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:
{|
|bla
||bla II
|}


#Album
{|
Represents all the albums available
Album
#Artist Contians information about the known artists
|Represents all albums available.
#Track Reference between ''Album'' and ''Artist''
|-Artist||Contians information about the known artists
#Asset ??
|-Track||Reference between ''Album'' and ''Artist''
#Playlist Contains information about the playlists created by the users of the on-line portal
|-Asset||??
#Playlist Item Associative reference between ''Track'' and ''Playlist''
|-Playlist||Contains information about the playlists created by the users of the on-line portal|-
#User Information concerning the users of the on-line portal. Referenced to ''Playlist''
|-Playlist Item||Associative reference between ''Track'' and ''Playlist''|-
#User action Data containing information about the operation a user executes within the on-line portal. Referenced to ''User''
|-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 Datatypes====

Revision as of 20:32, 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.


[Stefan Schnabl, 2005]

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:

  1. The user of MICE has different intentions than the person the data is about
  2. Basket Case Analysis and Cluster Analysis are heavily statistical techniques and quite intense in terms of required knowledge
  3. The questions wanted to be solved will gain on complexity once they are answered (report chain)
  4. The answering will not be a single "result" but a (iterative) process.
  5. Heavy task to realize a graphical abstryact view on the data.
  6. ...


Analysis of the Dataset

The data is organized in several tables which refer to each other by Item Ids. The following tables are available:

bla bla II
Album

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

  1. Extremely business focused.
  2. Extremely technically focused.
  3. Maybe forgetting the users needs to "ffel good".
  4. ...

Known Solutions / Methods (related to the target group)

Intended Purpose

Goals and Objectives

Problems and Tasks to Solve

Example Questions

Proposed Design

Types of Visualization Applied

Visual Mapping

(Datadimension => Attribute)

Description of Used Techniques

Possibilities of Interaction

Mockups / Fake Screenshots

Represents all albums available.