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UNT College of Engineering
Toward Communicating Simple Sentences Using Pictorial Representations
Date: April 2009
Creator: Mihalcea, Rada & Leong, Ben
Description: This paper evaluates the hypothesis that pictorial representations can be used to effectively convey simple sentences across language barriers. Comparative evaluations show that a considerable amount of understanding can be achieved using visual descriptions of information, with evaluation figures within a comparable range of those obtained with linguistic representations produced by an automatic machine translation system.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc31021/
Integrating Knowledge for Subjectivity Sense Labeling
Date: May 2009
Creator: Gyamfi, Yaw; Wiebe, Janyce M.; Mihalcea, Rada, 1974- & Akkaya, Cem
Description: This paper discusses integrating knowledge for subjectivity sense labeling. Abstract: This paper introduces an integrative approach to automatic word sense subjectivity annotation. We use features that exploit the hierarchical structure and domain information in lexical resources such as WordNet, as well as other types of features that measure the similarity of glosses and the overlap among sets of semantically related words. Integrated in a machine learning framework, the entire set of features is found to give better results than any individual type of feature.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc31013/
Maya: A Novel Block Encryption Function
Date: May 2009
Creator: Gomathisankaran, Mahadevan & Lee, Ruby Bei-Loh
Description: This paper discusses a novel block encryption function. Abstract: We propose a novel methodology to design Block Cipher functions. This methodology is illustrated with the design of a specific block cipher function Maya. Our design philosophy is to derive the S-Boxes themselves from the secret key. This makes breaking any round function equivalent to guessing all the key-bits. Advantages of our design include much larger key sizes in relation to the block size, an order of magnitude improvement in the hardware implementation efficiency together with the necessary resistance to cryptanalysis.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc94294/
Topic Identification Using Wikipedia Graph Centrality
Date: May 2009
Creator: Coursey, Kino High & Mihalcea, Rada
Description: 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.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc31020/
Using Encyclopedic Knowledge for Automatic Topic Identification
Date: May 2009
Creator: Coursey, Kino High & Mihalcea, Rada
Description: 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.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc31022/
Tantra: A fast PRNG algorithm and its implementation
Date: June 2009
Creator: Gomathisankaran, Mahadevan & Lee, Ruby B.
Description: This paper discusses Tantra. Tantra is a novel Pseudorandom number generator (PRNG) design that provides a long sequence high quality pseudorandom numbers at very high rate both in software and hardware implementations.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc94290/
Cross-lingual Semantic Relatedness Using Encyclopedic Knowledge
Date: August 2009
Creator: Hassan, Samer & Mihalcea, Rada, 1974-
Description: This paper discusses cross-lingual semantic relatedness using encyclopedic knowledge. Abstract: In this paper, we address the task of cross-lingual semantic relatedness. We introduce a method that relies on the information extracted from Wikipedia, by exploiting the interlanguage links available between Wikipedia versions in multiple languages. Through experiments performed on several language pairs, we show that the method performs well, with a performance comparable to monolingual measures of relatedness.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc31012/
Subjectivity Word Sense Disambiguation
Date: August 2009
Creator: Akkaya, Cem; Wiebe, Janyce & Mihalcea, Rada
Description: This paper investigates a new task, subjectivity word sense disambiguation (SWSD), which is to automatically determine which word instances in a corpus are being used with subjective senses, and which are being used with objective senses. The authors provide empirical evidence that SWSD is more feasible than full word sense disambiguation, and that it can be exploited to improve the performance of contextual subjectivity and sentiment analysis systems.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc31016/
The Effect of an Enhanced Channel Assignment Algorithm on an IEEE 802.11 WLAN
Date: December 2009
Creator: Haidar, Mohamad; Al-Rizzo, Hussain Mudhaffar Younis, 1957-; Akl, Robert G. & El-Bazzal, Zouhair
Description: This article discusses the effect of an enhanced channel assignment algorithm on an IEEE 802.11 WLAN. Abstract: In this paper, a channel-assignment algorithm at the Access Points (APs) of a Wireless Local Area Network (WLAN) is proposed in order to maximize Signal-to-Interference Ratio (SIR) at the user level. We start with an initial channel assignment based on minimizing the total interference between APs. Based on this assignment, we calculate the SIR for each user. Then, another channel assignment is performed based on maximizing the SIR at the users. The algorithm can be applied to any WLAN, irrespective of the users' and load distributions. Simulation results showed that the proposed algorithm is capable of significantly increasing the SIR over the WLAN, which in turn improves throughput. Finally, several scenarios were constructed using OPNET simulation tool to validate our results.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc30846/
Annotating and Identifying Emotions in Text
Date: 2010
Creator: Strapparava, Carlo & Mihalcea, Rada
Description: This book chapter discusses annotating and identifying emotions in text. Abstract: This paper focuses on the classification of emotions and polarity in news headlines and it is meant as an exploration of the connection between emotions and lexical semantics. The authors first describe the construction of the data set used in evaluation exercise "Affective Text" task at SemEval 2007, annotated for six basic emotions: Anger, Disgust, Fear, Joy, Sadness, and Surprise, and for Positive and Negative polarity. The authors also briefly describe the participating systems and their results. Second, exploiting the same data set, the authors propose and evaluate several knowledge-based and corpus-based methods for the automatic identification of emotions in text.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc31010/