Finding a team of Experts in Social Networks - PowerPoint PPT Presentation

1 / 22
About This Presentation
Title:

Finding a team of Experts in Social Networks

Description:

How can I find a team of experts that can collaborate effectively in order to ... Collaboration networks (e.g., DBLP graph, coauthor networks) ... – PowerPoint PPT presentation

Number of Views:110
Avg rating:3.0/5.0
Slides: 23
Provided by: IBMU301
Category:

less

Transcript and Presenter's Notes

Title: Finding a team of Experts in Social Networks


1
Finding a team of Experts in Social Networks
Theodoros Lappas UC Riverside
  • Joint work with Evimaria Terzi (IBM Almaden),
    Kun Liu (IBM Almaden)

2
Motivation
How can I find a team of experts that can
collaborate effectively in order to complete a
given task?
3
Problem
  • Given a task and a set of experts organized in a
    network, find a subset of experts that can
    effectively perform the task
  • Task set of required skills
  • Expert an individual with a specific skill-set
  • Network represents strength of relationships

4
Expertise networks
  • Collaboration networks (e.g., DBLP graph,
    coauthor networks)
  • Organizational structure of companies
  • LinkedIn
  • Geographical (map) of experts

5
What makes a team effective for a task?
  • T algorithms, java, graphics, python

Coverage every required skill in T is included
in the skill-set of at
least one team member
6
Is coverage enough?
Talgorithms,java,graphics,python
A,E could perform the task if they could
communicate
A
D
A
A,B,C form an effective group that can communicate
B
C
E
E
C
B
Communication the members of the team must be
able to efficiently communicate and work
together
7
Problem definition
  • Given a task and a social network of individuals
    G, find the subset (team) of G that can
    effectively perform the given task.
  • Thesis Good teams are teams that have the
    necessary skills and can also communicate
    effectively

8
How to measure effective communication?
The longest shortest path between any two nodes
in the subgraph
  • Diameter of the subgraph defined by the group
    members

A
D
A
B
C
E
E
C
B
diameter infty
diameter 1
9
How to measure effective communication?
The total weight of the edges of a tree that
spans all the team nodes
  • MST (Minimum spanning tree) of the subgraph
    defined by the group members

A
D
A
B
C
E
E
C
B
MST infty
MST 2
10
Problem definition v.1.1
  • Given a task and a social network G of
    individuals, find the subset (team) of
    individuals that can perform the given task and
    define a subgraph in G with the minimum diameter.
  • Problem is NP-hard

11
The RarestFirst algorithm
Talgorithms,java,graphics,python
graphics,python,java
algorithms,graphics
B
A
A
B
Skills algorithms graphics java python
E
E
algorithms,graphics,java
C
D
python,java
python
arare algorithms SrareBob, Eleanor
Diameter 2
12
The RarestFirst algorithm
Talgorithms,java,graphics,python
graphics,python,java
algorithms,graphics
A
B
Skills algorithms graphics java python
E
E
algorithms,graphics,java
C
C
D
python,java
python
arare algorithms SrareBob, Eleanor
Diameter 1
Running time Quadratic to the number of
nodes Approximation factor 2xOPT
13
Problem definition v.1.2
  • Given a task and a social network G of
    individuals, find the subset (team) of
    individuals that can perform the given task and
    define a subgraph in G with the minimum MST cost.
  • Problem is NP-hard

Best known Approximation factor O(log3n log k)
14
The SteinerTree problem
  • Graph G(V,E)
  • Set of Required Vertices R
  • Find G subgraph of G such that G contains all
    the required vertices (R) and MST(G) is minimized

Required vertices
15
The EnhancedSteiner algorithm
Talgorithms,java,graphics,python
graphics
graphics,python,java
algorithms,graphics
A
B
java
algorithms
E
E
algorithms,graphics,java
D
C
D
python
python,java
python
MST Cost 1
16
Experiments
17
Dataset
DBLP Dataset ( DM, AI, DB, T ) 6000
authors Skills keywords appearing in paper
titles 2000 features Social Network
Co-Authorship Graph Tasks Subsets of keywords
with different cardinality
18
Cardinality of teams
19
Example teams (I)
  • S. Brin, L. Page The anatomy of a large-scale
    hypertextual Web search engine
  • Paolo Ferragina, Patrick Valduriez, H. V.
    Jagadish, Alon Y. Levy, Daniela Florescu, Divesh
    Srivastava, S. Muthukrishnan
  • P. Ferragina ,J. Han, H. V.Jagadish, Kevin
    Chen-Chuan Chang, A. Gulli, S. Muthukrishnan,
    Laks V. S. Lakshmanan

20
Example teams (II)
  • J. Han, J. Pei, Y. Yin Mining frequent patterns
    without candidate generation
  • F. Bonchi
  • A. Gionis, H. Mannila, R. Motwani

21
Extensions
  • Other measures of effective communication
  • Other practical restrictions
  • Incorporate ability levels

22
  • Thanks for your attention!
Write a Comment
User Comments (0)
About PowerShow.com