UNT Scholarly Works - 857 Matching Results
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- A Bootstrapping Method for Building Subjectivity Lexicons for Languages with Scarce Resources
- This article discusses a bootstrapping method for building subjectivity lexicons for languages with scarce resources.
- BABYLON Parallel Text Builder: Gathering Parallel Texts for Low-Density Languages
- This paper discusses BABYLON parallel text builder.
- Learning to Identify Emotions in Text
- This paper discusses learning to identify emotions in text.
- An Algorithm for Open Text Semantic Parsing
- This paper describes an algorithm for open text shallow semantic parsing.
- Making Sense Out of the Web
- This paper discusses the main lines of research in deriving efficient Word Sense Disambiguation.
- Putting Pieces Together: Combining FrameNet, VerbNet and WordNet for Robust Semantic Parsing
- This paper describes the authors' work in integrating three different lexical resources: FrameNet, VerbNet, and WordNet, into a unified, richer knowledge-base, to the end of enabling more robust semantic parsing.
- Text Semantic Similarity, with Applications
- 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.
- Topic Identification Using Wikipedia Graph Centrality
- This paper presents a method for automatic topic identification using a graph-centrality algorithm applied to an encyclopedic graph derived from Wikipedia. When tested on a data set with manually assigned topics, the system is found to significantly improve over a simpler baseline that does not make use of the external encyclopedic knowledge.
- Using Encyclopedic Knowledge for Automatic Topic Identification
- This paper presents a method for automatic topic identification using an encyclopedic graph derived from Wikipedia. The system is found to exceed the performance of previously proposed machine learning algorithms for topic identification, with an annotation consistency comparable to human annotations.
- Cell Design to Maximize Capacity in CDMA Networks
- This presentation discusses the code division multiple access (CDMA) inter-cell effects, capacity regions, maximizing network capacity, mobility, a call admission control algorithm, and network performance.
- Toward Communicating Simple Sentences Using Pictorial Representations
- This article discusses communicating simple sentences using pictorial representations.
- Word Sense Disambiguation with Pattern Learning and Automatic Feature Selection
- Article discussing word sense disambiguation with pattern learning and automatic feature selection.
- Parallel Texts
- Article discussing parallel texts and natural language processing.
- Open Text Semantic Parsing Using FrameNet and WordNet
- This article discusses open text semantic parsing using FrameNet and WordNet.
- Using Wikipedia for Automatic Word Sense Disambiguation
- This paper describes a method for generating sense-tagged data using Wikipedia as a source of sense annotations. Through word sense disambiguation experiments, the authors show that the Wikipedia-based sense annotations are reliable and can be used to construct accurate sense classifiers.
- Unsupervised Graph-based Word Sense Disambiguation Using Measures of Word Semantic Similarity
- This paper describes an unsupervised graph-based method for word sense disambiguation, and presents comparative evaluations using several measures of word semantic similarity and several algorithms for graph centrality. The results indicate that the right combination of similarity metrics and graph centrality algorithms can lead to a performance competing with the state-of-the-art in unsupervised word sense disambiguation, as measured on standard data sets.
- Random-Walk Term Weighting for Improved Text Classification
- This paper describes a new approach for estimating term weights in a document, and shows how the new weighting scheme can be used to improve the accuracy of a text classifier.
- Retention and Recruitment of Women in Computer Engineering
- This presentation discusses strategies and goals for recruiting more women to Computer Science and Engineering degree (CSE) programs at the University of North Texas (UNT). It also describes a series of activities aimed at improving retention rates of women students already in our programs. Such recruitment and retention of women is critical to the country's efforts to increase the number of engineering professionals, and is a priority for the CSE Department at UNT.
- Annotating and Identifying Emotions in Text
- This book chapter discusses annotating and identifying emotions in text.
- Technologies That Make You Smile: Adding Humor to Text-Based Applications
- Article discussing technologies that make people smile and adding humor to text-based applications.
- A Language Independent Algorithm for Single and Multiple Document Summarization
- This paper discusses a language independent algorithm for single and multiple document summarization.
- Of Men, Women, and Computers: Data-Driven Gender Modeling for Improved User Interfaces
- This paper discusses data-driven gender modeling for improved user interfaces.
- CDMA Network Design
- This presentation gives an overview of code-division multiple access (CDMA) and inter-cell effects, network capacities, sensitivity analysis of base station locations, pilot-signal power, and transmission power of the mobiles, and concludes with numerical results.
- Capacity Allocations in Multi-cell UMTS Networks for Different Spreading Factors with Perfect and Imperfect Power Control [Presentation]
- This presentation discusses user and interference models, wideband code division multiple access (WCDMA) capacity with perfect and imperfect power control, and spreading factors with numerical results.
