CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures
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From the viewpoint of content-based retrieval, the researcher analyzes spatial information of a floor plan, with a focus on the apartment unit floor plan common in Korea. Then the metadata items are extracted in a structured manner. To manage the items efficiently, the researcher develops a data model for spatial information according to the concept of the “Structured Floor Plan”. The main object of content to retrieve is a spatial network that consists of nodes of spaces and their linkages. There are two ways to organize the metadata: the traditional index files and the RDF (Resource Description Framework). While the index files are still efficient with computability, the RDF applies greater options to retrieve, such as fuzzy predicates, semantic predicates, and so on. To exploit the metadata, this research shows several possibilities of query operations that present a set of sample queries about L-DK(Living room – Dining room – Kitchen). Implementation of the prototype system is divided into three parts: 1) a modeling module using Vitruvius; 2) an indexing module using MS SQL Server? 2000 in conjunction XML; and 3) a browsing module using the SpaceScope browser.
The future works may consider XML-based databases and a knowledge based query language, such as RQL/XQL, working on such databases. The more specific domain knowledge is involved, the more practical systems would be. Even in architecture, there may be a diverse range of domain knowledge, such as design, building performance, facility management, energy management, post occupied evaluation, historical research, and so on. Also the issue of interface should be investigated in depth, so that it will be adequate to the needs of the architectural field.
Situated Learning in Designing (SLiDe) is developed and implemented within the domain of architectural shape composition (in the form of floor plans), to construct the situatedness of shape semantics. An architectural shape semantic is a set of characteristics with a semantic meaning based on a particular view of a shape such as reflection symmetry, adjacency, rotation and linearity. Each shape semantic has preconditions without which it cannot be recognised. Such preconditions indicate nothing about the situation within which this shape semantic was recognised. The situatedness or the applicability conditions of a shape semantic is viewed as, the interdependent relationships between this shape semantic as the design knowledge in focus, and other shape semantics across the observations of a design composition. While designing, various shape semantics and relationships among them emerge in different representations of a design composition. Multiple representations of a design composition by re-interpretation have been proposed to serve as a platform for SLiDe. Multiple representations provide the opportunity for different shape semantics and relationships among them to be found from a single design composition. This is important if these relationships are to be used later because it is not known in advance which of the possible relationships could be constructed are likely to be useful. Hence, multiple representations provide a platform for different situations to be encountered. A symbolic representation of shape and shape semantics is used in which the infinite maximal lines form the representative primitives of the shape.
SLiDe is concerned with learning the applicability conditions (situatedness), of shape semantics locating them in relation to situations within which they were recognised (situation dependent), and updating the situatedness of shape semantics in response to new observations of the design composition. SLiDe consists of three primary modules: Generator, Recogniser and Incremental Situator. The Generator is used by the designer to develop a set of multiple representations of a design composition. This set of representations forms the initial design environment of SLiDe. The Recogniser detects shape semantics in each representation and produces a set of observations, each of which is comprised of a group of shape semantics recognised at each corresponding representation. The Incremental Situator module consists of two sub-modules, Situator and Restructuring Situator, and utilises an unsupervised incremental clustering mechanism not affected by concept drift. The Situator module locates recognised shape semantics in relation to their situations by finding regularities of relationships among them across observations of a design composition and clustering them into situational categories organised in a hierarchical tree structure. Such relationships change over time due to the changes taken place in the design environment whenever further representations are developed using the Generator module and new observations are constructed by the Recogniser module. The Restructuring Situator module updates previously learned situational categories and restructures the hierarchical tree accordingly in response to new observations.
Learning the situatedness shape semantics may play a crucial role in designing if designers pursue further some of these shape semantics. This thesis illustrates an approach in which SLiDe can be utilised in designing to explore the shapes in a design composition in various ways; bring designers! attention to potentially hidden features and shape semantics of their designs; and maintain the integrity of the design composition by using the situatedness of shape semantics. The thesis concludes by outlining future directions for this research to learn and update the situatedness of design knowledge within the context of use; considering the role of functional knowledge while learning the situatedness of design knowledge; and developing an autonomous situated agent-based designing system.
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