Digital Commons Network^™

A Pilot Study In An Application Of Text Mining To Learning System Evaluation, Nitsawan Katerattanakul

Masters Theses

"Text mining concerns discovering and extracting knowledge from unstructured data. It transforms textual data into a usable, intelligible format that facilitates classifying documents, finding explicit relationships or associations between documents, and clustering documents into categories. Given a collection of survey comments evaluating the civil engineering learning system, text mining technique is applied to discover and extract knowledge from the comments. This research focuses on the study of a systematic way to apply a software tool, SAS Enterprise Miner, to the survey data. The purpose is to categorize the comments into different groups in an attempt to identify "major" concerns from …

Understanding User-Generated Content On Social Media, Bala Meenakshi Nagarajan

Browse all Theses and Dissertations

Over the last few years, there has been a growing public and enterprise fascination with 'social media' and its role in modern society. At the heart of this fascination is the ability for users to participate, collaborate, consume, create and share content via a variety of platforms such as blogs, micro-blogs, email, instant messaging services, social network services, collaborative wikis, social bookmarking sites, and multimedia sharing sites.

This dissertation is devoted to understanding informal user-generated textual content on social media platforms and using the results of the analysis to build Social Intelligence Applications.

The body of research presented in this …

Adaptive Neuro-Fuzzy Inference System To Improve The Power Quality Of Variable-Speed Wind Power Generation System, Yüksel Oğuz, Kami̇l Ri̇fat İrfan Güney

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, an adaptive neuro-fuzzy inference system is designed for output voltage and frequency control of a variable-speed wind power generation system. Variable-speed wind power generation systems (VSWPGS) provide the opportunity to capture more power than fixed speed turbines. On the other hand, the variable-speed wind turbine output can be variable voltage and variable frequency for fluctuating wind speeds. The quality of output power can be improved if adequate controls are incorporated in the system. To bring the output voltage and frequency of system by means of control of blade pitch angle of wind turbine to a desirable value, …

Biomedical Relationship Extraction From Literature Based On Bio-Semantic Token Subsequences, Ying Xie, Jayasimha R. Katukuri, Vijay V. Raghavan

Faculty Articles

Relationship Extraction (RE) from biomedical literature is an important and challenging problem in both text mining and bioinformatics. Although various approaches have been proposed to extract protein?protein interaction types, their accuracy rates leave a large room for further exploring. In this paper, two supervised learning algorithms based on newly defined "bio-semantic token subsequence" are proposed for multi-class biomedical relationship classification. The first approach calculates a "bio-semantic token subsequence kernel", whereas the second one explicitly extracts weighted features from bio-semantic token subsequences. The two proposed approaches outperform several alternatives reported in literature on multi-class protein?protein interaction classification.

E-Carrel: An Environment For Collaborative Textual Scholarship, George K. Thiruvathukal, Steven E. Jones, Peter Shillingsburg

Computer Science: Faculty Publications and Other Works

The E-Carrel project aims to address the preservation of, access to, and re-uses of humanities electronic text files. It enables dynamic, growing resource projects as repositories for new knowledge. It provides for on-line distributed data and tools that are open to new scholarly enhancement through a user friendly tagging tool, sophisticated use of stand-off markup and annotation (leveraging RDF capabilities), and a browsing system anyone can use. It creates a secure system of text preparation and dissemination that encourages collaboration and participation by anyone interested in the texts. To insure the endurance of authenticated texts, multiple copies are distributed on …

Evaluating Models Of Latent Document Semantics In The Presence Of Ocr Errors, Daniel D. Walker, William B. Lund, Eric K. Ringger

Faculty Publications

Models of latent document semantics such as the mixture of multinomials model and Latent Dirichlet Allocation have received substantial attention for their ability to discover topical semantics in large collections of text. In an effort to apply such models to noisy optical character recognition (OCR) text output, we endeavor to understand the effect that character-level noise can have on unsupervised topic modeling. We show the effects both with document-level topic analysis (document clustering) and with word-level topic analysis (LDA) on both synthetic and real-world OCR data. As expected, experimental results show that performance declines as word error rates increase. Common …

