[ad_1] Thesis Overview Title: Partially Observable Markov Decision Processes for Imperfect Information Introduction: Partially Observable Markov decision processes (POMDPs) are a powerful framework for modeling decision-making problems in the presence of uncertainty. In many real-world…
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[ad_1] Introduction Markov decision processes (MDPs) are a powerful framework for modeling sequential decision-making problems in which an agent interacts with a dynamic environment. MDPs have been widely used in a variety of fields, including…
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[ad_1] Introduction: In today’s competitive and volatile business environment, organizations are constantly faced with uncertainty and unpredictable events that can have a significant impact on their operations and outcomes. Planning under uncertainty is a critical…
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[ad_1] Introduction 1.1 Introduction 1.2 Background of Study 1.3 Problem Statement 1.4 Objective of Study 1.5 Limitation of Study 1.6 Scope of Study 1.7 Significance of Study 1.8 Structure of the Thesis 1.9 Definition of…
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[ad_1] Introduction Information extraction is the process of automatically extracting structured knowledge from unstructured or semi-structured sources. It plays a critical role in various fields such as natural language processing, data mining, and knowledge management.…
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[ad_1] Introduction Keyword extraction is a crucial process in document indexing that involves identifying and extracting the most relevant terms from a document to facilitate efficient information retrieval and organization. With the exponential growth of…
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[ad_1] Introduction In recent years, the field of natural language processing (NLP) has seen significant advancements in the use of word embeddings for vector representation. Word embeddings are mathematical representations of words in a continuous…
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[ad_1] Introduction Dependency parsing is a crucial aspect of natural language processing that involves analyzing the grammatical structure of sentences to establish relationships between words. It enables the identification of syntactic dependencies within a sentence,…
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[ad_1] Introduction Semantic Role Labeling (SRL) is a crucial task in natural language processing that involves identifying the semantic roles of words in a sentence and assigning them to their corresponding predicates. The goal of…
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[ad_1] Introduction Relation extraction is a critical task in natural language processing and information extraction that involves identifying and extracting relationships between entities mentioned in text. This process plays a crucial role in knowledge base…
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