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  Partner: UNT College of Engineering
 Collection: UNT Scholarly Works
Non-Uniform Grid-Based Routing in Sensor Networks
This paper discusses non-uniform grid-based routing in sensor networks. digital.library.unt.edu/ark:/67531/metadc30847/
Simulation of Throughput in UMTS Networks with Different Spreading Factors
In this paper, the authors design and implement a local session admission control (SAC) algorithm for third-generation wireless networks which allows for the simulation of network throughput for different spreading factors and various mobility scenarios. digital.library.unt.edu/ark:/67531/metadc30832/
Channel Assignment and Load Distribution in a Power-Managed WLAN
This paper discusses a proposed algorithm. digital.library.unt.edu/ark:/67531/metadc30835/
Channel Assignment in an IEEE 802.11 WLAN Based on Signal-to-Interference Ratio
This article discusses channel assignment in an IEEE 802.11 WLAN based on signal-to-interference ratio. digital.library.unt.edu/ark:/67531/metadc30844/
Classification of Attributes and Behavior in Risk Management Using Bayesian Networks
This paper discusses issues in security. digital.library.unt.edu/ark:/67531/metadc30836/
Capacity Allocations in Multi-cell UMTS Networks for Different Spreading Factors with Perfect and Imperfect Power Control
This paper discusses capacity allocation in multi-cell UMTS networks. digital.library.unt.edu/ark:/67531/metadc30825/
Global versus Local Call Admission Control in CDMA Cellular Networks
This paper discusses global versus local call admission control. digital.library.unt.edu/ark:/67531/metadc30816/
Impact of Interference Model on Capacity in CDMA Cellular Networks
This paper discusses an impact of interference model on capacity in CDMA cellular networks. digital.library.unt.edu/ark:/67531/metadc30817/
Multicell CDMA Network Design
This article discusses multicell CDMA network design. digital.library.unt.edu/ark:/67531/metadc30815/
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 goo 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. digital.library.unt.edu/ark:/67531/metadc31023/
The Decomposition of Human-Written Book Summaries
In this paper, the authors evaluate the extent to which human-written book summaries can be obtained through cut-and-paste operations from the original book. The authors analyze the effect of the parameters involved in the decomposition algorithm, and highlight the distinctions in coverage obtained for different summary types. digital.library.unt.edu/ark:/67531/metadc31018/
Co-training and Self-training for Word Sense Disambiguation
This paper investigates the application of co-training and self-training to word sense disambiguation. Optimal and empirical parameter selection methods for co-training and self-training are investigated, with various degrees of error reduction. A new method that combines co-training with majority voting is introduced, with the effect of smoothing the bootstrapping learning curves, and improving the average performance. digital.library.unt.edu/ark:/67531/metadc30955/
Characterizing Humour: An Exploration of Features in Humorous Texts
This paper investigates the problem of automatic humor recognition, and provides an in-depth analysis of two of the most frequently observed features of humorous text: human-centeredness and negative polarity. Through experiments performed on two collections of humorous texts, the authors show that these properties of verbal humor are consisted across different data sets. digital.library.unt.edu/ark:/67531/metadc30988/
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. digital.library.unt.edu/ark:/67531/metadc30938/
Research, Teaching, and Outreach
This presentation discusses research in sensor network routing, WiFi network optimization, 3G cellular call admission, and the outreach and resources needed. digital.library.unt.edu/ark:/67531/metadc30934/
Robocamp: Encouraging Young Women to Embrace STEM
This presentation discusses Robocamp, a special summer camp that was created by the University of North Texas (UNT) Computer Science and Engineering department. Robocamp successfully promotes engineering among high school women. digital.library.unt.edu/ark:/67531/metadc30941/
WiFi and WCDMA Network Design
This presentation discusses WiFi access point selection and traffic balancing, multi-cell wideband code division multiple access (WCDMA) with multiple classes, user modeling using 2D Gaussian distribution, and intra-cell and inter-cell interference and capacity. digital.library.unt.edu/ark:/67531/metadc30935/
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. digital.library.unt.edu/ark:/67531/metadc30929/
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. digital.library.unt.edu/ark:/67531/metadc30928/
Capacity Allocations in Multi-cell UMTS Networks for Different Spreading Factors with Perfect and Imperfect Power Control
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. digital.library.unt.edu/ark:/67531/metadc30937/
Global versus Local Call Admission Control in CDMA Cellular Networks
This presentation discusses interference model impacts on capacity, global call admission controls, local call admission controls, and the differences in global versus local call admission controls. digital.library.unt.edu/ark:/67531/metadc30931/
Impact of Interference Model on Capacity in CDMA Cellular Networks
This presentation introduces code division multiple access (CDMA) networks, average and actual interference models, optimized capacity, and the 2D Gaussian user model. digital.library.unt.edu/ark:/67531/metadc30932/
