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Articles 3661 - 3690 of 6727
Full-Text Articles in Physical Sciences and Mathematics
An Adaptive Gradient Method For Online Auc Maximization, Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong
An Adaptive Gradient Method For Online Auc Maximization, Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong
Research Collection School Of Computing and Information Systems
Learning for maximizing AUC performance is an important research problem in machine learning. Unlike traditional batch learning methods for maximizing AUC which often suffer from poor scalability, recent years have witnessed some emerging studies that attempt to maximize AUC by single-pass online learning approaches. Despite their encouraging results reported, the existing online AUC maximization algorithms often adopt simple stochastic gradient descent approaches, which fail to exploit the geometry knowledge of the data observed in the online learning process, and thus could suffer from relatively slow convergence. To overcome the limitation of the existing studies, in this paper, we propose a …
Cepsim: A Simulator For Cloud-Based Complex Event Processing, Wilson Higashino, Miriam Capretz, Luiz Bittencourt
Cepsim: A Simulator For Cloud-Based Complex Event Processing, Wilson Higashino, Miriam Capretz, Luiz Bittencourt
Wilson A Higashino
As one of the Vs defining Big Data, data velocity brings many new challenges to traditional data processing approaches. The adoption of cloud environments in complex event processing (CEP) systems is a recent architectural style that aims to overcome these challenges. Validating cloud-based CEP systems at the required Big Data scale, however, is often a laborious, error-prone, and expensive task. This article presents CEPSim, a new simulator that has been developed to facilitate this validation process. CEPSim extends CloudSim, an existing cloud simulator, with an application model based on directed acyclic graphs that is used to represent continuous CEP queries. …
Information Technology, Ying Chen
Information Technology, Ying Chen
Ying Chen
This research guide includes lists and links for recommended databases, journals, and web resources on Information Technology. It also provides helpful information for citation and writing with emphasis on the science disciplines.
Data, Analytics And Community-Based Organizations: Transforming Data To Decisions For Community Development, Michael P. Johnson Jr.
Data, Analytics And Community-Based Organizations: Transforming Data To Decisions For Community Development, Michael P. Johnson Jr.
Michael P. Johnson
The past ten years have seen a revolution in two disciplines related to operations and strategy design. “Big Data” has transformed the theory and practice of producing and selling goods and services through methods associated with computer science and information technology. “Analytics” has popularized primarily quantitative models and methods by which organizations and systems can measure multiple aspects of performance. As these fields rely on information technology to collect, store, process and share data, we refer to the collection of knowledge and applications associated with Big Data and analytics as “data analytics and information technology.” The impacts of data analytics …
Drip - Data Rich, Information Poor: A Concise Synopsis Of Data Mining, Muhammad Obeidat, Max North, Lloyd Burgess, Sarah North
Drip - Data Rich, Information Poor: A Concise Synopsis Of Data Mining, Muhammad Obeidat, Max North, Lloyd Burgess, Sarah North
Faculty Articles
As production of data is exponentially growing with a drastically lower cost, the importance of data mining required to extract and discover valuable information is becoming more paramount. To be functional in any business or industry, data must be capable of supporting sound decision-making and plausible prediction. The purpose of this paper is concisely but broadly to provide a synopsis of the technology and theory of data mining, providing an enhanced comprehension of the methods by which massive data can be transferred into meaningful information.
