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open access

Text Semantic Similarity, with Applications

Description: In this paper, the authors present a knowledge-based method for measuring the semantic-similarity of texts. Through experiments performed on two different applications: (1) paraphrase and entailment identification, and (2) word sense similarity, the authors show that this method outperforms the traditional text similarity metrics based on lexical matching.
Date: September 2005
Creator: Corley, Courtney; Csomai, Andras & Mihalcea, Rada, 1974-
Partner: UNT College of Engineering
open access

Towards a Domain Independent Semantics: Enhancing Semantic Representation with Construction Grammar

Description: This paper shows results from an investigation whether a classifier can be taught to identify these constructions and consideration of the hypothesis that identifying construction types can improve the semantic interpretation of previously unseen predicate uses.
Date: June 2010
Creator: Hwang, Jena D.; Nielsen, Rodney D. & Palmer, Martha
Partner: UNT College of Engineering

Using Query Expansion to Improve Findability of Resources Addressing Multiple Chronic Conditions

Description: With advances in natural language processing (NLP), machine learning (ML) and artificial intelligence (AI), there are new opportunities for improving findability among existing public-facing resources. This project seeks to inform findability, especially for multiple chronic condition (MCC) resources, by describing current search capabilities and limitations across several of AHRQ’s publicly available domains and by identifying and piloting a novel NLP/ML approach to make suggested improvements… more
Date: December 2020
Creator: Marcial, Laura Haak; Santini, Silas; Kery, Caroline; Brown, Stephen; Chew, Rob & Blumenfeld, Barry
Partner: UNT College of Information
open access

Toward Supporting Fine-Grained, Structured, Meaningful and Engaging Feedback in Educational Applications

Description: Recent advancements in machine learning have started to put their mark on educational technology. Technology is evolving fast and, as people adopt it, schools and universities must also keep up (nearly 70% of primary and secondary schools in the UK are now using tablets for various purposes). As these numbers are likely going to follow the same increasing trend, it is imperative for schools to adapt and benefit from the advantages offered by technology: real-time processing of data, availabilit… more
Date: December 2018
Creator: Bulgarov, Florin Adrian
Partner: UNT Libraries

Countering Hate Speech: Modeling User-Generated Web Content Using Natural Language Processing

Description: Social media is considered a particularly conducive arena for hate speech. Counter speech, which is a "direct response that counters hate speech" is a remedy to address hate speech. Unlike content moderation, counter speech does not interfere with the principle of free and open public spaces for debate. This dissertation focuses on the (a) automatic detection and (b) analyses of the effectiveness of counter speech and its fine-grained strategies in user-generated web content. The first goal is … more
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Date: July 2023
Creator: Yu, Xinchen
Partner: UNT Libraries
open access

A Platform for Aligning Academic Assessments to Industry and Federal Job Postings

Description: The proposed tool will provide users with a platform to access a side-by-side comparison of classroom assessment and job posting requirements. Using techniques and methodologies from NLP, machine learning, data analysis, and data mining: the employed algorithm analyzes job postings and classroom assessments, extracts and classifies skill units within, then compares sets of skills from different input volumes. This effectively provides a predicted alignment between academic and career sources, b… more
Date: July 2023
Creator: Parks, Tyler J.
Partner: UNT Libraries
open access

Towards Comprehensive Syntactic and Semantic Annotations of the Clinical Narrative

Description: This article discusses the creation of annotated clinical narratives with layers of syntactic and semantic labels to facilitate advances in clinical natural language processing (NLP).
Date: January 25, 2013
Creator: Albright, Daniel; Lanfranchi, Arrick; Fredriksen, Anwen; Styler, William F., IV; Warner, Colin; Hwang, Jena D. et al.
Partner: UNT College of Engineering
open access

Synthetic data for annotation and extraction of family history information from clinical text

Description: This article investigates the use of synthetic data for the annotation and automated extraction of family history information relating to cases of cardiac disease from Norwegian clinical text. This work assesses the validity and applicability of the annotated synthetic corpus using machine learning techniques. The methodology outlined in this article may be useful in other situations where limited availability of clinical text hinders NLP tasks.
Date: July 14, 2021
Creator: Brekke, Pål H.; Kasicheyanula, Taraka; Pilán, Ildikó; Nytrø, Øystein & Øvrelid, Lilja
Partner: UNT College of Information
open access

Unsupervised Large-Vocabulary Word Sense Disambiguation with Graph-based Algorithms for Sequence Data Labeling

Description: This paper introduces a graph-based algorithm for sequence data labeling, using random walks on graphs encoding label dependencies. The algorithm is illustrated and tested in the context of an unsupervised word sense disambiguation problem, and shown to significantly outperform the accuracy achieved through individual label assignment, as measured on standard sense-annotated data sets.
Date: October 2005
Creator: Mihalcea, Rada, 1974-
Partner: UNT College of Engineering
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