TY  - CONF
AU  - Jäschke, Robert
AU  - Rudolph, Sebastian
A2  - Cellier, Peggy
A2  - Distel, Felix
A2  - Ganter, Bernhard
T1  - Attribute Exploration on the Web
T2  - Contributions to the 11th International Conference on Formal Concept Analysis
PB  - 
CY  - 
PY  - 2013/05
M2  - 
VL  - 
IS  - 
SP  - 19
EP  - 34
UR  - http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-113133
M3  - 
KW  - 2013
KW  - acquisition
KW  - analysis
KW  - attribute
KW  - computing
KW  - concept
KW  - crowdsourcing
KW  - data
KW  - exploration
KW  - fca
KW  - formal
KW  - human
KW  - information
KW  - ir
KW  - iteg
KW  - knowledge
KW  - l3s
KW  - linked
KW  - lod
KW  - open
KW  - retrieval
KW  - search
KW  - sparql
KW  - web
L1  - 
SN  - 
N1  - 
N1  - 
AB  - We propose an approach for supporting attribute exploration by web information retrieval, in particular by posing appropriate queries to search engines, crowd sourcing systems, and the linked open data cloud. We discuss underlying general assumptions for this to work and the degree to which these can be taken for granted.
ER  -

TY  - JOUR
AU  - Hereth, Joachim
AU  - Stumme, Gerd
AU  - Wille, Rudolf
AU  - Wille, Uta
T1  - Conceptual Knowledge Discovery - a Human-Centered Approach
JO  - Journal of Applied Artificial Intelligence (AAI)
PY  - 2003/
VL  - 17
IS  - 3
SP  - 281
EP  - 301
UR  - http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hereth2003conceptual.pdf
M3  - 
KW  - 2003
KW  - analysis
KW  - concept
KW  - conceptual
KW  - discovery
KW  - fca
KW  - formal
KW  - human
KW  - kdd
KW  - knowledge
KW  - myown
L1  - 
SN  - 
N1  - Publications of Gerd Stumme
N1  - 
AB  - In this paper we discuss Conceptual Knowledge Discovery in Databases (CKDD) as it is developing in the field of Conceptual Knowledge
<p> Processing. Conceptual Knowledge
<p> Processing is based on the mathematical theory of Formal Concept
<p> Analysis which has become a successful theory for data analysis during
<p> the last two decades. CKDD aims to support a human-centered process
<p>of discovering knowledge from data by visualizing and analyzing
<p>the conceptual structure of the data. We dicuss how the
<p>management system TOSCANA for conceptual information systems
<p>supports CKDD, and illustrate it by two applications in database
<p>marketing and flight movement analysis. Finally, we present a
<p>new tool for conceptual deviation discovery, Chianti.
ER  -