Optimizing Data Movement In Hybrid Analytic Systems, Patrick Michael Leyshock
Optimizing Data Movement In Hybrid Analytic Systems, Patrick Michael Leyshock
Dissertations and Theses
Hybrid systems for analyzing big data integrate an analytic tool and a dedicated data-management platform, storing data and operating on the data at both components. While hybrid systems have benefits over alternative architectures, in order to be effective, data movement between the two hybrid components must be minimized. Extant hybrid systems either fail to address performance problems stemming from inter-component data movement, or else require the user to explicitly reason about and manage data movement. My work presents the design, implementation, and evaluation of a hybrid analytic system for array-structured data that automatically minimizes data movement between the hybrid components. …
A Gis-Centric Approach For Modeling Vessel Management Behavior System Data To Determine Oyster Vessel Behavior On Public Oyster Grounds In Louisiana, David X. Gallegos
A Gis-Centric Approach For Modeling Vessel Management Behavior System Data To Determine Oyster Vessel Behavior On Public Oyster Grounds In Louisiana, David X. Gallegos
University of New Orleans Theses and Dissertations
The satellite communications system called the Vessel Management System was used to provide geospatial data on oyster fishing over the nearly 1.7 million acres of the public water bottoms in Louisiana. An algorithm to analyze the data was developed in order to model vessel behaviors including docked, gearing, fishing and traveling. Vessel speeds were calculated via the Haversine formula at small and large intervals and compared to derive a measure of linearity. The algorithm was implemented into software using Python and inserted into a PostgreSQL database supporting geospatial information. Queries were developed to obtain reports on vessel activities and daily …
Recommender Systems Research: A Connection-Centric Survey, Saverio Perugini, Marcos André Gonçalves, Edward A. Fox
Recommender Systems Research: A Connection-Centric Survey, Saverio Perugini, Marcos André Gonçalves, Edward A. Fox
Saverio Perugini
Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in recommender systems grew out of information retrieval and filtering, the topic has steadily advanced into a legitimate and challenging research area of its own. Recommender systems have traditionally been studied from a content-based filtering vs. collaborative design perspective. Recommendations, however, are not delivered within a vacuum, but rather cast within an informal community of users and social context. Therefore, ultimately all recommender systems make connections among people and thus should be surveyed from …
Symbolic Links In The Open Directory Project, Saverio Perugini
Symbolic Links In The Open Directory Project, Saverio Perugini
Saverio Perugini
We present a study to develop an improved understanding of symbolic links in web directories. A symbolic link is a hyperlink that makes a directed connection from a web page along one path through a directory to a page along another path. While symbolic links are ubiquitous in web directories such as Yahoo!, they are under-studied, and as a result, their uses are poorly understood. A cursory analysis of symbolic links reveals multiple uses: to provide navigational shortcuts deeper into a directory, backlinks to more general categories, and multiclassification. We investigated these uses in the Open Directory Project (ODP), the …
Interacting With Web Hierarchies, Saverio Perugini, Naren Ramakrishnan
Interacting With Web Hierarchies, Saverio Perugini, Naren Ramakrishnan
Saverio Perugini
Web site interfaces are a particularly good fit for hierarchies in the broadest sense of that idea, i.e. a classification with multiple attributes, not necessarily a tree structure. Several adaptive interface designs are emerging that support flexible navigation orders, exposing and exploring dependencies, and procedural information-seeking tasks. This paper provides a context and vocabulary for thinking about hierarchical Web sites and their design. The paper identifies three features that interface to information hierarchies. These are flexible navigation orders, the ability to expose and explore dependencies, and support for procedural tasks. A few examples of these features are also provided
The Partial Evaluation Approach To Information Personalization, Naren Ramakrishnan, Saverio Perugini
The Partial Evaluation Approach To Information Personalization, Naren Ramakrishnan, Saverio Perugini
Saverio Perugini
Information personalization refers to the automatic adjustment of information content, structure, and presentation tailored to an individual user. By reducing information overload and customizing information access, personalization systems have emerged as an important segment of the Internet economy. This paper presents a systematic modeling methodology— PIPE (‘Personalization is Partial Evaluation’) — for personalization. Personalization systems are designed and implemented in PIPE by modeling an information-seeking interaction in a programmatic representation. The representation supports the description of information-seeking activities as partial information and their subsequent realization by partial evaluation, a technique for specializing programs. We describe the modeling methodology at a …
