SPIDA: Abstracting and generalizing layout design cases
Abstraction and generalization of layout design cases generate new knowledge that is more widely applicable to use than specific design cases. The abstraction and generalization of design cases into hierarchical levels of abstractions provide the designer with the flexibility to apply any level of a...
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| Veröffentlicht in: | AI EDAM 1998-04, Vol.12 (2), p.141-159 |
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| container_title | AI EDAM |
| container_volume | 12 |
| creator | MANFAAT, D. DUFFY, A.H.B. LEE, B.S. |
| description | Abstraction and generalization of layout design
cases generate new knowledge that is more widely applicable
to use than specific design cases. The abstraction and
generalization of design cases into hierarchical levels
of abstractions provide the designer with the flexibility
to apply any level of abstract and generalized knowledge
for a new layout design problem. Existing case-based layout
learning (CBLL) systems abstract and generalize cases into
single levels of abstractions, but not into a hierarchy.
In this paper, we propose a new approach, termed customized
viewpoint—spatial (CV–S), which supports
the generalization and abstraction of spatial layouts into
hierarchies along with a supporting system, SPIDA (SPatial
Intelligent Design Assistant). |
| doi_str_mv | 10.1017/S0890060498122060 |
| format | Article |
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cases generate new knowledge that is more widely applicable
to use than specific design cases. The abstraction and
generalization of design cases into hierarchical levels
of abstractions provide the designer with the flexibility
to apply any level of abstract and generalized knowledge
for a new layout design problem. Existing case-based layout
learning (CBLL) systems abstract and generalize cases into
single levels of abstractions, but not into a hierarchy.
In this paper, we propose a new approach, termed customized
viewpoint—spatial (CV–S), which supports
the generalization and abstraction of spatial layouts into
hierarchies along with a supporting system, SPIDA (SPatial
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to use than specific design cases. The abstraction and
generalization of design cases into hierarchical levels
of abstractions provide the designer with the flexibility
to apply any level of abstract and generalized knowledge
for a new layout design problem. Existing case-based layout
learning (CBLL) systems abstract and generalize cases into
single levels of abstractions, but not into a hierarchy.
In this paper, we propose a new approach, termed customized
viewpoint—spatial (CV–S), which supports
the generalization and abstraction of spatial layouts into
hierarchies along with a supporting system, SPIDA (SPatial
Intelligent Design Assistant).</description><subject>Abstraction</subject><subject>Generalization</subject><subject>Machine Learning</subject><subject>Pattern Matching</subject><subject>Spatial Layout Design</subject><issn>0890-0604</issn><issn>1469-1760</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1998</creationdate><recordtype>article</recordtype><recordid>eNp9kDFPwzAQhS0EEqXwA9gysQV8iWPHbFWBUlQJqgIDi3WxnSglTcBOJMqvJ1ErFiRuudPd9-5Jj5BzoJdAQVytaCop5ZTJFKKoHw7ICBiXIQhOD8loOIfD_ZiceL-mfcmEjYhYPc1vJtfBJPOtQ92WdRFgbYLC1tZhVX4Piwq3TdcGxvqyqAON3vpTcpRj5e3Zvo_Jy93t8_Q-XDzO5tPJItSxlG0YMcMSTbVNE2tAQB5bGiFGmUiMTGwqDQADTTNEmnMUYNBGGmIE7MlMxGNysfv74ZrPzvpWbUqvbVVhbZvOq4iLVDLOehB2oHaN987m6sOVG3RbBVQNEak_EfWacKcpfWu_fgXo3hUXsUgUny2VXL69UvHA1aLn470HbjJXmsKqddO5ug_gH5cf2Dx2kg</recordid><startdate>19980401</startdate><enddate>19980401</enddate><creator>MANFAAT, D.</creator><creator>DUFFY, A.H.B.</creator><creator>LEE, B.S.</creator><general>Cambridge University Press</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>19980401</creationdate><title>SPIDA: Abstracting and generalizing layout design cases</title><author>MANFAAT, D. ; DUFFY, A.H.B. ; LEE, B.S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c399t-24d45c0ce85ed171f3e02aa2b75d95e89d1141c0baa0f6a71dae2c13a1a3e0b73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1998</creationdate><topic>Abstraction</topic><topic>Generalization</topic><topic>Machine Learning</topic><topic>Pattern Matching</topic><topic>Spatial Layout Design</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>MANFAAT, D.</creatorcontrib><creatorcontrib>DUFFY, A.H.B.</creatorcontrib><creatorcontrib>LEE, B.S.</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>AI EDAM</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>MANFAAT, D.</au><au>DUFFY, A.H.B.</au><au>LEE, B.S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>SPIDA: Abstracting and generalizing layout design cases</atitle><jtitle>AI EDAM</jtitle><addtitle>AIEDAM</addtitle><date>1998-04-01</date><risdate>1998</risdate><volume>12</volume><issue>2</issue><spage>141</spage><epage>159</epage><pages>141-159</pages><issn>0890-0604</issn><eissn>1469-1760</eissn><abstract>Abstraction and generalization of layout design
cases generate new knowledge that is more widely applicable
to use than specific design cases. The abstraction and
generalization of design cases into hierarchical levels
of abstractions provide the designer with the flexibility
to apply any level of abstract and generalized knowledge
for a new layout design problem. Existing case-based layout
learning (CBLL) systems abstract and generalize cases into
single levels of abstractions, but not into a hierarchy.
In this paper, we propose a new approach, termed customized
viewpoint—spatial (CV–S), which supports
the generalization and abstraction of spatial layouts into
hierarchies along with a supporting system, SPIDA (SPatial
Intelligent Design Assistant).</abstract><pub>Cambridge University Press</pub><doi>10.1017/S0890060498122060</doi><tpages>19</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0890-0604 |
| ispartof | AI EDAM, 1998-04, Vol.12 (2), p.141-159 |
| issn | 0890-0604 1469-1760 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_26789464 |
| source | Cambridge University Press Journals Complete |
| subjects | Abstraction Generalization Machine Learning Pattern Matching Spatial Layout Design |
| title | SPIDA: Abstracting and generalizing layout design cases |
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