Map-based Mobile Services Design,Interacton and Usability Phần 5 doc

7 Personalising Map Feature Content for Mobile Map Users 137

2006) files that have been loaded into an Oracle 9i spatial database (Oracle Spatial,

2006). Using vector data allows the map to be divided into distinct layers, where each

layer can be further decomposed into individual features. The user has the freedom of

browsing mobile maps by executing any of the map actions described in Table 7.1.

Looking at Fig. 7.2 we can see the different components of the MAPPER GUI.

In Fig. 7.2 the user is presented with a map containing different layers where each

layer is categorized as one of the following types:

x Full layer – recommended non-landmark layers and landmark layers. For a land￾mark layer to be displayed as a full layer, all individual features describing the

layer must have a score exceeding the personalisation threshold į.

x Partial layer – recommended landmark layer where only a subset of the individual

features describing the layer have a score exceeding į.

x Empty layer – any layer that is not recommended by the system or any recom￾mended landmark layer where no individual features describing that layer have a

score exceeding į.

Fig. 7.2. MAPPER application GUI4

As is evident from Fig. 7.2, layers that are displayed as partial layers have a second

checkbox beside the layer name in the layers panel. This enables the user to request

further detail describing the layer if desired. This action is recorded in the log files

along with all other map actions and is taken into consideration when updating the

4

Figures 7.2, 7.5, 7.6, and 7.7 are in color. See accompanying CD-ROM for color versions.

138 Joe WEAKLIAM, David WILSON, Michela BERTOLOTTO

user’s profile. If the user wishes to see the names of any features then they simply

place the stylus over that feature and the name is displayed at the bottom of the map.

In addition to those actions outlined in Table 7.1 we have also implemented several

high level spatial queries allowing the user to highlight various aspects of feature con￾tent contained in the map. These queries are classified as strong actions and enable

further detail related to user map feature preferences to be ascertained. These may be

of interest to professionals requiring access to specific aspects of the spatial map data.

7.4.2 Capturing user-map interactions in log files

All user-map interactions are captured in log files in XML. Using XML facilitates fast

parsing of log files and enables specific session information to be extracted from the

files once sessions are terminated. Fig. 7.3 shows an excerpt from a sample log file

describing the detail that is captured at the map layer level when the user manually

zooms in (z03) on a specific region of the map. As the detail displayed in Fig. 7.3 is

captured only at the layer level, no preference information at an individual feature

level, irrespective of whether layers involved in the action are landmark layers or oth￾erwise, can be ascertained through log file analysis.

<useraction>

<mapaction>

<action_id>z03</action_id>

<layer_id>D21</layer_id>

<layer_id>D43</layer_id>

<layer_id>D61</layer_id>

</mapaction>

<frame>

<frame_number>6</frame_number>

<frame_time>1115891528609</frame_time>

<frame_boundary>- 105.0215,39.87568,-

105.0215,39.84096,-104.96144,39.87568,-

104.96144,39.84096</frame_boundary>

<layer_id>D21</layer_id>

<layer_id>D43</layer_id>

<layer_id>D61</layer_id>

</frame>

</useraction>

Fig. 7.3. XML excerpt showing map layer level of detail

Fig. 7.4 shows a second excerpt displaying what is recorded at the feature level

when a user executes a manual zoom in action. For each landmark map layer that ei￾ther intersects or lies wholly inside the selected zoom window, the individual features

of that layer type that are involved in the action are recorded, e.g. D43 represents

schools shown as points on the map. This allows for more detailed analysis of user in￾teractions as content preferences at the individual feature level can be established.

7 Personalising Map Feature Content for Mobile Map Users 139

<useraction>

<mapaction>

<action_id>z03</action_id>

<layer_id>D43</layer_id>

<layer_id>A11</layer_id>

</mapaction>

<frame>

<frame_number>20</frame_number>

<frame_time>1140795217000</frame_time>

<frame_boundary>…</frame_boundary>

<frame_layer>

<layer_id>D43</layer_id>

<feature_id>79</feature_id>

<feature_id>81</feature_id>

</frame_layer>

<frame_layer>

<layer_id>A11</layer_id>

</frame_layer>

</frame>

</useraction>

Fig. 7.4. XML excerpt showing map feature level of detail

Each user-map interaction results in the generation of a map frame that has several

associated attributes, namely a frame time, frame boundary, and frame layers. Interest

map frames are extracted from log files based on time and action criteria where a

frame score is calculated for each interest frame. If the time interval between two con￾secutive map frames exceeds a specified threshold m, then the first frame is deemed to

be an interest frame (m is calculated based on each individual user’s session history).

However, there is also an upper bound on the time interval that elapses between suc￾cessive frames. If the time interval between two consecutive actions exceeds k (60

seconds), then the first frame is not recorded as an interest frame as it is presumed that

the user was interrupted in their current task. At the moment we are working with

fixed thresholds, as the current focus is to determine whether map personalization can

be achieved and if so, does it benefit map users in any way. The next step is to im￾prove the accuracy of the personalization based on each individual MAPPER user,

which may involve the incorporation of thresholds with varying values.

7.4.3 Displaying personalisation at the layer and feature levels

Personalisation is provided at both the layer and feature level. Non-landmark layers

are personalised at the layer level whereas landmark layers can be personalised at the

layer and individual feature level. The following section displays maps that are per￾sonalised based on the profiles of users who have contrasting content preferences.