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Weight elicitation methods in multi-criteria decision analysis (MCDA) are often cognitively demanding, require too much precision, time and effort. Some of the issues may be remedied by connecting elicitation methods to an inference engine facilitating a quick and easy method for decision-makers to use weaker input statements, yet being able to utilize these statements in a method for decision evaluation. In this paper, we propose a fast and practically useful weight elicitation method, answering to many of the requirements. The method builds on the ideas of rank-order methods, but can also take imprecise cardinal information into account. The method is subsequently employed in two real-life case studies and compared to a case where a simple ratio weight procedure using exact input statements was employed.
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Stored only when both papers are in the corpus — 41 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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