Teaching:TUW - UE InfoVis WS 2005/06 - Gruppe G8 - Aufgabe 3: Difference between revisions
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The data is organized in several tables which refer to each other by Item Ids. The following tables are available: | The data is organized in several tables which refer to each other by Item Ids. The following tables are available: | ||
#Album Represents all the albums available | #Album | ||
Represents all the albums available | |||
#Artist Contians information about the known artists | #Artist Contians information about the known artists | ||
#Track Reference between ''Album'' and ''Artist'' | #Track Reference between ''Album'' and ''Artist'' | ||
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#Playlist Item Associative reference between ''Track'' and ''Playlist'' | #Playlist Item Associative reference between ''Track'' and ''Playlist'' | ||
#User Information concerning the users of the on-line portal. Referenced to ''Playlist'' | #User Information concerning the users of the on-line portal. Referenced to ''Playlist'' | ||
#User action Data containing information about the operation a user executes within the on-line portal | #User action Data containing information about the operation a user executes within the on-line portal. Referenced to ''User'' | ||
====Description of the Datatypes==== | ====Description of the Datatypes==== |
Revision as of 20:26, 19 November 2005
Topic
On-line Music Portals: Analyzing the Users' Activities
Area of Application
This section describes the application area of
MICE - Music Investigation and Clustering Environment.
Analysis of Application Area
General Description
Shopping analysis, Cluster / Pattern analysis, Web based area of application, all data analysed comes form online users, areas of application include shopping optimazation, web application development, technical optimization. The tool might also be interesting for pure online stores.
Special Issues
We identified the following spots of interest:
- The user of MICE has different intentions than the person the data is about
- Basket Case Analysis and Cluster Analysis are heavily statistical techniques and quite intense in terms of required knowledge
- The questions wanted to be solved will gain on complexity once they are answered (report chain)
- The answering will not be a single "result" but a (iterative) process.
- Heavy task to realize a graphical abstryact view on the data.
- ...
Analysis of the Dataset
The data is organized in several tables which refer to each other by Item Ids. The following tables are available:
- Album
Represents all the albums available
- Artist Contians information about the known artists
- Track Reference between Album and Artist
- Asset ??
- Playlist Contains information about the playlists created by the users of the on-line portal
- Playlist Item Associative reference between Track and Playlist
- User Information concerning the users of the on-line portal. Referenced to Playlist
- User action Data containing information about the operation a user executes within the on-line portal. Referenced to User
Description of the Datatypes
Description of the Datastructures
Target Group
Identifying the Target
The target for the exploration tool are mainly shopping analysts and web developer. It is the aim to suit the needs of persone who run the on-line portal (since they are interested in optimization). On the other hand one must not forget about the technical aspects, abd by that help the developers of such systems.
Special Issues of the Target Group
- Extremely business focused.
- Extremely technically focused.
- Maybe forgetting the users needs to "ffel good".
- ...
Intended Purpose
Goals and Objectives
Problems and Tasks to Solve
Example Questions
Proposed Design
Types of Visualization Applied
Visual Mapping
(Datadimension => Attribute)