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. digital.library.unt.edu/ark:/67531/metadc30933/
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. digital.library.unt.edu/ark:/67531/metadc30979/
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. digital.library.unt.edu/ark:/67531/metadc31020/
Current Research in Wireless at UNT
This presentation discusses wireless networks, access point selections, traffic balancing, multi-cell CDMA, user distribution modeling, and call admission control. digital.library.unt.edu/ark:/67531/metadc30930/
Graph-based Ranking Algorithms for Sentence Extraction, Applied to Text Summarization
Abstract: This paper presents an innovative unsupervised method for automatic sentence extraction using graph-based ranking algorithms. We evaluate the method in the context of a text summarization task, and show that the results obtained compare favorably with previously published results on established benchmarks. digital.library.unt.edu/ark:/67531/metadc30957/
Finding Semantic Associations on Express Lane
This paper introduces a new codification scheme for efficient computation of measures in semantic networks. The scheme is particularly useful for fast computation of semantic associations between words and implementation of an informational retrieval operator for efficient search in semantic spaces. Other applications may also be possible. digital.library.unt.edu/ark:/67531/metadc30956/
Energy-Aware Routing and Hybrid Synchronization in Sensor Networks
This presentation discusses the research of sensor synchronization, sensor grid routing, and voice over internet protocol (VoIP). digital.library.unt.edu/ark:/67531/metadc30939/
Self-Configuring Wireless MEMS Network
This presentation discusses miniature, lightweight, self-powered wireless sensors, and networking software needs. digital.library.unt.edu/ark:/67531/metadc30940/
[Review] The Text Mining Handbook: Advanced Approaches to Analyzing Unstructured Data
This book review discusses 'The Text Mining Handbook: Advanced Approaches to Analyzing Unstructured Data' by Ronen Feldman and James Sanger. The book is an introduction to text mining, covering the general architecture of text mining systems, along with the main techniques used by such systems. digital.library.unt.edu/ark:/67531/metadc31009/
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. digital.library.unt.edu/ark:/67531/metadc30999/
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. digital.library.unt.edu/ark:/67531/metadc30976/
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. digital.library.unt.edu/ark:/67531/metadc31000/
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. digital.library.unt.edu/ark:/67531/metadc31028/
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. digital.library.unt.edu/ark:/67531/metadc30977/
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. digital.library.unt.edu/ark:/67531/metadc30985/
Word Sense Disambiguation with Pattern Learning and Automatic Feature Selection
Article discussing word sense disambiguation with pattern learning and automatic feature selection. digital.library.unt.edu/ark:/67531/metadc30945/
An Algorithm for Open Text Semantic Parsing
This paper describes an algorithm for open text shallow semantic parsing. digital.library.unt.edu/ark:/67531/metadc30953/
Computational Models for Incongruity Detection in Humour
In this paper, the authors explore several computational models for incongruity resolution. digital.library.unt.edu/ark:/67531/metadc31024/
The Multidisciplinary Facets of Research on Humour
In this paper, the authors summarize the main theories of humor that emerged from philosophical and modern psychological research, and survey the past and present developments in the fields of theoretical and computational linguistics. digital.library.unt.edu/ark:/67531/metadc30996/
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. digital.library.unt.edu/ark:/67531/metadc30994/
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. digital.library.unt.edu/ark:/67531/metadc31026/
PicNet: Augmenting Semantic Resources with Pictorial Representations
In this paper, the authors introduce PicNet, a Web-based system for augmenting semantic resources with illustrative images using volunteer contributions over the Web. digital.library.unt.edu/ark:/67531/metadc30972/
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. digital.library.unt.edu/ark:/67531/metadc30973/
Text-to-text Semantic Similarity for Automatic Short Answer Grading
In this paper, the authors explore unsupervised techniques for the task of automatic short answer grading. digital.library.unt.edu/ark:/67531/metadc31017/
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. digital.library.unt.edu/ark:/67531/metadc30963/
SemEval-2007 Task 14: Affective Text
The "Affective Text" task focuses on the classification of emotions and valence (positive/negative polarity) in news headlines, and is meant as an exploration of the connection between emotions and lexical semantics. In this paper, the authors describe the data set used in the evaluation and the results obtained by the participating systems. digital.library.unt.edu/ark:/67531/metadc30995/
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. digital.library.unt.edu/ark:/67531/metadc31001/
TextRank: Bringing Order into Texts
In this paper, the authors introduce TextRank, a graph-based ranking model for text processing, and show how this model can be successfully used in natural language applications. digital.library.unt.edu/ark:/67531/metadc30962/