Databases and Information Systems Commons^™

An Investigation Into A Hybrid Genetic Programming And Ant Colony Optimization Method For Credit Scoring, Rojin Aliehyaei

Theses and Dissertations

This thesis proposes and investigates a new hybrid technique based on Genetic Programming (GP) and Ant Colony Optimization (ACO) techniques for inducing data classification rules. The proposed hybrid approach aims to improve on the accuracy of data classification rules produced by the original GP technique, which uses randomly generated initial populations. This hybrid technique relies on the ACO technique to produce the initial populations for the GP technique. To evaluate and compare their effectiveness in producing good data classification rules, GP, ACO, and hybrid techniques were implemented in the C programming language. The data classification rules were created and evaluated …

Self‐Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Yuan-Sin Tan

Research Collection School Of Computing and Information Systems

The basic tenet of a learning process is for an agent to learn for only as much and as long as it is necessary. With reinforcement learning, the learning process is divided between exploration and exploitation. Given the complexity of the problem domain and the randomness of the learning process, the exact duration of the reinforcement learning process can never be known with certainty. Using an inaccurate number of training iterations leads either to the non-convergence or the over-training of the learning agent. This work addresses such issues by proposing a technique to self-regulate the exploration rate and training duration …

Predictive Modeling For Navigating Social Media, Meiqun Hu

Dissertations and Theses Collection (Open Access)

Social media changes the way people use the Web. It has transformed ordinary Web users from information consumers to content contributors. One popular form of content contribution is social tagging, in which users assign tags to Web resources. By the collective efforts of the social tagging community, a new information space has been created for information navigation. Navigation allows serendipitous discovery of information by examining the information objects linked to one another in the social tagging space. In this dissertation, we study prediction tasks that facilitate navigation in social tagging systems. For social tagging systems to meet complex navigation needs …

Topic Based Query Suggestions For Video Search, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia

Research Collection School Of Computing and Information Systems

Query suggestion is an assistive technology mechanism commonly used in search engines to enable a user to formulate their search queries by predicting or completing the next few query words that the user is likely to type. In most implementations, the suggestions are mined from query log and use some simple measure of query similarity such as query frequency or lexicographical matching. In this paper, we propose an alternative method of presenting query suggestions by their thematic topics. Our method adopts a document-centric approach to mine topics in the corpus, and does not require the availability of a query log. …

Evaluating The Use Of A Mobile Annotation System For Geography Education, Dion Hoe-Lian Goh, Khasfariyati Razikin, Chei Sian Lee, Ee Peng Lim, Kalyani Chatterjea, Chew-Hung Chang

Research Collection School Of Computing and Information Systems

Mobile devices used in educational settings are usually employed within a collaborative learning activity in which learning takes place in the form of social interactions between team members while performing a shared task. The authors aim to introduce MobiTOP (Mobile Tagging of Objects and People), a mobile annotation system that allows users to contribute and share geospatial multimedia annotations via mobile devices. Field observations and interviews were conducted. A group of trainee teachers involved in a geography field study were instructed to identify rock formations by collaborating with each other using the MobiTOP system. The trainee teachers who were in …

Who Is Retweeting The Tweeters? Modeling, Originating, And Promoting Behaviors In The Twitter Network, Achananuparp Palakorn, Ee Peng Lim, Jing Jiang, Tuan Anh Hoang

Research Collection School Of Computing and Information Systems

Real-time microblogging systems such as Twitter offer users an easy and lightweight means to exchange information. Instead of writing formal and lengthy messages, microbloggers prefer to frequently broadcast several short messages to be read by other users. Only when messages are interesting, are they propagated further by the readers. In this article, we examine user behavior relevant to information propagation through microblogging. We specifically use retweeting activities among Twitter users to define and model originating and promoting behavior. We propose a basic model for measuring the two behaviors, a mutual dependency model, which considers the mutual relationships between the two …

Structural Analysis In Multi-Relational Social Networks, Bingtian Dai, Freddy Chua, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Modern social networks often consist of multiple relations among individuals. Understanding the structure of such multi-relational network is essential. In sociology, one way of structural analysis is to identify different positions and roles using blockmodels. In this paper, we generalize stochastic blockmodels to Generalized Stochastic Blockmodels (GSBM) for performing positional and role analysis on multi-relational networks. Our GSBM generalizes many different kinds of Multivariate Probability Distribution Function (MVPDF) to model different kinds of multirelational networks. In particular, we propose to use multivariate Poisson distribution for multi-relational social networks.

Cycles Of Electronic Health Records Adaptation By Physicians: How Do The Positive And Negative Experience With The Ehr System Affect Physicians' Ehr Adaptation Process?, Cherie Noteboom, Dhundy Bastola, Sajda Qureshi

Research & Publications

The integration of EHR in IT infrastructures supporting organizations enable improved access and recording of patient data, enhanced ability to make improved decisions, improved quality and reduced errors in patient care. Despite these benefits, there are mixed results as to the use of EHR. The literature suggests that the reasons for the limited use relate to policy, financial and usability considerations, but it does not provide an understanding of reasons for physicians’ limited interaction and adaptation of EHR.

