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  Partner: UNT Libraries
 Degree Discipline: Computer Science
 Collection: UNT Theses and Dissertations
Logic Programming Tools for Dynamic Content Generation and Internet Data Mining

Logic Programming Tools for Dynamic Content Generation and Internet Data Mining

Access: Use of this item is restricted to the UNT Community.
Date: December 2000
Creator: Gupta, Anima
Description: The phenomenal growth of Information Technology requires us to elicit, store and maintain huge volumes of data. Analyzing this data for various purposes is becoming increasingly important. Data mining consists of applying data analysis and discovery algorithms that under acceptable computational efficiency limitations, produce a particular enumeration of patterns over the data. We present two techniques based on using Logic programming tools for data mining. Data mining analyzes data by extracting patterns which describe its structure and discovers co-relations in the form of rules. We distinguish analysis methods as visual and non-visual and present one application of each. We explain that our focus on the field of Logic Programming makes some of the very complex tasks related to Web based data mining and dynamic content generation, simple and easy to implement in a uniform framework.
Contributing Partner: UNT Libraries
Machine Language Techniques for Conversational Agents

Machine Language Techniques for Conversational Agents

Date: December 2003
Creator: Sule, Manisha D.
Description: Machine Learning is the ability of a machine to perform better at a given task, using its previous experience. Various algorithms like decision trees, Bayesian learning, artificial neural networks and instance-based learning algorithms are used widely in machine learning systems. Current applications of machine learning include credit card fraud detection, customer service based on history of purchased products, games and many more. The application of machine learning techniques to natural language processing (NLP) has increased tremendously in recent years. Examples are handwriting recognition and speech recognition. The problem we tackle in this Problem in Lieu of Thesis is applying machine-learning techniques to improve the performance of a conversational agent. The OpenMind repository of common sense, in the form of question-answer pairs is treated as the training data for the machine learning system. WordNet is interfaced with to capture important semantic and syntactic information about the words in the sentences. Further, k-closest neighbors algorithm, an instance based learning algorithm is used to simulate a case based learning system. The resulting system is expected to be able to answer new queries with knowledge gained from the training data it was fed with.
Contributing Partner: UNT Libraries
Measuring Semantic Relatedness Using Salient Encyclopedic Concepts

Measuring Semantic Relatedness Using Salient Encyclopedic Concepts

Date: August 2011
Creator: Hassan, Samer
Description: While pragmatics, through its integration of situational awareness and real world relevant knowledge, offers a high level of analysis that is suitable for real interpretation of natural dialogue, semantics, on the other end, represents a lower yet more tractable and affordable linguistic level of analysis using current technologies. Generally, the understanding of semantic meaning in literature has revolved around the famous quote ``You shall know a word by the company it keeps''. In this thesis we investigate the role of context constituents in decoding the semantic meaning of the engulfing context; specifically we probe the role of salient concepts, defined as content-bearing expressions which afford encyclopedic definitions, as a suitable source of semantic clues to an unambiguous interpretation of context. Furthermore, we integrate this world knowledge in building a new and robust unsupervised semantic model and apply it to entail semantic relatedness between textual pairs, whether they are words, sentences or paragraphs. Moreover, we explore the abstraction of semantics across languages and utilize our findings into building a novel multi-lingual semantic relatedness model exploiting information acquired from various languages. We demonstrate the effectiveness and the superiority of our mono-lingual and multi-lingual models through a comprehensive set of evaluations on specialized ...
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Measuring Vital Signs Using Smart Phones

Measuring Vital Signs Using Smart Phones

Date: December 2010
Creator: Chandrasekaran, Vikram
Description: Smart phones today have become increasingly popular with the general public for its diverse abilities like navigation, social networking, and multimedia facilities to name a few. These phones are equipped with high end processors, high resolution cameras, built-in sensors like accelerometer, orientation-sensor, light-sensor, and much more. According to comScore survey, 25.3% of US adults use smart phones in their daily lives. Motivated by the capability of smart phones and their extensive usage, I focused on utilizing them for bio-medical applications. In this thesis, I present a new application for a smart phone to quantify the vital signs such as heart rate, respiratory rate and blood pressure with the help of its built-in sensors. Using the camera and a microphone, I have shown how the blood pressure and heart rate can be determined for a subject. People sometimes encounter minor situations like fainting or fatal accidents like car crash at unexpected times and places. It would be useful to have a device which can measure all vital signs in such an event. The second part of this thesis demonstrates a new mode of communication for next generation 9-1-1 calls. In this new architecture, the call-taker will be able to control the ...
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A Mechanism for Facilitating Temporal Reasoning in Discrete Event Simulation

A Mechanism for Facilitating Temporal Reasoning in Discrete Event Simulation

Date: May 1992
Creator: Legge, Gaynor W.
Description: This research establishes the feasibility and potential utility of a software mechanism which employs artificial intelligence techniques to enhance the capabilities of standard discrete event simulators. As background, current methods of integrating artificial intelligence with simulation and relevant research are briefly reviewed.
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Mediation on XQuery Views

