Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 27 for “"Dependency parsing"”.
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Advances in discriminative dependency parsing
… understanding of natural language syntax and parsing is a critical step in producing useful natural language processing systems. In this thesis, we focus on the formalism of dependency grammar as it allows one to model important head modifier relationships with a minimum of extraneous …
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Neural Dependency Parsing of Informal Persian
… the open-source Informal Persian Universal Dependency Treebank (iPerUDT), a new treebank created in this effort, and provide empirical evidence for the need of this treebank that focuses explicitly on informal language. Experimenting with two state-of-the-art parsers, I show that the …
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Typology-aware neural dependency parsing : challenges and directions
… typology in the context of cross-lingual dependency parsing. While this linguistic information has shown great promise in pre-neural parsing, results for neural architectures have been mixed. The aim of the investigation put forth in this thesis is to better understand this …
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Linguistically motivated models for lightly-supervised dependency parsing
Today, the top performing parsing algorithms rely on the availability of annotated data for learning the syntactic structure of a language. Unfortunately, syntactically annotated texts are available only for a handful of languages. The research presented in this thesis aims at developing parsing …
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Models for Improved Tractability and Accuracy in Dependency Parsing
… problems in natural language processing. Dependency parses (directed trees in which edges represent the syntactic relationships between the words in a sentence) have been found to be particularly useful for machine translation, question answering, and other practical applications. For …
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A hitchhiker’s guide to efficient non-projective dependency parsing
Dependency parsing has played a pivotal role in NLP over the last few decades, and non- projective, graph-based dependency parsers have become a dominant approach for this task in the 21st century. While much research has focused on advancing log-linear parameterisations and neural network …
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Does it have to be trees? : Data-driven dependency parsing with incomplete and noisy training data
… present a novel approach to training data-driven dependency parsers on incomplete annotations. Our parsers are simple modifications of two well-known dependency parsers, the transition-based Malt parser and the graph-based MST parser. While previous work on parsing with incomplete data has …
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Efficient Lagrangian relaxation algorithms for exact inference in natural language tasks
… processing including higher-order non-projective dependency parsing, syntactic machine translation, integrated constituency and dependency parsing, and part-of-speech tagging with inter-sentence constraints. For each of these tasks, we show that the Lagrangian relaxation algorithms are often …
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Using Dependency Parses to Augment Feature Construction for Text Mining
… In this dissertation, we evaluate the utility of dependency parses as textual features for different text mining applications. Dependency parsing is one form of syntactic parsing, based on the dependency grammar implicit in sentences. While dependency parsing has traditionally been used for text …
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Transforming dependency parses into ternary expressions for enhanced indexing and matching
Advancements in dependency parsing allow machines to quickly and accurately analyze natural language sentences; however, these parses often require non-trivial manipulation to be useful for many applications. This thesis describes Astroparse, a system for producing ternary expression …
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Clustered Layout Word Cloud for User Generated Online Reviews
… language processing approach, called grammatical dependency parsing, to analyze user generated review content and create a semantic graph. A force-directed graph layout was applied to the graph to create the clustered layout word cloud. We conducted a two-task user study to compare the clustered …
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Computational Framing Analysis: Proposing And Applying an Unsupervised Entity-Centric Semantic Relations Approach
… language processing techniques, including dependency parsing, to extract and analyze entity-centric frames (e.g., shooter, victims, incident). The study outlines the strengths, limitations, and practical applications of SUFA, demonstrating its potential as a scalable and context-aware …
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Lexical syntax for statistical machine translation
… Moreover, we introduce a novel Incremental Dependency-based Syntactic Language Model (IDLM) based on wide-coverage CCG incremental parsing which we integrate into a direct translation SMT system. Our proposed approach is the first to integrate full dependency parsing in SMT systems with a …
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Lagrangian relaxation for natural language decoding
… tasks : (1) examines the classical problem of parsing and part-of-speech tagging; (2) addresses the problem of language model composition in syntactic machine translation; (3) develops efficient algorithms for non-projective dependency parsing. The second set of chapters discuss methods that …
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Argument mining with informal text
… end-to-end approach to argument mining based on dependency parsing. My approach uses new dependency representations for arguments and two new neural dependency parsers, one based on biaffine parsing and the other on GNNs. It comfortably beats a strong baseline on the Quora dataset. When applied …
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Challenges in recommender systems : scalability, privacy, and structured recommendations
… Finally, we develop a tensor factorization for dependency parsing. Instead of manually selecting features, we use tensors to map high-dimensional sparse features into low dimensional (dense) features. Our parser achieves state of the art results across multiple languages.
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News Analytics for Global Infectious Disease Surveillance
… methods such as, topic models, deep learning and dependency parsing can lead to automated generation of the mentioned surveillance tools. Moreover, real-time global availability of these open sources from web-based bio-surveillance systems, such as HealthMap and WHO Disease Outbreak News (DONs) …
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Morphological competence in neural natural language processing
… a task for which this information is key: dependency parsing. To answer this question I propose a new evaluation paradigm which involves evaluating the models on various counterfactual versions of dependency corpora. Through evaluation of Polish, Russian, Finnish and Estonian dependency …
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Towards Knowledge Graph Construction From Unstructured Text with LLMs, Triple Identification and Alignment to Wikidata
… employs traditional NLP tools, such as semantic dependency parsing and SPARQL querying, to extract and align triples with Wikidata entities. Doc-KG includes a predicate mapping mechanism and is evaluated both quantitatively and qualitatively against existing approaches. The advent of LLMs such as …
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Towards Knowledge Graph Construction From Unstructured Text with LLMs, Triple Identification and Alignment to Wikidata
… employs traditional NLP tools, such as semantic dependency parsing and SPARQL querying, to extract and align triples with Wikidata entities. Doc-KG includes a predicate mapping mechanism and is evaluated both quantitatively and qualitatively against existing approaches. The advent of LLMs such as …
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