The Staging Transformation Approach To Mixing Initiative, Robert Capra, Michael Narayan, Saverio Perugini, Naren Ramakrishnan, Manuel A. Pérez-Quiñones
The Staging Transformation Approach To Mixing Initiative, Robert Capra, Michael Narayan, Saverio Perugini, Naren Ramakrishnan, Manuel A. Pérez-Quiñones
Saverio Perugini
Mixed-initiative interaction is an important facet of many conversational interfaces, flexible planning architectures, intelligent tutoring systems, and interactive information retrieval systems. Software systems for mixed-initiative interaction must enable us to both operationalize the mixing of initiative (i.e., support the creation of practical dialogs) and to reason in real-time about how a flexible mode of interaction can be supported (e.g., from a meta-dialog standpoint). In this paper, we present the staging transformation approach to mixing initiative, where a dialog script captures the structure of the dialog and dialog control processes are realized through generous use of program transformation techniques (e.g., partial …
A Study Of Out-Of-Turn Interaction In Menu-Based, Ivr, Voicemail Systems, Saverio Perugini, Taylor J. Anderson, William F. Moroney
A Study Of Out-Of-Turn Interaction In Menu-Based, Ivr, Voicemail Systems, Saverio Perugini, Taylor J. Anderson, William F. Moroney
Saverio Perugini
We present the first user study of out-of-turn interaction in menu-based, interactive voice-response systems. Out-ofturn interaction is a technique which empowers the user (unable to respond to the current prompt) to take the conversational initiative by supplying information that is currently unsolicited, but expected later in the dialog. The technique permits the user to circumvent any flows of navigation hardwired into the design and navigate the menus in a manner which reflects their model of the task. We conducted a laboratory experiment to measure the effect of the use of outof- turn interaction on user performance and preference in a …
Exploring Out-Of-Turn Interactions With Websites, Saverio Perugini, Naren Ramakrishnan, Manuel A. Pérez-Quiñones, Mary E. Pinney, Mary Beth Rosson
Exploring Out-Of-Turn Interactions With Websites, Saverio Perugini, Naren Ramakrishnan, Manuel A. Pérez-Quiñones, Mary E. Pinney, Mary Beth Rosson
Saverio Perugini
Hierarchies are ubiquitous on the web for structuring online catalogs and indexing multidimensional attributed data sets. They are a natural metaphor for information seeking if their levelwise structure mirrors the user's conception of the underlying domain. In other cases, they can be frustrating, especially if multiple drill‐downs are necessary to arrive at information of interest. To support a broad range of users, site designers often expose multiple faceted classifications or provide within‐page pruning mechanisms. We present a new technique, called out-of-turn interaction, that increases the richness of user interaction at hierarchical sites, without enumerating all possible completion paths in the …
Personalizing The Gams Cross-Index, Saverio Perugini, Priya Lakshminarayanan, Naren Ramakrishnan
Personalizing The Gams Cross-Index, Saverio Perugini, Priya Lakshminarayanan, Naren Ramakrishnan
Saverio Perugini
The NIST Guide to Available Mathematical Software (GAMS) system at http://gams.nist .gov serves as the gateway to thousands of scientific codes and modules for numerical computation. We describe the PIPE personalization facility for GAMS, whereby content from the cross-index is specialized for a user desiring software recommendations for a specific problem instance. The key idea is to (i) mine structure, and (ii) exploit it in a programmatic manner to generate personalized web pages. Our approach supports both content-based and collaborative personalization and enables information integration from multiple (and complementary) web resources. We present case studies for the domain of linear, …
Information Assurance Through Binary Vulnerability Auditing, William B. Kimball, Saverio Perugini
Information Assurance Through Binary Vulnerability Auditing, William B. Kimball, Saverio Perugini
Saverio Perugini
The goal of this research is to develop improved methods of discovering vulnerabilities in software. A large volume of software, from the most frequently used programs on a desktop computer, such as web browsers, e-mail programs, and word processing applications, to mission-critical services for the space shuttle, is unintentionally vulnerable to attacks and thus insecure. By seeking to improve the identification of vulnerabilities in software, the security community can save the time and money necessary to restore compromised computer systems. In addition, this research is imperative to activities of national security such as counterterrorism. The current approach involves a systematic …