Egal: Exploration Guided Active Learning For Tcbr, Rong Hu, Sarah Jane Delany, Brian Mac Namee

Conference papers

The task of building labelled case bases can be approached using active learning (AL), a process which facilitates the labelling of large collections of examples with minimal manual labelling effort. The main challenge in designing AL systems is the development of a selection strategy to choose the most informative examples to manually label. Typical selection strategies use exploitation techniques which attempt to refine uncertain areas of the decision space based on the output of a classifier. Other approaches tend to balance exploitation with exploration, selecting examples from dense and interesting regions of the domain space. In this paper we present …

An Empirically-Based Model For Perspective Selection In Route-Finding Dialogues, Robert J. Ross, Kavita E. Thomas

Conference papers

In this work we aim to computationally model the extent to which certain empirical factors affect spatial perspective selection as used in route-finding dialogues. In such dialogues, both interlocutors need to adopt a spatial perspective in which to describe movement direction. In map-based tasks such as the one we are concerned with, two perspective choices are typically available, i.e., route perspective, where projective terms are defined with respect to the perspective of the route follower themselves, e.g., ``go to your right'', or survey perspective, where projective terms are defined with respect to a global or allocentric perspective, e.g., ``go down'', …

Structure And Content Semantic Similarity Detection Of Extensible Markup Language Documents Using Keys, Waraporn Viyanon

Doctoral Dissertations

"XML (eXtensible Mark-up Language) has become the fundamental standard for efficient data management and exchange. Due to the widespread use of XML for describing and exchanging data on the web, XML-based comparison is central issues in database management and information retrieval. In fact, although many heterogeneous XML sources have similar content, they may be described using different tag names and structures. This work proposes a series of algorithms for detection of structural and content changes among XML data. The first is an algorithm called XDoI (XML Data Integration Based on Content and Structure Similarity Using Keys) that clusters XML documents …

Intelligent Computational Argumentation For Evaluating Performance Scores In Multi-Criteria Decision Making, Rubal Wanchoo

Masters Theses

"Multi Criteria Decision Making (MCDM) is a discipline aimed at assisting multiple stakeholders in contemplating a decision paradigm in an uncertain environment. The decision analysis to be performed involves numerous alternative positions assessed under varied criterion. A performance score is assigned for each alternative in terms of every criterion and it represents satisfaction of the criteria by that alternative. In a collaborative decision making environment, performance scores are either obtained when a consensus can be reached among stakeholders on a particular score or in some cases or controversial when stakeholders do not agree with each other about them. In the …

Contribution-Based Priority Assessment In A Web-Based Intelligent Argumentation Network For Collaborative Software Development, Maithili Satyavolu

Masters Theses

"Decision making is an important aspect of the collaborative software development process which usually involves complex process of conflict resolution. Stakeholders approach decision making process from multiple perspectives and their priorities play a vital role in it. The priority assessment methods used in the argumentation process so far are usually static. Priorities remain constant throughout the decision making process. In order to make the collaborative system more closely replicate real-world scenarios, this work incorporates dynamic priority assessment into a web-based collaborative system which is based on intelligent computational argumentation. It evaluates priorities dynamically for each cycle of decision process based …

Crctol: A Semantic Based Domain Ontology Learning System, Xing Jiang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Domain ontologies play an important role in supporting knowledge‐based applications in the Semantic Web. To facilitate the building of ontologies, text mining techniques have been used to perform ontology learning from texts. However, traditional systems employ shallow natural language processing techniques and focus only on concept and taxonomic relation extraction. In this paper we present a system, known as Concept‐Relation‐Concept Tuple‐based Ontology Learning (CRCTOL), for mining ontologies automatically from domain‐specific documents. Specifically, CRCTOL adopts a full text parsing technique and employs a combination of statistical and lexico‐syntactic methods, including a statistical algorithm that extracts key concepts from a document collection, …

