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  Partner: UNT College of Engineering
 Collection: UNT Scholarly Works
Subscriber Maximization in CDMA Cellular Networks

Subscriber Maximization in CDMA Cellular Networks

Date: August 2004
Creator: Akl, Robert G.
Description: This paper discusses subscriber maximization in CDMA cellular networks.
Contributing Partner: UNT College of Engineering
An Evaluation Exercise for Romanian Word Sense Disambiguation

An Evaluation Exercise for Romanian Word Sense Disambiguation

Date: July 2004
Creator: Mihalcea, Rada, 1974-; Nastase, Vivi; Chklovski, Timothy A. (Timothy Anatolievich), 1977-; Tatar, Doina; Tufis, Dan & Hristea, Florentina T.
Description: This paper discusses an evaluation exercise for Romanian word sense disambiguation.
Contributing Partner: UNT College of Engineering
Global versus Local Call Admission Control in CDMA Cellular Networks

Global versus Local Call Admission Control in CDMA Cellular Networks

Date: July 2004
Creator: Akl, Robert G. & Parvez, Asad
Description: 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.
Contributing Partner: UNT College of Engineering
Global versus Local Call Admission Control in CDMA Cellular Networks

Global versus Local Call Admission Control in CDMA Cellular Networks

Date: July 2004
Creator: Akl, Robert G. & Parvez, Asad
Description: This paper discusses global versus local call admission control.
Contributing Partner: UNT College of Engineering
Graph-based Ranking Algorithms for Sentence Extraction, Applied to Text Summarization

Graph-based Ranking Algorithms for Sentence Extraction, Applied to Text Summarization

Date: July 2004
Creator: Mihalcea, Rada, 1974-
Description: 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.
Contributing Partner: UNT College of Engineering
Impact of Interference Model on Capacity in CDMA Cellular Networks

Impact of Interference Model on Capacity in CDMA Cellular Networks

Date: July 2004
Creator: Akl, Robert G. & Parvez, Asad
Description: This presentation introduces code division multiple access (CDMA) networks, average and actual interference models, optimized capacity, and the 2D Gaussian user model.
Contributing Partner: UNT College of Engineering
The SENSEVAL-3 English Lexical Sample Task

The SENSEVAL-3 English Lexical Sample Task

Date: July 2004
Creator: Mihalcea, Rada, 1974-; Chklovski, Timothy A. (Timothy Anatolievich), 1977- & Kilgarriff, Adam
Description: Abstract: 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.
Contributing Partner: UNT College of Engineering
The SENSEVAL-3 Multilingual English-Hindi Lexical Sample Task

The SENSEVAL-3 Multilingual English-Hindi Lexical Sample Task

Date: July 2004
Creator: Chklovski, Timothy A. (Timothy Anatolievich), 1977-; Mihalcea, Rada, 1974-; Pedersen, Ted & Purandare, Amruta
Description: This paper describes the English-Hindi Multilingual lexical sample task in SENSEVAL-3.
Contributing Partner: UNT College of Engineering
TextRank: Bringing Order into Texts

TextRank: Bringing Order into Texts

Date: July 2004
Creator: Mihalcea, Rada, 1974- & Tarau, Paul
Description: Abstract: In this paper, we introduce TextRank, a graph-based ranking model for text processing, and show how this model can be successfully used in natural language applications. In particular, we propose two innovative unsupervised methods for keyword and sentence extraction, and show that the results obtained compare favorably with previously published results on established benchmarks.
Contributing Partner: UNT College of Engineering
Co-training and Self-training for Word Sense Disambiguation

Co-training and Self-training for Word Sense Disambiguation

Date: May 2004
Creator: Mihalcea, Rada, 1974-
Description: 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.
Contributing Partner: UNT College of Engineering