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'Semantic fitness' (yogyatā) is an intriguing concept.
To confuse matters further, The Manual of Reason says that the 'guṇa', causal factor responsible for the truth of the testifiee's belief, is 'yathārtha-yogyatā-jñāna', which can mean either (i) veridical cognition of semantic fitness, or (ii) cognition of veridical semantic fitness.
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In effect, they identify 'semantic fitness' with the 'guṇa' or 'causal factor leading to truth', in the language-processing mechanism.
Nyāya isolates four such factors for special attention, namely: spatio-temporal 'contiguity' (sannidhi) of the uttered words; the speaker's intention (tātparya); 'syntactic expectancy' (ākāṅkṣā); and 'semantic fitness' (yogyatā) (cf. TS 67).
The second is a "Fitness-model", which maps solutions in the semantic space to the objective or fitness space.
The simulations were made on ten real data-sets and, even though the studied problem does not belong to the classes of problems for which geometric semantic operators induce a unimodal fitness landscape, the results we present demonstrate the effectiveness of the proposed technique.
In this paper, a new semantic image retrieval method using the analytic hierarchical process is proposed, to provide a new way to incorporate experts' judgment into the system and to evaluate the fitness of a semantic description used to represent an image.
Semantic representations.
Semantic definiteness.
Semantic infiltration indeed.
Is this semantic quibbling?
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