Automatic Readability Assessment, Lijun Feng

Dissertations, Theses, and Capstone Projects

We describe the development of an automatic tool to assess the readability of text documents. Our readability assessment tool predicts elementary school grade levels of texts with high accuracy. The tool is developed using supervised machine learning techniques on text corpora annotated with grade levels and other indicators of reading difficulty. Various independent variables or features are extracted from texts and used for automatic classification. We systematically explore different feature inventories and evaluate the grade-level prediction of the resulting classifiers. Our evaluation comprises well-known features at various linguistic levels from the existing literature, such as those based on language modeling, …

Hybrid Matching And Risk Assessment Of The Misspelled Names Hmra, Cihan Varol

Theses and Dissertations

Companies acquire personal information from phone, World Wide Web, or email in order to sell or send an advertisement about their product. However, when this information is acquired, moved, copied or edited, the data may loose its quality. Often, the use of data administrators or a tool that has limited capabilities to correct the mistyped information can cause many problems. Moreover, most of the correction techniques are particularly implemented for the words used in daily conversations. Since personal names have different characteristics compared to general text, firstly, we proposed a hybrid matching algorithm (PNRS) which employs phonetic encoding, string matching …

Statistical Tools For Linking Engine-Generated Malware To Its Engine, Edna Chelangat Milgo

Theses and Dissertations

Malware-generating engines challenge typical malware analysts by requiring them to quickly extract and upload to their customers' machines, a signature for each of a possibly vast number of never-before-seen malware instances that an engine can generate in a short amount of time In this thesis we propose and evaluate two methods for linking variants of engine-generated malware to its engine. The proposed methods use the w-gram frequency vector (NFV) of the opcode mnemonics of an engine-generated malware in- stance as a feature vector for the instance. An NFV is a tuple that maps «-grams with their frequencies. The in-formation contained …

An Animation Framework For Improving The Comprehension Of Tinyos Programs, Sravanthi Dandamudi

All Theses

To meet the increasing demand for monitoring of the physical world, there has been an increase in the development of wireless sensor network applications. The TinyOS platform has emerged as a de facto standard for developing these applications. The platform offers a number of advantages, with its support for concurrency, power-efficient operation, and resource-constrained hardware chief among them. However, the benefits come at a price. Even without the TinyOS platform, the inherent parallel and distributed nature of these applications makes it difficult for developers to reason about program behavior. Further, the TinyOS programming model adopts
asynchronous, split-phase execution semantics. Developers …

Adaptive Type-2 Fuzzy Maintenance Advisor For Offshore Power Systems, Zhaoxia Wang, C. S. Chang, Fan Yang, W. W. Tan

Research Collection School Of Computing and Information Systems

Proper maintenance strategies are very desirable for minimizing the operational and maintenance costs of power systems without sacrificing reliability. Condition-based maintenance has largely replaced time-based maintenance because of the former's potential economic benefits. As offshore substations are often remotely located, they experience more adverse environments, higher failures, and therefore need more powerful analytical tools than their onshore counterpart. As reliability information collected during operation of an offshore substation can rarely avoid uncertainties, it is essential to obtain consistent estimates of reliability measures under changing environmental and operating conditions. Some attempts with type-1 fuzzy logic were made with limited success in …

A System For Detecting Xml Similarity In Content And Structure Using Relational Database, Waraporn Viyanon, Sanjay Kumar Madria

Computer Science Faculty Research & Creative Works

In this paper, we describe a system incorporating an improved technique that detects the similarity of two XML documents based on content and structure similarity using keys. the technique consists of three major components: A subtree generator and validator, a key generator, and similarity components that compare content and structure of the XML documents. First, an XML document is stored in a relational database and extracted into small subtrees using leaf-node parents. the leaf-node parents are considered as a root of a subtree which is then recursively traversed bottom-up for matching. Second, a possible key(s) is identified in order to …

