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The semantic gap characterizes the difference between two descriptions of an object by different linguistic representations, for instance languages or symbols. According to Andreas M. Hein, the semantic gap can be defined as "the difference in meaning between constructs formed within different representation systems". [ 1 ]
Semantic intelligence [1] is the ability to gather the necessary information to allow to identify, detect and solve semantic gaps on all level of the organization.. Similar to Operational intelligence or Business Process intelligence, which aims to identify, detect and then optimize business processes, semantic intelligence targets information instead of processes.
The symbol grounding problem is a concept in the fields of artificial intelligence, cognitive science, philosophy of mind, and semantics.It addresses the challenge of connecting symbols, such as words or abstract representations, to the real-world objects or concepts they refer to.
One central question in the economics of corruption asks whether corruption is confined solely to the public sector, or whether it can equally stem from the private sector. [16] What gives rise to this debate is the very definition of ‘corruption’.
STOCKHOLM (Reuters) -Harvard economic historian Claudia Goldin won the 2023 Nobel economics prize for her work exposing the causes of deeply rooted wage and labour market inequality between men ...
The fiscal gap is a measure of a government's total indebtedness proposed by economists Laurence Kotlikoff and Alan Auerbach, who define it as the difference between the present value of all of government's projected financial obligations, including future expenditures, including servicing outstanding official federal debt, and the present value of all projected future tax and other receipts ...
Despite progress made over the years, the gender pay gap still exists across all racial and ethnic groups in the U.S.. According to a new report from the Institute for Women's Policy Research ...
Semantic spaces [note 1] [1] in the natural language domain aim to create representations of natural language that are capable of capturing meaning. The original motivation for semantic spaces stems from two core challenges of natural language: Vocabulary mismatch (the fact that the same meaning can be expressed in many ways) and ambiguity of natural language (the fact that the same term can ...