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Presentation at the SF-COST High-Level Research Conference on Networked Humanities
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Social filter
1.
Is a personal
network better than Google? Social networks as collaborative ïŹlter to ïŹnd relevant information Patrick Danowski IST Austria
2.
Outline âą The problem âą
An idea âą 4 solutions âą Sum-up
3.
The problem
4.
What we are
looking 4
5.
6.
Found 10/10 0 additional
result
7.
100 % Complete 100
% Relevance
8.
Google
9.
10.
11.
12.
Found 9/10 990 additional
result
13.
90 % Complete
1 % Relevance
14.
Database
15.
16.
Found 5/10 90 additional
result
17.
50 % Complete 10
% Relevance
18.
Problem Optimization of the
relationship between Precision and Completeness
19.
An idea
20.
The Ingredients
21.
Tags
22.
23.
social networks
24.
CC-BY DarwinPeacock http://commons.wikimedia.org/wiki/File:Sna_large.png
25.
26.
27.
28.
Social Search
29.
Looking for informations inside
of your network
30.
31.
Found 6/10 10 addition
result
32.
60 % Complete 50
% Relevance
33.
Precision
Recall Google 1Â % 90Â % Database 10Â % 50Â % Social Search 50Â % 60Â %
34.
Social Filters in
practice
35.
4 Solutions âą Tagging âą
Recommender Systems âą Social Search âą Lazyweb
36.
Tagging
37.
delicious
38.
39.
40.
Bibsonomy
41.
42.
Recommender Systems
43.
Users who bought
A bought also B
44.
Mandeley âą Citation Management
Software âą support different Methods of Social Filtering
45.
46.
47.
48.
Social Search
49.
http://www.sharetivity.com/movie.html http://www.sharetivity.com/movie.html
50.
Social Search âą Integration
of your shared sources (facebook, twitter, myspace ... ) âą Integration of resources of your friends âą Whats your friends ïŹnd interesting is higher ranked
51.
Lazyweb
52.
Old Method, new
Tools Ask your friends
53.
On Facebook & Twitter
54.
55.
56.
So Problem solved?
57.
no :-(
58.
new strength
59.
new weaknesses
60.
no answer for
everything
61.
additional strategies
62.
Go social, explore the
potential patrick.danowski@ist.ac.at
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