An Anytime Algorithm For Computing Inconsistency Measurement, Yue Ma, Guilin Qi, Guohui Xiao, Pascal Hitzler, Zuoquan Lin

Computer Science and Engineering Faculty Publications

Measuring inconsistency degrees of inconsistent knowledge bases is an important problem as it provides context information for facilitating inconsistency handling. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. In this paper, we consider the computational aspects of inconsistency degrees of propositional knowledge bases under 4-valued semantics. We first analyze its computational complexity. As it turns out that computing the exact inconsistency degree is intractable, we then propose an anytime algorithm that provides tractable approximation of the inconsistency degree from above and below. We show that …

Udel/Smu At Trec 2009 Entity Track, Wei Zheng, Swapna Gottipati, Jing Jiang, Hui Fang

Research Collection School Of Computing and Information Systems

We report our methods and experiment results from the collaborative participation of the InfoLab group from University of Delaware and the school of Information Systems from Singapore Management University in the TREC 2009 Entity track. Our general goal is to study how we may apply language modeling approaches and natural language processing techniques to the task. Specically, we proposed to find supporting information based on segment retrieval, to extract entities using Stanford NER tagger, and to rank entities based on a previously proposed probabilistic framework for expert finding.

Contribution Based Priority Assessment In A Web-Based Intelligent Argumentation Network For Collaborative Software Development, Xiaoqing Frank Liu, Maithili Satyavolu, Ming-Chuan Leu

Computer Science Faculty Research & Creative Works

Decision making is an important aspect in a collaborative software development process which involves a complex process of conflict resolution. the priority of the participants plays a vital role in conflict resolution as the decision-making process involves many participants from multiple perspectives. the priority assessment methods used in the process so far are usually static in nature, i.e., the priorities of the participants remain constant throughout the decision-making process. in order to make the collaborative system closer to real world scenarios, we incorporate dynamic priority assessment into a web-Based collaborative system based on intelligent computational argumentation, which was developed in …

Semantic Context Transfer Across Heterogeneous Sources For Domain Adaptive Video Search, Yu-Gang Jiang, Chong-Wah Ngo, Shih-Fu Chang

Research Collection School Of Computing and Information Systems

Automatic video search based on semantic concept detectors has recently received significant attention. Since the number of available detectors is much smaller than the size of human vocabulary, one major challenge is to select appropriate detectors to response user queries. In this paper, we propose a novel approach that leverages heterogeneous knowledge sources for domain adaptive video search. First, instead of utilizing WordNet as most existing works, we exploit the context information associated with Flickr images to estimate query-detector similarity. The resulting measurement, named Flickr context similarity (FCS), reflects the co-occurrence statistics of words in image context rather than textual …

Scalable Detection Of Partial Near-Duplicate Videos By Visual-Temporal Consistency, Hung-Khoon Tan, Chong-Wah Ngo, Richang Hong, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Following the exponential growth of social media, there now exist huge repositories of videos online. Among the huge volumes of videos, there exist large numbers of near-duplicate videos. Most existing techniques either focus on the fast retrieval of full copies or near-duplicates, or consider localization in a heuristic manner. This paper considers the scalable detection and localization of partial near-duplicate videos by jointly considering visual similarity and temporal consistency. Temporal constraints are embedded into a network structure as directed edges. Through the structure, partial alignment is novelly converted into a network flow problem where highly efficient solutions exist. To precisely …

Vocate: Auditory Interfaces For The Lok8 Project, John Mcgee, Charlie Cullen

9th. IT & T Conference

The auditory modality has a number of unique advantages over other modalities, such as a fast neural processing rate and focus-independence. As part of the LOK8 project’s aim to develop location-based services, the Vocate module will be seeking to exploit these advantages to augment the overall usability of the LOK8 interface and also to deliver scalable content in scenarios where the user may be in transit or requires focus-independence. This paper discusses these advantages and outlines three possible approaches that the Vocate module may take within the LOK8 project: speech interfaces, auditory user interfaces, and sonification.

