Frame  Finder  Module

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The system will recommend a list of potential themes based on the score ranking. Designers not only can choose the themes recommended by the system but also can input themes they found.

4.2.2. Frame Finder Module

The frame finder module is set for framing and reframing the design challenge. Frames are a response to a problem situation. When facing new design challenge, experienced designers would keep searching for what are the key points that make the problem hard to solve (Dorst, 2011). On the other hand, reframing is to view the situation in a new perspective.

Traditionally, framing and reframing were done by designers with their personal experiences. Accordingly, the frames generated might be subjective to the designers. Besides, this step may be very difficult for novice designers since their experiences are not sufficient.

The frame finder module aims to find and construct frames that are relevant to the themes and objective from the stakeholders’ point of view. We divide the concept of framing into four parts - user perspectives, environments, embodiments and user goals as suggested by Kolko (2011). The supplements of the facilitation are then detailed below.

(1) User perspective

When doing context framing, the first step is to identify the user perspective. Different users may have different concerns. Every frame should clearly describe the user’s persona so that designers can understand each type of user and their thoughts. Further mote, a well-defined user perspective may prompt designers’ empathy to the users which makes the insight closer to the users’ real needs.

For example, think about a design challenge of designing a new type of hotel services and the first task is to refine the experience of using bathroom in hotel. We can use the

‘Desires’ edges, which represent the affective connections between user and their wants (Liu

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and Singh, 2004), in ConceptNet to find prospective users. For example, ‘gym’ is connected with ‘hotel’ through the ‘AtLocation’ edge, and ‘athlete’ is connected with ‘gym’ by the

‘Desires’ relation. As a result, we can infer that athlete may be a potential user of hotel.

Besides, when thinking of athletes, we may also think of children who love sports since they may have similar requirements of hotel facilities. In contrast, we should also take handicapped people who move with difficulties should into consideration when designing services in hotels. By making similarity and contrast associations, designers can discover different types of possible user perspectives. On the other hand, using contiguity associations also helps designers to find more potential user perspectives. For example, when viewing the service from the perspectives of a student, designers may also think about the perspectives of a teacher, a secretary, or a librarian. The system will give a list of recommended potential users through the calculation shown in Figure 4.6.

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User Perspectives Recommendation T: Theme concept nodes

R: Recommend list

E(V1,V2): Edges between V1 and V2 (Direction: V1àV2) FOR EACH T

FOR EACH V ADJACENT TO T IF E(V,T) == ‘Desire’

Push node V into recommend list R ELSE

FOR EACH W ADJACENT TO V IF E(W,V) == ‘Desire’

Push node W into recommend list R END

END END

Figure 4.6 User Perspective Recommendation Algorithm

This module aims to find potentially relative and innovative user perspectives. We temporarily set the finding scope with two degrees of searching on ConceptNet, which we think is suitable for framing and reframing. After our testing, comparing with data beyond three degrees, data within two degrees are comparatively effective to stimulate creativity since these data are somehow conceptually related with the themes yet not too far. Hence, we set the searching scope to two degrees. And the same for the following parts of the frame finder module.

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(2) Environment

Using environment as an aspect to do the reframing facilitates designers to think about different using scenario in different environments. In continuation of the above example of design challenge, to find potential using environments, we search for ‘AtLocation’ and

‘LocatedNear’ edges in ConceptNet, which show the spatial relationship between things and their ordinary locations (Liu and Singh, 2004).

For example, if we are designing the experience of using bathroom in hotel. We can find that ‘bathroom’ is spatially connected to ‘school’, ‘theater’, ‘gym’, ‘plane’, ’library’, etc. with the ‘AtLocation’ edge, which means bathrooms usually can be found in these places. We can think of a lot of places with bathroom like these. It utilizes our abilities of make similarity associations to find potential new environments. Hence, before designing the bathroom in hotel, designers can think about what are the using experiences of bathrooms in these different environments to find some inspirations from them. The system will generate a list of potential using environment to simulate designers’ reframing process.

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Figure 4.7 Environment Recommendation Algorithm

(3) Embodiment

For finding new embodiment, the idea is to find different things for the same goal. The

‘UsedFor’ edges are the source of these knowledge. This type of edges reflects the functional connections for things and their functions, namely, what are the purposes when people use them (Liu and Singh, 2004).

For example, one of the goal of using ‘bathroom’ is ‘relax’ while ‘energetic music’,

‘movie’, ‘party’, ‘vacation’ are also for ‘relax’. Hence, when re-designing the bathroom using experience, designers can add some energetic music or films to build up the relaxing atmosphere. Furthermore, reframing the experience of using bathroom to be an experience

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like having party or having a trip is also a nice inspiration. Designers can make some analogy associations, which we connect the source with the target with similar meaning, to find more possible new embodiments.

Embodiment Recommendation T: Theme concept nodes R: Recommend list

E(V1,V2): Edges between V1 and V2 (Direction: V1àV2) FOR EACH T

FOR EACH V ADJACENT TO T IF E(T,V) == ‘UsedFor’

FOR EACH W ADJACENT TO V IF the E(W,V) == ‘Desire’

Push node W into recommend list R END

END END

Figure 4.8 Embodiment Recommendation Algorithm

(4) User goal

In order to discover insights, identifying the users’ goals is also very important. If the target users are businessmen, knowing what they desire may be important information for the insight. This can be aided by finding the ‘Desires’ relations in the ConceptNet. Since the

‘Desire’ edges are the relations between users and things they desire. Previously we use

‘Desires’ relation only to find out different user perspectives. Here we put more emphasis on

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For example, designers can find that businessmen want a meeting space in the hotel and don’t want the room to be too noisy. Knowing these helps designers to achieve better designs. To discover more user goals, designers may also utilize context associations to reveal the real reason of people’s behavior.

User Goal Recommendation T: Theme concept nodes R: Recommend list

E(V1,V2): Edges between V1 and V2

FOR EACH T

FOR EACH V ADJACENT TO T IF E(T,V) == ‘Desire’

Push node V into recommend list R ELSE

FOR EACH W ADJACENT TO V IF the E(V,W) == ‘Desire’

Push node W into recommend list R END

END END

Figure 4.9 User Goal Recommendation Algorithm