Following an analysis of qualitative data, collected in a case study at a hospital using interviews, this research explains how physicians interact …

Economic Culture And Trading Behaviors In Information Markets, Khalid Nasser Alhayyan

USF Tampa Graduate Theses and Dissertations

There are four main components for influencing traders' behaviors in an information market context: trader characteristics, organizational characteristics, market design, and external information. This dissertation focuses on investigating the impact of individual trader characteristics on trading behaviors. Two newly-developed constructs, highly relevant to information market contexts, were identified to increase our understanding about trading behaviors: trader's economic culture and trader independence. The theory of planned behavior is used as the theoretical basis to postulate hypotheses for empirical testing. Data collected from subjects through a series of web-based experiments shows that trader participation can be fostered through recruiting individuals who are …

The Application Of A Visual Data Mining Framework To Determine Soil, Climate And Land-Use Relationships, Yunous Vagh

Research outputs 2012

In this research study, the methodology of action research dynamics and a case study was employed in constructing a visual data mining framework for the processing and analysis of geographic land-use data in an agricultural context. The geographic data was made up of a digital elevation model (DEM), soil and land use profiles that were juxtaposed with previously captured climatic data from fixed weather stations in Australia. In this pilot study, monthly rainfall profiles for a selected study area were used to identify areas of soil variability. The rainfall was sampled for the beginning (April) of the rainy season for …

Wikis: Transactive Memory Systems In Digital Form, Paul Jackson

Research outputs 2012

Wikis embed information about authors, tags, hyperlinks and other metadata into the information they create. Wiki functions use this metadata to provide pointers which allow users to track down, or be informed of, the information they need. In this paper we provide a firm theoretical conceptualization for this type of activity by showing how this metadata provides a digital foundation for a Transactive Memory System (TMS). TMS is a construct from group psychology which defines directory-based knowledge sharing processes to explain the phenomenon of "group mind". We analyzed the functions and data of two leading Wiki products to understand where …

A Perspective On Resource Synchronization, Herbert Van De Sompel, Robert Sanderson, Martin Klein, Michael L. Nelson, Bernhard Haslhofer, Simeon Warner, Carl Lagoze

Computer Science Faculty Publications

Web applications frequently leverage resources made available by remote web servers. As resources are created, updated, deleted, or moved, these applications face challenges to remain in lockstep with changes on the server. Several approaches exist to help meet this challenge for use cases where "good enough" synchronization is acceptable. But when strict resource coverage or low synchronization latency is required, commonly accepted Web-based solutions remain illusive. This paper provides a perspective on the resource synchronization problem that results from inspiration gained from prior work, and initial insights resulting from the recently launched NISO/OAI ResourceSync effort.

Demographic Prediction Of Mobile User From Phone Usage, Shahram Mohrehkesh, Shuiwang Ji, Tamer Nadeem, Michele C. Weigle

Computer Science Faculty Publications

In this paper, we describe how we use the mobile phone usage of users to predict their demographic attributes. Using call log, visited GSM cells information, visited Bluetooth devices, visited Wireless LAN devices, accelerometer data, and so on, we predict the gender, age, marital status, job and number of people in household of users. The accuracy of developed classifiers for these classification problems ranges from 45-87% depending upon the particular classification problem.

Warcreate - Create Wayback-Consumable Warc Files From Any Webpage, Mat Kelly, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

[First Slide]

What is WARCreate?

• Google Chrome extension
• Creates WARC files
• Enables preservation by users from their browser
• First steps in bringing Institutional Archiving facilities to the PC

Modeling And Compressing 3-D Facial Expressions Using Geometry Videos, Jiazhi Xia, Dao T. P. Quynh, Ying He, Xiaoming Chen, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

In this paper, we present a novel geometry video (GV) framework to model and compress 3-D facial expressions. GV bridges the gap of 3-D motion data and 2-D video, and provides a natural way to apply the well-studied video processing techniques to motion data processing. Our framework includes a set of algorithms to construct GVs, such as hole filling, geodesic-based face segmentation, expression-invariant parameterization (EIP), and GV compression. Our EIP algorithm can guarantee the exact correspondence of the salient features (eyes, mouth, and nose) in different frames, which leads to GVs with better spatial and temporal coherence than that of …

Systems And Methods For Transaction Account Offerings, Clinton Allen, Michael Digregorio, Glade Erikson, Deepinder Gulati, Jacob Plammoottil Jacob, Sanjiv Khosla, Seema Chokshi

