Paraphrasing, textual entailment, and semantic similarity above word level
It addresses foundational problems in natural language processing for researchers and developers, but appears incremental as it builds on existing work in distributional semantics and paraphrase identification.
This dissertation explores computational methods for analyzing meaning relations like paraphrasing, textual entailment, and semantic similarity at complex linguistic levels, presenting a novel research direction that integrates these areas.
This dissertation explores the linguistic and computational aspects of the meaning relations that can hold between two or more complex linguistic expressions (phrases, clauses, sentences, paragraphs). In particular, it focuses on Paraphrasing, Textual Entailment, Contradiction, and Semantic Similarity. In Part I: "Similarity at the Level of Words and Phrases", I study the Distributional Hypothesis (DH) and explore several different methodologies for quantifying semantic similarity at the levels of words and short phrases. In Part II: "Paraphrase Typology and Paraphrase Identification", I focus on the meaning relation of paraphrasing and the empirical task of automated Paraphrase Identification (PI). In Part III: "Paraphrasing, Textual Entailment, and Semantic Similarity", I present a novel direction in the research on textual meaning relations, resulting from joint research carried out on on paraphrasing, textual entailment, contradiction, and semantic similarity.