度的估计

群体
1.
情感突发的在线突发事件检测模型
2.
话题层次

传播
1.
个体传播能力分析
16.11.2006
KEG seminar
11
Keynote talk 2

Prof. Christian S. Jensen , Aalborg University

Keyword-Based Spatial Web Querying

Mobile Internet ; Spatial web query

takes a user location and user-supplied keywords as arguments, and it
returns web objects that are spatially and textually relevant to these
arguments.

Prestige-Based Ranking

Graph; V: Spatial web objects; E: connect object that meet constraints
(distance; similarity)
16.11.2006
KEG seminar
12
Keynote talk 3

Dr. Divesh Srivastava, AT&T Labs-Research

Controversy Detection in Wikipedia

Wikipedia; Wisdom of the crowds; Controversy

How to understand the quality of the data?

Fine-grained controversy (when submitted)

Track same topic (surrounding text)

Distinguish other editor (support and duration)

Variability of text content ( sequence of wiki links)
16.11.2006
KEG seminar
13
Keynote talk 4

Prof. Neoklis Polyzotis, University of California Santa Cruz

Scaling Machine Learning to Big Data.

Machine Learning

More Data

More Powerful Models

The Machine Learning Workflow

Step I: Example Formation; Step II: Modeling; Step III: Evaluation

MapReduceMapReduce+LoopsSpecialized Tools
16.11.2006
KEG seminar
14
Best Paper

Group-based Personalized Location Recommendation on Social Networks
(Wang Henan*, Tsinghua; Li Guoliang, Tsinghua; Feng Jianhua, Tsinghua)

Location-based social networks
16.11.2006
KEG seminar
15

Abstract submission:

Research paper submission: March 31, 2015

Notification to authors: May 31, 2015

http://www.dmirlab.com/apweb2015/
16.11.2006
March 24, 2015
KEG seminar
16