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UNT Scholarly Works
- 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. The authors compare a number of knowledge-based and corpus-based measures of text similarity, evaluate the effect of domain and size on the corpus-based measures, and also introduce a novel technique to improve the performance of the system by integrating automatic feedback from the student answers. Overall, our system significantly and consistently outperforms other unsupervised methods for short answer grading that have been proposed in the past. digital.library.unt.edu/ark:/67531/metadc31017/
- 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. In particular, the authors 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. digital.library.unt.edu/ark:/67531/metadc30962/
- Throughput Optimization in Multi-Cell CDMA Networks
- In this paper, the authors investigate the performance of a multi-cell CDMA network by determining the maximum throughput that the network can archive for a given grade-of-service requirement, quality-of-service requirement, network topology and call arrival rate profile. The analysis is restricted to the reverse link and accounts for mobility of users between cell. A constrained nonlinear optimization problem is formulated that maximizes the network throughput subject to upper bounds on the blocking probabilities and a lower bound on the bit energy to interference ratio. The goal is to optimize the usage of network resources, provide consistent grade-of-service for all the cells in the network, and maintain a pre-specified quality-of-service. The solution to the optimization problem yields the maximum network throughput as well as the maximum number of calls that should be admitted in each cell for a given topology and call arrival rate profile. Our optimization algorithm yields significantly higher throughput compared with traditional call admission schemes. digital.library.unt.edu/ark:/67531/metadc30823/
- Throughput Validation of an Advanced Channel Assignment Algorithm in IEEE 802.11 WLAN
- In this article, an enhanced channel-assignment algorithm at the Access Points (APs) of a Wireless Local Area Network (WLAN) is validated. The algorithm aims to maximize the Signal-to-Interference Ratio (SIR) at the user level in order to determine the appropriate channel at the APs. The initial channel assignment step at the APs is based on minimizing the total interference between APs. Based on this initial assignment, the SIR for each user is calculated. 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 user distribution and user load. Results show that the algorithm is capable of significantly increasing the SIR over the WLAN, which in turn should improve throughput. Therefore, the authors use OPNET simulation tool to construct several realistic scenarios in order to validate our results. digital.library.unt.edu/ark:/67531/metadc30850/
- 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/
- Toward Communicating Simple Sentences Using Pictorial Representations
- 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. digital.library.unt.edu/ark:/67531/metadc31021/
- Toward Communicating Simple Sentences Using Pictorial Representations
- 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. digital.library.unt.edu/ark:/67531/metadc30986/
- Transformational Paradigm for Engineering and Engineering Technology Education
- This paper discusses a transformational paradigm for engineering and engineering technology education. The knowledge explosion in science, technology, engineering & mathematics (STEM) over the past decades is unquestionably overwhelming. It is important that those involved in STEM quickly adapt. Life-long learning has taken a do-or-die slant, as technological breakthroughs turn obsolete within only a few years of their inception. Medical and law degree curricula became more "professional" and require a "pre-degree" status to be considered for admission. However, the traditional engineering degree plan is essentially the same as that of the mid 20th Century. Legislation in some states places additional pressure on baccalaureate degrees by questioning the need for anything above 120 credit hours. The result is (i) fewer engineering-specific courses; (ii) courses that heavily emphasize theory; and (iii) a subsequent reduction in hands-on, laboratory oriented, experimental learning. Engineering Technology curricula are designed to have experiential learning as the educational backbone. This forces a reduction in mathematical and scientific depth that is compensated by a richness of laboratory courses in almost one-to-one proportion to lecture courses, and which emphasize the application of engineering. The main challenges to establish and maintain experiential learning include (i) availability of slots in the curricula for laboratory courses; (ii) availability of funding for lab equipment and maintenance; (iii) space constraints exacerbated by the ongoing conversion of education laboratory space to graduate research space; and (iv) availability of dedicated faculty for instruction and preparation of labs that are modern, project-based, inquisitive, and synchronized with the lectures. The authors examine the factors that have prevented Engineering Schools & Colleges in the United States from following the medical or law models and advocate that Engineering Technology programs can play an important role in a new educational paradigm for Engineering Education. The model that the authors propose is based upon the thinking behind the Conceive, Design, Implement, Operate (CDIO™ http://www.cdio.org/) initiative. digital.library.unt.edu/ark:/67531/metadc115194/
