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Document classification for categorization – Complete Phd and Masters Thesis

Document classification for categorization – Complete Phd and Masters Thesis

[ad_1] Introduction Document classification is the process of categorizing text documents into different predefined classes or categories. It is a fundamental task in information retrieval and natural language processing, with applications in various fields such…

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Document clustering for grouping similar documents – Complete Phd and Masters Thesis

Document clustering for grouping similar documents – Complete Phd and Masters Thesis

[ad_1] Introduction Document clustering is the process of grouping similar documents together based on their content or attributes. This technique is widely used in various applications such as information retrieval, text mining, and document organization.…

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Keyword extraction for document indexing – Complete Phd and Masters Thesis

Keyword extraction for document indexing – Complete Phd and Masters Thesis

[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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Topic modeling for document discovery – Complete Phd and Masters Thesis

Topic modeling for document discovery – Complete Phd and Masters Thesis

[ad_1] Introduction In the era of big data, the need for efficient document discovery tools has become increasingly important. Topic modeling is a powerful technique that allows researchers to automatically discover the underlying themes or…

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Semantic similarity for word relatedness – Complete Phd and Masters Thesis

Semantic similarity for word relatedness – Complete Phd and Masters Thesis

[ad_1] Introduction Semantic similarity is a crucial concept in the field of Natural Language Processing (NLP) that aims to measure the relatedness between words based on their meanings. The ability to accurately determine the semantic…

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Word sense disambiguation for lexical semantics – Complete Phd and Masters Thesis

Word sense disambiguation for lexical semantics – Complete Phd and Masters Thesis

[ad_1] Introduction: Word sense disambiguation (WSD) is a crucial task in the field of lexical semantics, with the objective of determining the correct sense of a word within a given context. The ambiguity of natural…

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Constituency parsing for phrase structure – Complete Phd and Masters Thesis

Constituency parsing for phrase structure – Complete Phd and Masters Thesis

[ad_1] Introduction: Constituency parsing is a fundamental task in natural language processing that involves analyzing the structure of a sentence based on its syntactic constituents. In phrase structure parsing, sentences are parsed based on the…

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Coreference resolution for entity linking – Complete Phd and Masters Thesis

Coreference resolution for entity linking – Complete Phd and Masters Thesis

[ad_1] Introduction Coreference resolution is the task of determining when two or more expressions in a text refer to the same entity. This is a crucial component in natural language processing systems, as it helps…

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Event extraction for situational awareness – Complete Phd and Masters Thesis

Event extraction for situational awareness – Complete Phd and Masters Thesis

[ad_1] Introduction: Event extraction is a crucial aspect of situational awareness, which is the perception of the elements in an environment within a volume of time and space, the comprehension of their meaning, and the…

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Relation extraction for knowledge base population – Complete Phd and Masters Thesis

Relation extraction for knowledge base population – Complete Phd and Masters Thesis

[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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