手法を比較

	ソフトシステム方法論（SSM）	Delphi Method	形態素解析
分野	問題構造化	質的手法	テキストマイニング
系統	Process / pipeline	Process / pipeline	Process / pipeline
提唱年	1981	1963	1980
提唱者	Peter Checkland	Norman Dalkey & Olaf Helmer (RAND Corporation)	M.F. Porter (Porter stemmer)
種類	Interpretive problem-structuring methodology	Structured iterative expert-elicitation process	Text-normalisation preprocessing task
原典	Checkland, P. (1981). Systems Thinking, Systems Practice. Wiley. ISBN: 978-0-471-27911-2	Dalkey, N. & Helmer, O. (1963). An Experimental Application of the Delphi Method to the Use of Experts. Management Science, 9(3), 458-467.	Porter, M.F. (1980). An Algorithm for Suffix Stripping. Program, 14(3), 130-137.
別名	SSM, Checkland's SSM, Soft Systems Analysis, Yumuşak Sistemler Metodolojisi	Delphi Yöntemi, Delphi technique, expert consensus method	stemming, lemmatization, Morfolojik Analiz ve Kök Bulma
関連	3	5	4
概要	Soft Systems Methodology (SSM) is an interpretive, action-research approach for structuring and managing complex, ill-defined ('soft') problem situations involving human activity. Developed by Peter Checkland at Lancaster University throughout the 1970s and formally presented in 1981, SSM guides practitioners through iterative cycles of inquiry that move from an unstructured problem situation to purposeful action through structured learning rather than optimization.	The Delphi method is a structured, iterative survey technique developed by Norman Dalkey and Olaf Helmer at the RAND Corporation in 1963 for eliciting and converging expert opinion on complex topics where empirical data are unavailable or insufficient. It collects independent judgements from a geographically dispersed expert panel over multiple anonymous rounds, feeding aggregated results back to participants after each round so they can revise their views in light of the group's collective position.	Morphological analysis splits words into their stems and affixes so that different surface forms of the same word can be treated as one. It covers two complementary approaches — rule-based stemming, such as the Porter (1980) and Snowball algorithms, and dictionary-aware lemmatization — and is a critical text-normalisation step for agglutinative languages such as Turkish and Arabic.