Research Collection School Of Computing and Information Systems

A method for receiving a user input for providing offerings is disclosed. Fields may be populated for creating a database query for matching a selection of offerings to a population of customers. Data may be received from the database, in response to interactively building the query and/or executing the query. Multiple rank ordered results may be produced for comparison, wherein the producing uses preprogrammed analytics, data from the database and user input, and wherein the results include customer lists linked to a distinct offering and a preferred delivery channel of the offering to a customer. A transaction account may be …

Tweets And Votes: A Study Of The 2011 Singapore General Election, Marko M. Skoric, Nathaniel D. Poor, Palakorn Achananuparp, Ee Peng Lim, Jing Jiang

Research Collection School Of Computing and Information Systems

This study focuses on the uses of Twitter during the elections, examining whether the messages posted online are reflective of the climate of public opinion. Using Twitter data obtained during the official campaign period of the 2011 Singapore General Election, we test the predictive power of tweets in forecasting the election results. In line with some previous studies, we find that during the elections the Twitter sphere represents a rich source of data for gauging public opinion and that the frequency of tweets mentioning names of political parties, political candidates and contested constituencies could be used to make predictions about …

Information Extraction From Text, Jing Jiang

Research Collection School Of Computing and Information Systems

Information extraction is the task of finding structured information from unstructured or semi-structured text. It is an important task in text mining and has been extensively studied in various research communities including natural language processing, information retrieval and Web mining. It has a wide range of applications in domains such as biomedical literature mining and business intelligence. Two fundamental tasks of information extraction are named entity recognition and relation extraction. The former refers to finding names of entities such as people, organizations and locations. The latter refers to finding the semantic relations such as FounderOf and HeadquarteredIn between entities. In …

Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Trends in natural and machine intelligence are increasingly reflecting a convergence in these two well-established fields of study. The Third International Neural Network Society Winter Conference (INNS-WC 2012) was held in Bangkok, Thailand, on October 3-5, 2012. INNS-WC2012, with an aim to bring together scientists, practitioners, and students worldwide, to discuss the past, present, and future challenges and trends in the area of natural and machine intelligence. This event has been a bi-annual conference of the International Neural Network Society (INNS) to provide a forum for international researchers to exchange latest ideas and advances on neural networks and related discipline.

An Improved K-Nearest-Neighbor Algorithm For Text Categorization, Shengyi Jiang, Guansong Pang, Meiling Wu, Limin Kuang

Research Collection School Of Computing and Information Systems

Text categorization is a significant tool to manage and organize the surging text data. Many text categorization algorithms have been explored in previous literatures, such as KNN, Naive Bayes and Support Vector Machine. KNN text categorization is an effective but less efficient classification method. In this paper, we propose an improved KNN algorithm for text categorization, which builds the classification model by combining constrained one pass clustering algorithm and KNN text categorization. Empirical results on three benchmark corpora show that our algorithm can reduce the text similarity computation substantially and outperform the-state-of-the-art KNN, Naive Bayes and Support Vector Machine classifiers. …

Mining Diversity On Social Media Networks, Lu Liu, Feida Zhu, Meng Jiang, Jiawei Han, Lifeng Sun, Shiqiang Yang

Research Collection School Of Computing and Information Systems

The fast development of multimedia technology and increasing availability of network bandwidth has given rise to an abundance of network data as a result of all the ever-booming social media and social websites in recent years, e.g., Flickr, Youtube, MySpace, Facebook, etc. Social network analysis has therefore become a critical problem attracting enthusiasm from both academia and industry. However, an important measure that captures a participant’s diversity in the network has been largely neglected in previous studies. Namely, diversity characterizes how diverse a given node connects with its peers. In this paper, we give a comprehensive study of this concept. …

Automatic Document Classification In Small Environments, Jonathan David Mcelroy

Master's Theses

Document classification is used to sort and label documents. This gives users quicker access to relevant data. Users that work with large inflow of documents spend time filing and categorizing them to allow for easier procurement. The Automatic Classification and Document Filing (ACDF) system proposed here is designed to allow users working with files or documents to rely on the system to classify and store them with little manual attention. By using a system built on Hidden Markov Models, the documents in a smaller desktop environment are categorized with better results than the traditional Naive Bayes implementation of classification.

A Data-Descriptive Feedback Framework For Data Stream Management Systems, Rafael J. Fernández Moctezuma

Dissertations and Theses

Data Stream Management Systems (DSMSs) provide support for continuous query evaluation over data streams. Data streams provide processing challenges due to their unbounded nature and varying characteristics, such as rate and density fluctuations. DSMSs need to adapt stream processing to these changes within certain constraints, such as available computational resources and minimum latency requirements in producing results. The proposed research develops an inter-operator feedback framework, where opportunities for run-time adaptation of stream processing are expressed in terms of descriptions of substreams and actions applicable to the substreams, called feedback punctuations. Both the discovery of adaptation opportunities and the exploitation of …