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The focus on ``feeling'' in design text is a distinctive turn from the prior focus in design research on understanding design text, which has heretofore emphasized semantic meaning. Semantic meaning has been a principle concern of research in understanding design documents . Semantic meaning is the subject matter of design text. Broadly speaking the subject matter of design text is about product, process or people. Ascertaining the subject matter of design text and the purpose of understanding the subject matter has been approached in different ways. For instance, Hill examined design teams' share understanding by adopting latent semantic analysis(LSA), a matrix computational method, to reveal design documents' document similarity. In LSA, documents are represented by a word frequency-document matrix. The semantic meaning of a given word is represented in the matrix by labeling its appearing frequency in the corresponding documents. By applying a series of computations on the matrix, similarity of two documents is measured by the cosine of their document vectors in high-dimension space sense. Dong used the LSA approach to study the cohesiveness of design team communication and mapped the results over time to provide an intuitive way for understanding. Dong explored the relationship between designers' individual mind and design concept formation with the use of a computational linguistic method (lexical chain analysis, LCA). The authors adopted LCA to reveal language's role in forming and representing knowledge in design, examine the grammatical structures associated with representing knowledge and knowledge accumulation. The principle of LCA is revealing nouns/concepts' semantic connections between two utterances within a utterance window. The difference between latent semantic analysis (LSA) and lexical chain analysis (LCA) is the way they express semantic meaning. In latent semantic analysis, semantic meaning is carried in individual words themselves. Semantic meaning is expressed by statistical co-occurrence of word across large body in lexical chain analysis. Segers created WordGraphs to stimulate architects thinking about related concepts using semantically similar words. Initially, the system selected single words as input for two existing words. The system searched the semantic relationship between them and inserted a new word which can connect them to compose WordGraphs. The researchers selected only those WordGraphs which can interest designers for further observation, and found that the designers prefer to use those intermediary words in the following design activities.

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The focus on “feeling" in design text is a distinctive turn from the prior focus in

design research on understanding design text, which has heretofore emphasized semantic

meaning. Semantic meaning is the subject matter of design text. Broadly speaking

the subject matter of design text is about design project (product), design process or

design team (people). Semantic meaning has been a principle concern of research in

understanding design documents. Ascertaining the subject matter of design text

and the purpose of understanding the subject matter has been approached in di®erent

ways.

 

For instance, Segers  created WordGraphs to stimulate architects thinking about

related concepts using semantically similar words. Initially, the system selected single

words as input for two existing words. The system searched the semantic relationship be-

tween them and inserted a new word which can connect them to compose WordGraphs.

The researchers selected only those WordGraphs which can interest designers for fur-

ther observation, and found that the designers prefer to use those intermediary words

in the following design activities. Hill  examined design teams' share understanding

by adopting latent semantic analysis(LSA), a matrix computational method, to reveal

design documents' document similarity. Dong  used the same approach to study the

cohesiveness of design team communication and mapped the results over time to provide

an intuitive way for understanding. Dong  explored the relationship between designers'

individual mind and design concept formation with the use of another computational lin-

guistic method (lexical chain analysis, LCA). Dong  adopted LCA to reveal language's

role in forming and representing knowledge in design, examine the grammatical structures associated with representing knowledge and knowledge accumulation.

 

The difference between latent semantic analysis (LSA) and lexical chain analysis

(LCA) is the way they express semantic meaning. Semantic meaning is carried in in-

dividual words themselves in latent semantic analysis (LSA) while it is expressed by

statistical co-occurrence of words across large body in lexical chain analysis (LCA).

In latent semantic analysis (LSA), documents are represented by a word frequency-

document matrix X with n (rows) words w1;w2; :::wn and m (columns) documents

d1; d2; :::dm . The semantic meaning of a given word is represented in the matrix

by labeling its appearing frequency in the corresponding documents. By applying a se-

ries of computations on the matrix, similarity of two documents is measured by the cosine of their document vectors in high-dimension space sense.

 

Dong  uses the lexical chain analysis (LCA) to reveal nouns or concepts' semantic

connections between two utterances within an utterance window. Semantic connection

(lexical chain) between nouns or concepts is derived from dictionary databases such as

WordNet. The analysis of these lexical chains is applied to examine how designer format

their concept and how they focus on the same topic in their conversations.

 

 

.
The focus on “feeling" in design text is a distinctive turn from the prior focus in design research on understanding design text, which has heretofore emphasized semantic meaning.

Semantic meaning is the subject matter of design text. Broadly speaking, the subject matter of design text is about design project (product), design process or design team (people). Semantic meaning has been a principle concern of research in understanding design documents.

Ascertaining the subject matter of design text and the purpose of understanding the subject matter has been approached in different ways. For instance, Segers created WordGraphs to stimulate architects into thinking about related concepts using semantically similar words. Initially, the system selected single words as input for two existing words. To compose WordGraphs, the system searched the semantic relationships between them and inserted a new word which could connect them. The researchers selected only those WordGraphs which could interest designers for further observation and found that the designers preferred to use those intermediary words in subsequent design activities.

Hill examined a design team's shared understanding by adopting latent semantic analysis (LSA), a matrix computational method, to reveal design document similarity.  In LSA, documents are represented by a word-frequency document matrix X with n (rows) words w1;w2; :::wn and m (columns) documents d1; d2; :::dm. The semantic meaning of a given word is represented in the matrix by labeling its frequency of appearance in the corresponding documents. By applying a series of computations to the matrix, the similarity of two documents is measured by the cosine of their document vectors in high-dimension space sense.

Dong used the same approach to study the cohesiveness of design team communication and mapped the results over time to provide an intuitive way of understanding. Dong explored the relationship between the designer's individual mind and design concept formation with the use of another computational linguistic method, lexical chain analysis or LCA. Dong adapted LCA to reveal the role of language in forming and representing knowledge in design and examine the grammatical structures associated with representing knowledge and knowledge accumulation.

The difference between LSA and LCA is the way in which they express semantic meaning. Semantic meaning is carried in individual words themselves in LSA, while it is expressed by statistical co-occurrence of words across larger bodies in LCA. Dong uses LCA to reveal the semantic connections of nouns or concepts between two utterances within an utterance window. Semantic connection (lexical chains) between nouns or concepts is derived from dictionary databases such as WordNet. The analysis of these lexical chains is applied to examine how designers format their concepts and how they focus on the same topic in their conversations.