A Mobile Multimodal Dialogue System For Location Based Services, Niels Schütte, John D. Kelleher, Brian Macnamee

9th. IT & T Conference

This paper describes ongoing work on the dialogue management components for LOK8, a multimodal dialogue system. We describe our plans for a basic architecture of the system, the rough modules and outline the kinds of models in the project, as well as the next steps in our work.

Vowel Recognition From Articulatory Position Time-Series Data, Jun Wang, Ashok Samal, Jordan R. Green, Tom D. Carrell

School of Computing: Conference and Workshop Papers

A new approach of recognizing vowels from articulatory position time-series data was proposed and tested in this paper. This approach directly mapped articulatory position time-series data to vowels without extracting articulatory features such as mouth opening. The input time-series data were time-normalized and sampled to fixed-width vectors of articulatory positions. Three commonly used classifiers, Neural Network, Support Vector Machine and Decision Tree were used and their performances were compared on the vectors. A single speaker dataset of eight major English vowels acquired using Electromagnetic Articulograph (EMA) AG500 was used. Recognition rate using cross validation ranged from 76.07% to 91.32% for …

Detecting Automotive Exhaust Gas Based On Fuzzy Inference System, Li. Shujin, Ming Bai, Quan Wang, Bo Chen, Xiaobing Zhao, Ting Yang, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

This paper proposes a method of detecting automotive exhaust gas based on fuzzy logic inference after analyzing the principle of the infrared automobile exhaust gas analyzer and the influence of the environmental temperature on analyzer. This paper analyses the measurement error caused by environmental temperature, and then makes a non-linear error correction of temperature for the infrared sensor using fuzzy inference. The results of simulation have clearly demonstrated that the proposed fuzzy compensation scheme is better than the non-fuzzy method.

Using Bpm As An Interoperability Platform, Dennis Taylor, Hisham Assal, Jens G. Pohl

Collaborative Agent Design (CAD) Research Center

Data mediation is an essential component in the Modeling and Simulation field (M&S). Managing multiple data sources and exchanging data among multiple systems requires sophisticated tools and a powerful process management system. Business Process Management (BPM) provides a framework for modeling and managing business activities, both manual and automated, in a consistent manner. Managing automated processes offers an opportunity to integrate external applications into the platform. By integrating automated data transformation tools into the business processes using graphical programming, we provide an approach to achieve operational interoperability among diverse applications without the need for any application to be aware of …

Artificial Intelligence – I: Subjective Decision Making Using Type-2 Fuzzy Logic Advisor, Owais Malik

International Conference on Information and Communication Technologies

In this paper, we present and compare two-stage type-2 fuzzy logic advisor (FLA) for subjective decision making in the domain of students' performance evaluation. We test our proposed model for evaluating students' performance in our computer science and engineering department at HBCC/KFUPM in two domains namely cooperating training and capstone/senior project assessment where we find these FLAs very useful and promising. In our proposed model, the assessment criteria for different components of cooperative training and senior project are transformed into linguistic labels and evaluation information is extracted into the form of IF-THEN rules from the experts. These rules are modeled …

Exploiting Bilingual Information To Improve Web Search, Wei Gao, John Bitzer, Ming Zhou, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Web search quality can vary widely across languages, even for the same information need. We propose to exploit this variation in quality by learning a ranking function on bilingual queries: queries that appear in query logs for two languages but represent equivalent search interests. For a given bilingual query, along with corresponding monolingual query log and monolingual ranking, we generate a ranking on pairs of documents, one from each language. Then we learn a linear ranking function which exploits bilingual features on pairs of documents, as well as standard monolingual features. Finally, we show how to reconstruct monolingual ranking from …