- UMTS Capacity and Throughput Maximization for Different Spreading Factors
- This article discusses UMTS capacity and throughput maximization for different spreading factors. An analytical model for calculating capacity in multi-cell UMTS networks is presented. Capacity is maximized for different spreading factors and for perfect and imperfect power control. The authors also design and implement a local call admission control (CAC) algorithm which allows for the simulation of network throughput for different spreading factors and various mobility scenarios. The design of the CAC algorithm uses global information ; it incorporates the call arrival rates and the user mobilities across the network and guarantees the users' quality of service as well as pre-specified blocking probabilities. On the other hand, its implementation in each cell uses local information; it only requires the number of calls currently active in that cell. The capacity and network throughput were determined for signal-to-interference threshold from 5 dB to 10 dB and spreading factor values of 256, 64, 16, and 4. digital.library.unt.edu/ark:/67531/metadc30833/
- 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/
- 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/
- UNT: SubFinder: Combining Knowledge Sources for Automatic Lexical Substitution
- This paper describes the University of North Texas SubFinder system. The system is able to provide the most likely set of substitutes for a word in a given context, by combining several techniques and knowledge sources. SubFinder has successfully participated in the best and out of ten (oot) tracks in the SEMEVAL lexical substitution task, consistently ranking in the first or second place. digital.library.unt.edu/ark:/67531/metadc30997/
- UNT-Yahoo: SuperSenseLearner: Combining SenseLearner with SuperSense and other Coarse Semantic Features
- In this paper, the authors describe the SuperSenseLearner system that participated in the English all-words disambiguation task. The system relies on automatically-learned semantic models using collocational features coupled with features extracted from the annotations of coarse-grained semantic categories generated by an HMM tagger. digital.library.unt.edu/ark:/67531/metadc30998/
- User-Based Channel Assignment Algorithm in a Load-Balanced IEEE 802.11 WLAN
- This article discusses a user-based channel assignment algorithm in a load-balanced IEEE 802.11 WLAN. A new load balancing algorithm is presented based on power management of Access Points (APs) to reduce congestion at hot spots in Wireless Local Area Networks (WLANs) and to assign channels to APs. The algorithm first finds the Most Congested Access Point (MCAP), then decreases its transmitted power in discrete steps, and the process continues until the users' assignment which leads to a high balance index is reached. A new mathematical programming formulation is then applied to assign channels to the APs such that the Signal-to-Interference Ratio (SIR) at the users' level is maximized. Results show that the algorithm is capable of reducing the overall congestion at hot spots in a WLAN and increases the SIR significantly for cases involving relatively large WLANs. In the process, network throughput is increased. digital.library.unt.edu/ark:/67531/metadc30851/
- 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. digital.library.unt.edu/ark:/67531/metadc31022/
- Using the Essence of Texts to Improve Document Classification
- This paper explores the possible benefits of the interaction between automatic extractive summarization and text classification. Through experiments performed on standard test collections, the authors show that techniques for extractive summarization can be effectively combined with classification methods, resulting in improved performance in a text categorization task. Moreover, comparative results suggest that the synergy between text summarization and text classification can be regarded as a new application-oriented evaluation testbed for automatic summarization. digital.library.unt.edu/ark:/67531/metadc30978/
- 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/
- Virtualization Based Secure Execution And Testing Framework
- This article discusses virtualization based secure execution and testing. Computer security aims at protecting confidentiality, integrity, and availability of sensitive information that are processed, used, or stored by computing systems. Computer scientists working in the field of computer security have successfully designed and developed software and hardware mechanisms to provide security in modern day computing devices. As compared to hardware security mechanisms, software-only security mechanisms are easy to implement and patch. But software-only security mechanisms cannot ensure protection against hardware-based attacks, thus rendering them vulnerable to such attacks. Hardware mechanism such as secure architectures aim to root the trust of the security solution in the hardware architecture. These security architectures typically deploy security mechanisms like encryption/decryption to protect confidentiality and hashing to protect data integrity. Though the security provided by hardware secure architectures is reliably high, they require modifications to the processor micro-architecture. Any changes to the micro-architecture is an extremely costly and time consuming process. Also, testing these hardware secure architectures is difficult as it requires testing the complete system including hardware, software and applications. Recently, virtualization has emerged to be an efficient and cost effective technology that allows emulating hardware mechanisms. It also enables emulating new hardware features in a virtualized environment. This makes the task of testing security architectures efficient and easy. In this paper, the authors use a virtualization software to build a Virtualization Based Secure Execution and Testing Framework for testing hardware secure architectures. The authors' framework provides a mechanism to plug-in secure architectures and monitor or test the system behavior by performing attacks on it. digital.library.unt.edu/ark:/67531/metadc94275/
