Search results
Results from the WOW.Com Content Network
Consequently, any mapping from real world applications into computer applications requires a certain amount of technical background knowledge by the user, where the semantic gap manifests itself. It is a fundamental task of software engineering to close the gap between application specific knowledge and technically doable formalization. For ...
Model diagrams can be more understandable and can allow users to give developers feedback on the appropriate structure of the system. A key goal of the Object-Oriented approach is to decrease the "semantic gap" between the system and the real world by using terminology that is the same as the functions that users perform.
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.
Denotational semantic descriptions can also serve as compositional translations from a programming language into the denotational metalanguage and used as a basis for designing compilers. Operational semantics , [ 7 ] whereby the execution of the language is described directly (rather than by translation).
Before the RISC philosophy became prominent, many computer architects tried to bridge the so-called semantic gap, i.e., to design instruction sets that directly support high-level programming constructs such as procedure calls, loop control, and complex addressing modes, allowing data structure and array accesses to be combined into single instructions.
Knowledge representation makes complex software easier to define and maintain than procedural code and can be used in expert systems. For example, talking to experts in terms of business rules rather than code lessens the semantic gap between users and developers and makes development of complex systems more practical.
Virtual machine monitor usually provides low-level information like raw bytes of the memory. Converting this low-level view into something meaningful for the user is known as the semantic gap problem. Solving this problem requires analysis and understanding of the systems being monitored.
Distributional–relational models were first formalized, [3] [4] as a mechanism to cope with the vocabulary/semantic gap between users and the schema behind the data. In this scenario, distributional semantic relatedness measures, combined with semantic pivoting heuristics can support the approximation between user queries (expressed in their own vocabulary), and data (expressed in the ...