Mediation on XQuery Views

Date: December 2006
Creator: Peng, Xiaobo
Description: The major goal of information integration is to provide efficient and easy-to-use access to multiple heterogeneous data sources with a single query. At the same time, one of the current trends is to use standard technologies for implementing solutions to complex software problems. In this dissertation, I used XML and XQuery as the standard technologies and have developed an extended projection algorithm to provide a solution to the information integration problem. In order to demonstrate my solution, I implemented a prototype mediation system called Omphalos based on XML related technologies. The dissertation describes the architecture of the system, its metadata, and the process it uses to answer queries. The system uses XQuery expressions (termed metaqueries) to capture complex mappings between global schemas and data source schemas. The system then applies these metaqueries in order to rewrite a user query on a virtual global database (representing the integrated view of the heterogeneous data sources) to a query (termed an outsourced query) on the real data sources. An extended XML document projection algorithm was developed to increase the efficiency of selecting the relevant subset of data from an individual data source to answer the user query. The system applies the projection algorithm ...
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Memory Management and Garbage Collection Algorithms for Java-Based Prolog

Memory Management and Garbage Collection Algorithms for Java-Based Prolog

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Date: August 2001
Creator: Zhou, Qinan
Description: Implementing a Prolog Runtime System in a language like Java which provides its own automatic memory management and safety features such as built--in index checking and array initialization requires a consistent approach to memory management based on a simple ultimate goal: minimizing total memory management time and extra space involved. The total memory management time for Jinni is made up of garbage collection time both for Java and Jinni itself. Extra space is usually requested at Jinni's garbage collection. This goal motivates us to find a simple and practical garbage collection algorithm and implementation for our Prolog engine. In this thesis we survey various algorithms already proposed and offer our own contribution to the study of garbage collection by improvements and optimizations for some classic algorithms. We implemented these algorithms based on the dynamic array algorithm for an all--dynamic Prolog engine (JINNI 2000). The comparisons of our implementations versus the originally proposed algorithm allow us to draw informative conclusions on their theoretical complexity model and their empirical effectiveness.
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A Minimally Supervised Word Sense Disambiguation Algorithm Using Syntactic Dependencies and Semantic Generalizations

A Minimally Supervised Word Sense Disambiguation Algorithm Using Syntactic Dependencies and Semantic Generalizations

Date: December 2005
Creator: Faruque, Md. Ehsanul
Description: Natural language is inherently ambiguous. For example, the word "bank" can mean a financial institution or a river shore. Finding the correct meaning of a word in a particular context is a task known as word sense disambiguation (WSD), which is essential for many natural language processing applications such as machine translation, information retrieval, and others. While most current WSD methods try to disambiguate a small number of words for which enough annotated examples are available, the method proposed in this thesis attempts to address all words in unrestricted text. The method is based on constraints imposed by syntactic dependencies and concept generalizations drawn from an external dictionary. The method was tested on standard benchmarks as used during the SENSEVAL-2 and SENSEVAL-3 WSD international evaluation exercises, and was found to be competitive.
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Mobile agent security through multi-agent cryptographic protocols.

Mobile agent security through multi-agent cryptographic protocols.

Date: May 2004
Creator: Xu, Ke
Description: An increasingly promising and widespread topic of research in distributed computing is the mobile agent paradigm: code travelling and performing computations on remote hosts in an autonomous manner. One of the biggest challenges faced by this new paradigm is security. The issue of protecting sensitive code and data carried by a mobile agent against tampering from a malicious host is particularly hard but important. Based on secure multi-party computation, a recent research direction shows the feasibility of a software-only solution to this problem, which had been deemed impossible by some researchers previously. The best result prior to this dissertation is a single-agent protocol which requires the participation of a trusted third party. Our research employs multi-agent protocols to eliminate the trusted third party, resulting in a protocol with minimum trust assumptions. This dissertation presents one of the first formal definitions of secure mobile agent computation, in which the privacy and integrity of the agent code and data as well as the data provided by the host are all protected. We present secure protocols for mobile agent computation against static, semi-honest or malicious adversaries without relying on any third party or trusting any specific participant in the system. The security of ...
Contributing Partner: UNT Libraries
Modeling Alcohol Consumption Using Blog Data

Modeling Alcohol Consumption Using Blog Data

Date: May 2013
Creator: Koh, Kok Chuan
Description: How do the content and writing style of people who drink alcohol beverages stand out from non-drinkers? How much information can we learn about a person's alcohol consumption behavior by reading text that they have authored? This thesis attempts to extend the methods deployed in authorship attribution and authorship profiling research into the domain of automatically identifying the human action of drinking alcohol beverages. I examine how a psycholinguistics dictionary (the Linguistics Inquiry and Word Count lexicon, developed by James Pennebaker), together with Kenneth Burke's concept of words as symbols of human action, and James Wertsch's concept of mediated action provide a framework for analyzing meaningful data patterns from the content of blogs written by consumers of alcohol beverages. The contributions of this thesis to the research field are twofold. First, I show that it is possible to automatically identify blog posts that have content related to the consumption of alcohol beverages. And second, I provide a framework and tools to model human behavior through text analysis of blog data.
Contributing Partner: UNT Libraries