- WARM SRAM: A Novel Scheme to Reduce Static Leakage Energy in SRAM Arrays
- This presentation accompanies a paper discussing research on a novel scheme to reduce static leakage energy in SRAM arrays. The increasing sub-threshold leakage current levels with newer technology nodes have been identified by ITRS (2001) as one of the major fundamental problems faced by the semiconductor industry. Concurrently, the expected performance improvement and functionality integration expectations drive the continued reduction in feature size. This results in ever-increasing power per unit area and the accompanying problem of heat removal and cooling as stated in J.M.C. Stork (1995). Portable battery-powered applications, fuelled by pervasive and embedded computing, have seen tremendous growth and have reached a point where battery energy and power density can't be increased further according to T. Bell (1991). This raises the computational throughput per watt target for the future technology nodes. SRAM arrays which are used widely as a system component, such as caches and register files, in both high-performance and portable systems, are getting to be dominant power consumers because of their large capacity and area. Hence any reduction in cache energy can result in considerable overall power reduction. The authors propose a novel circuit technique using depletion mode devices, to reduce the static energy of SRAM array in an on-chip by 90% without any performance impact. digital.library.unt.edu/ark:/67531/metadc96819/
- 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/
- 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. The paper also shows how the two methods can be combined into a system able to automatically enrich a text with links to encyclopedic knowledge. Given an input document, the system identifies the important concepts in the text and automatically links these concepts to the corresponding Wikipedia pages. Evaluations of the system show that the automatic annotations are reliable and hardly distinguishable from manual annotations. digital.library.unt.edu/ark:/67531/metadc31001/
- 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/
- Word Sense and Subjectivity
- Subjectivity and meaning are both important properties of language. This paper explores their interaction, and brings empirical evidence in support of the hypotheses that (1) subjectivity is a property that can be associated with word senses, and (2) word sense disambiguation can directly benefit from subjectivity annotations. digital.library.unt.edu/ark:/67531/metadc30987/
- Word Sense Disambiguation based on Semantic Density
- This paper presents a Word Sense Disambiguation method based on the idea of semantic density between words. The disambiguation is done in the context of WordNet. The Internet is used as a raw corpora to provide statistical information for word associations. A metric is introduced and used to measure the semantic density and to rank all possible combinations of the senses of two words. This method provides a precision of 58% in indicating the correct sense for both words at the same time. The precision increases as we consider more choices: 70% for top two ranked and 73% for top three ranked. digital.library.unt.edu/ark:/67531/metadc83303/
- Word Sense Disambiguation with Pattern Learning and Automatic Feature Selection
- This paper presents a novel approach for word sense disambiguation. The underlying algorithm has two main components: (1) pattern learning from available sense-tagged corpora (SemCor), from dictionary definitions (WordNet) and from a generated corpus (GenCor), and (2) instance based learning with automatic feature selection, when training data is available for a particular word. The ideas described in this paper were implemented in a system that achieved the best score during the SENSEVAL-2 evaluation exercise, for both English all words and English lexical sample tasks. digital.library.unt.edu/ark:/67531/metadc30945/
- A WordNet-Based Interface to Internet Search Engines
- This paper discusses a WordNet-based interface to Internet search engines. A vast amount of information is available on the Internet, and naturally, many information gathering tools have been developed. Several search engines with different characteristics, such as Alta Vista, Lycos, Infoseek, and others are available. However, the web information retrieval technology is still in its infancy, and there is need for considerable improvement. Some inherent difficulties are: (1) the web information is diverse and highly unstructured, (2) the size of information is large and it grows at an exponential rate, and (3) the current search engine technology is still rudimentary. While the first two issues are more profound and require long term solutions, it may be possible to develop software around the search engines to improve the quality of the information retrieved. In this paper the authors present a natural language interface system to a search engine and discuss some of the results obtained. digital.library.unt.edu/ark:/67531/metadc83305/