Teaching:TUW - UE InfoVis WS 2005/06 - Gruppe G8 - Aufgabe 3

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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:

- Album Represents all albums available.
- Artist Contains 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

The tables consist of the following Data items:

Album
Field Name Datatype Default value Constraints
artistId String (255 Bytes) [key] NULL
homeClusters String (255 Bytes) NULL
creationDate DateTime NULL
albumId Integer (20 Bytes) 0 not NULL
title String (255 Bytes) [key] NULL
albumId Primary Key
Artist
Field Name Datatype Default value Constraints
creationDate DateTime NULL
defaultAssetId String (255 Bytes) NULL
firstName String (255 Bytes) NULL
artistId Integer (20 Bytes) 0 not NULL
lastName String (255 Bytes) [key] NULL
homeClusters String (255 Bytes) NULL
artistId Primary Key
Track
Field Name Datatype Default value Constraints
artistId Integer (20 Bytes) NULL
creationDate DateTime [key] NULL
trackId Integer (20 Bytes) [key] 0 not NULL
title String (255 Bytes) NULL
ISRC String (255 Bytes) NULL
homeCluster String (255 Bytes) NULL
albumId String (255 Bytes) [key] NULL
trackId Primary Key
Asset
Field Name Datatype Default value Constraints
artistId Integer (20 Bytes) [key] NULL
assetType String (255 Bytes) NULL
creationDate DateTime NULL
assetId Integer (20 Bytes) 0 not NULL
trackId Integer (20 Bytes) [key] NULL
assetId Primary Key
Playlist
Field Name Datatype Default value Constraints
claim String (255 Bytes) NULL
creationDate DateTime NULL
playlistId Integer (20 Bytes) 0 not NULL
playListName String (255 Bytes) NULL
userId Integer (20 Bytes) [key] NULL
playlistId Primary Key
Playlist Item
Field Name Datatype Default value Constraints
trackId Integer (20 Bytes) [key] NULL
playlistId Integer (20 Bytes) [key] NULL
User
Field Name Datatype Default value Constraints
handSetId String (255 Bytes) NULL
userId Integer (20 Bytes) NOT NULL, auto increment
language String (255 Bytes) NULL
lastLoginDate DateTime NULL
registrationDate DateTime NULL
gender char(1) NULL
yearOfBirth Integer (10 Bytes) unsigned NULL
genrePref varchar(250) NULL
favouredArtists text
userId Primary Key
User Action
Field Name Datatype Default value Constraints
context Integer (11 Bytes) -1 NOT NULL
userId Integer (20 Bytes) [key] 0 NOT NULL
productId Integer (20 Bytes) [key] 0 NOT NULL
actionTime TimeStamp [key] 0000-00-00 00:00:00 NOT NULL
action String (20 Bytes) <emtpy> NOT NULL
productType String (20 Bytes) <emtpy> NOT NULL

Description of the Datastructures

[description...]

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