[ad_1] Thesis Overview: Aspect-based sentiment analysis has gained significant attention in recent years due to the increasing volume of user-generated content on the internet. This technique allows for the extraction of fine-grained opinions from text…
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[ad_1] Introduction Discourse analysis is a valuable tool in linguistics and communication studies that focuses on understanding how language is used in communication to create coherent and cohesive texts. Coherence refers to the interconnectedness and…
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[ad_1] Introduction Computational linguistics is a field that combines the study of linguistics and computer science to develop algorithms and models for understanding and processing natural language. With the increasing use of computers and digital…
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[ad_1] Introduction: Category theory is a branch of mathematics that is becoming increasingly important in various fields of study, particularly in computer science and physics. It provides a powerful framework for understanding mathematical structures and…
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[ad_1] Introduction: Abstract interpretation is a powerful technique used in the field of program analysis to approximate the behavior of programs. By abstracting the details of a program’s execution, abstract interpretation allows for the efficient…
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[ad_1] Introduction: Symbolic execution is a powerful technique used in program analysis to explore multiple execution paths of a program by representing program inputs symbolically. By treating inputs as symbols, symbolic execution allows for the…
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[ad_1] Introduction Model checking is a formal verification technique that has gained significant popularity in recent years for verifying the correctness of systems. It involves the automatic verification of system properties against a formal model…
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[ad_1] Introduction Formal verification is a crucial process in software development that involves mathematically proving that a software system meets its specifications and requirements. This process helps to ensure that software is correct, reliable, and…
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[ad_1] Introduction Constraint programming is a powerful paradigm for solving complex combinatorial problems by representing problem constraints as logical assertions over variables. This approach is widely used in various fields such as scheduling, planning, resource…
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[ad_1] Introduction Inductive logic programming (ILP) is a subfield of machine learning and artificial intelligence that combines logic programming and traditional machine learning techniques to induce logic programs from data. Rule learning, which involves the…
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