- Subscriber Maximization in CDMA Cellular Networks
- This presentation gives an overview of code division multiple access (CDMA), traffic and mobility models, subscriber optimization formulation, and numerical results.
- Multilingual Subjectivity: Are More Languages Better?
- This paper discusses multilingual subjectivity.
- Combining Lexical Resources for Contextual Synonym Expansion
- This paper discusses combining lexical resources for contextual synonym expansion.
- Linking Educational Materials to Encyclopedic Knowledge
- This paper discusses linking educational materials to encyclopedic knowledge.
- Explorations in Automatic Book Summarization
- This paper discusses explorations in automatic book summarization.
- Making Computers Laugh: Investigations in Automatic Humor Recognition
- This paper discusses investigations in automatic humor recognition.
- Unsupervised Large-Vocabulary Word Sense Disambiguation with Graph-based Algorithms for Sequence Data Labeling
- 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.
- Text Mining for Automatic Image Tagging
- This paper introduces several extractive approaches for automatic image tagging, relying exclusively on information mined from texts. Through evaluations on two datasets, the authors show that their methods exceed competitive baselines by a large margin, and compare favorably with the state-of-the-art that uses both textual and image features.
- An Evaluation Exercise for Romanian Word Sense Disambiguation
- This paper discusses an evaluation exercise for Romanian word sense disambiguation.
- Exploiting Agreement and Disagreement of Human Annotators for Word Sense Disambiguation
- This paper discusses word sense disambiguation.
- PageRank on Semantic Networks, with Application to Word Sense Disambiguation
- This article discusses PageRank on semantic networks, with application to word sense disambiguation.
- Amazon Mechanical Turk for Subjectivity Word Sense Disambiguation
- In this paper, the authors discuss research on whether they can use Mechanical Turk (MTurk) to acquire good annotations with respect to gold-standard data, whether they can filter out low-quality workers (spammers), and whether there is a learning effect associated with repeatedly completing the same kind of task.
- Automatic Keyword Extraction for Learning Object Repositories
- This article discusses automatic keyword extraction for learning object repositories.
- Quantifying the Limits and Success of Extractive Summarization Systems Across Domains
- This paper analyzes the topic identification stage of single-document automatic text summarization across four different domains, consisting of newswire, literary, scientific and legal documents.
- Word Alignment for Languages with Scarce Resources
- This paper presents the task definition, resources, participating systems, and comparative results for the shared task on word alignment which was organized as part of the Association for Computational Linguistics (ACL) 2005 Workshop on Building and Using Parallel Texts. The shared task included English-Inuktitut, Romanian-English, and English-Hindi sub-tasks, and drew the participation of ten teams from around the world with a total of 50 systems.
- Linguistically Motivated Features for Enhanced Back-of-the-Book Indexing
- This paper discusses linguistically motivated features for enhanced back-of-the-book indexing.
- The SENSEVAL-3 English Lexical Sample Task
- This paper presents the task definition, resources, participating systems, and comparative results for the English lexical sample task, which was organized as part of the SENSEVAL-3 evaluation exercise.
- The SENSEVAL-3 Multilingual English-Hindi Lexical Sample Task
- This paper describes the English-Hindi Multilingual lexical sample task in SENSEVAL-3.
- SenseLearner: Minimally Supervised Word Sense Disambiguation for All Words in Open Text
- This paper introduces SenseLearner - a minimally supervised sense tagger that attempts to disambiguate all content words in a text using the sense from WordNet. SenseLearner participated in the SENSEVAL-3 English all words task, and achieved an average accuracy of 64.6%.
- Measuring the Semantic Similarity of Texts
- This paper discusses measuring the semantic similarity of texts.
- SemEval-2010 Task 2: Cross-Lingual Lexical Substitution
- This article describes the SemEval-2010 Cross-Lingual Lexical Substitution task.
- Integrating Knowledge for Subjectivity Sense Labeling
- This paper discusses integrating knowledge for subjectivity sense labeling.
- Semantic Document Engineering with WordNet and PageRank
- This article discusses semantic document engineering with WordNet and PageRank.
- An Evaluation Exercise for Word Alignment
- This paper discusses an evaluation exercise for word alignment.
- Wikify! Linking Documents to Encyclopedic Knowledge
- This paper introduces the use of Wikipedia as a resource for automatic keyword extraction and word sense disambiguation, and shows how this online encyclopedia can be used to achieve state-of-the-art results on both these tasks.
- Networks and Natural Language Processing
- Article discussing networks and natural language processing. The authors present some of the most successful graph-based representations and algorithms used in language processing and try to explain how and why they work.