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+ | ======Semantic Network====== | ||
+ | == Introduction == | ||
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+ | (http:// | ||
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+ | //A semantic network is a graphic notation for representing knowledge in patterns of interconnected nodes and arcs. -- Sowa, J. F., Encyclopedia of cognitive science, v.4, 2005, p. 1082// | ||
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+ | //A semantic network is often used as a form of knowledge representation. It is a directed graph consisting of vertices which represent concepts and edges which represent semantic relations between the concepts. -- Wikipedia, 2006// | ||
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+ | **Defination**: | ||
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+ | 語義網路的概念最早在哲學、心理學與語言學中都有涉及,而在當代的計算機研究領域中,被用來發展出人工智慧與自動翻譯技術。在計算機科學中,語義網路被視為一種宣告性的圖示表徵,用以呈現知識或完成自動推論系統。 | ||
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+ | **six kinds of semantic network**: | ||
+ | Sowa 在其為人工智慧與認知科學的語義網路百科辭目中,將語義網路區分為六類: | ||
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+ | - Definitional networks: 定義式網路: | ||
+ | - Assertional networks: 宣稱式網路: | ||
+ | - Implicational networks: 蘊涵(暗示)式網路: | ||
+ | - Executable networks: 實行式網路: | ||
+ | - Learning networks: 學習式網路: | ||
+ | - Hybrid networks: 混合式網路: | ||
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+ | 某些語義網路是依據人類認知機制的假設設計的,某些主要是為了電腦計算機運作效率的目的。有時,計算機科學的推論需求與心理學證據達到相同的結論。 | ||
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+ | == Definational networks 定義式網路 == | ||
+ | * //monotonic logics// 單一邏輯 | ||
+ | * FOL (first-order logic): 一階邏輯/ | ||
+ | * Tree of Porphyry: 由 Porphyry 所繪出的亞里斯多德的知識架構 \\ {{ http:// | ||
+ | * KL-ONE (knowledge language one) \\ {{ http:// | ||
+ | * // | ||
+ | * [[wp> | ||
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+ | == Assertional networks 宣稱式網路 == | ||
+ | * Cottlob Frege (1879) - tree notation for first-order logic \\ {{http:// | ||
+ | * Charles Sanders Peirce (1880, 1885) - | ||
+ | * modern algebraic notation for predicate calculus 述語計算的代數表記系統 | ||
+ | * relational graph | ||
+ | * existential graph (1897) | ||
+ | * Hans Kamp (Kamp and Reyle, 1993) - discourse represtation structure (DRS) | ||
+ | * Linguist Lucien Tesnière (1959) - graph notations for his system of dependency grammar \\ {{http:// | ||
+ | * Roger Schank (1969) - // | ||
+ | * Roger Schank (1982) - larger structure: //scripts// (Schank & Abelson 1977), //memory organization packets (MOPs)//, and //thematic organization packets (TOPs)// (Schank 1982). | ||
+ | * Roger Schank (1994) - // | ||
+ | * MIND system (1971) - the first propositional semantic networks be implemented in AI developed by Stuart Shapiro. | ||
+ | * Semantic Network Processing System (SNePS)(Shapiro 1979; Maida & Shapiro 1982; Shapiro & Rappaport 1992) \\ {{http:// | ||
+ | * Sowa (1984, 2000) - Conceptual graphs \\ {{http:// | ||
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+ | **differencte between those propositional semantic networks: | ||
+ | * Peirce, Sowa, and Kamp used strictily nested propositional enclosures with variables or lines to show coreferences between different enclosures. | ||
+ | * Frege and Shapiro attached the relations to the propositional nodes (or lines in Frege' | ||
+ | * Gary Hendrix (1979)' | ||
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+ | == Implicational Networks 蘊涵式網路 == | ||
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+ | 蘊涵式網路是命題語義網路(propositional semantic network)的一種特殊型式,在蘊涵式網路中,暗示(implication)是概念間主要的關係。其他的關係會包含在命題節點之內,而被不會被推論程序所處理。根據詮釋,此種語義網路也被稱為「信條網路(belief networks)」、「隨意網路(casual networks)」、「貝氏網路(Bayesian networks)」、或「真理維持系統(truth-maintenance systems)」。有時相同的圖型可以與任何或所有的詮釋一起使用。 | ||
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+ | {{ http:// | ||
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+ | * Chuck Rieger (1976) developed a version of //causal networks,// which he used for analyzing problem descriptions in English and translating them to a network that could support metalevel reasoning. | ||
+ | * Benjamin Kuipers (1984, 1994) developed methods of // | ||
+ | * Judea Pearl (1988, 2000)developed techniques for applying statistics and probability to AI, introduced //belief networks,// which are //causal networks// whose links are labeled with probabilities. | ||
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+ | 蘊涵式網路有兩種推論的方法:邏輯與機率。 | ||
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+ | * 邏輯: Methods of logical inference are used in // | ||
+ | * 機率: 真(T)與假(F)可以用機率的1.0與0.0來表達,機率推論認為在計算上有處理在1與0之間更細微複雜情況的需求。Pearl (2000)研究了causal或belief networks中機率的問題 |