Personalizing Interactions With Information Systems, Saverio Perugini, Naren Ramakrishnan
Personalizing Interactions With Information Systems, Saverio Perugini, Naren Ramakrishnan
Saverio Perugini
Personalization constitutes the mechanisms and technologies necessary to customize information access to the end-user. It can be defined as the automatic adjustment of information content, structure, and presentation tailored to the individual. In this chapter, we study personalization from the viewpoint of personalizing interaction. The survey covers mechanisms for information-finding on the web, advanced information retrieval systems, dialog-based applications, and mobile access paradigms. Specific emphasis is placed on studying how users interact with an information system and how the system can encourage and foster interaction. This helps bring out the role of the personalization system as a facilitator which reconciles …
Supporting Multiple Paths To Objects In Information Hierarchies: Faceted Classification, Faceted Search, And Symbolic Links, Saverio Perugini
Supporting Multiple Paths To Objects In Information Hierarchies: Faceted Classification, Faceted Search, And Symbolic Links, Saverio Perugini
Saverio Perugini
We present three fundamental, interrelated approaches to support multiple access paths to each terminal object in information hierarchies: faceted classification, faceted search, and web directories with embedded symbolic links. This survey aims to demonstrate how each approach supports users who seek information from multiple perspectives. We achieve this by exploring each approach, the relationships between these approaches, including tradeoffs, and how they can be used in concert, while focusing on a core set of hypermedia elements common to all. This approach provides a foundation from which to study, understand, and synthesize applications which employ these techniques. This survey does not …
Recommender Systems Research, Saverio Perugini
Recommender Systems Research, Saverio Perugini
Saverio Perugini
We outline the history of recommender systems from their roots in information retrieval and filtering to their role in today’s Internet economy. Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. Research in recommender systems lies at the intersection of several areas of computer science, such as artificial intelligence and human-computer interaction, and has progressed to an important research area of its own. It is important to note that recommendations are not delivered within a vacuum, but rather cast within an informal community of users …
Program Transformations For Information Personalization, Saverio Perugini
Program Transformations For Information Personalization, Saverio Perugini
Saverio Perugini
Personalization constitutes the mechanisms and technologies necessary to customize information access to the end-user. It can be defined as the automatic adjustment of information content, structure, and presentation. The central thesis of this dissertation is that modeling interaction explicitly in a representation, and studying how partial information can be harnessed in it by program transformations to direct the flow of the interaction, can provide insight into, reveal opportunities for, and define a model for personalized interaction. To evaluate this thesis, a formal modeling methodology is developed for personalizing interactions with information systems, especially hierarchical hypermedia, based on program transformations. The …
A Generative Programming Approach To Interactive Information Retrieval: Insights And Experiences, Saverio Perugini, Naren Ramakrishnan
A Generative Programming Approach To Interactive Information Retrieval: Insights And Experiences, Saverio Perugini, Naren Ramakrishnan
Saverio Perugini
We describe the application of generative programming to a problem in interactive information retrieval. The particular interactive information retrieval problem we study is the support for "out-of-turn interaction" with a website – how a user can communicate input to a website when the site is not soliciting such information on the current page, but will do so on a subsequent page. Our solution approach makes generous use of program transformations (partial evaluation, currying, and slicing) to delay the site’s current solicitation for input until after the user’s out-of-turn input is processed. We illustrate how studying out-of-turn interaction through a generative …
Realtime Query Expansion And Procedural Interfaces For Information Hierarchies, Saverio Perugini
Realtime Query Expansion And Procedural Interfaces For Information Hierarchies, Saverio Perugini
Saverio Perugini
We demonstrate the use of two user interfaces for interacting with web hierarchies. One uses the dependencies underlying a hierarchy to perform real-time query expansion and, in this way, acts as an in situ feedback mechanism. The other enables the user to cascade the output from one interaction to the input of another, and so on, and, in this way, supports procedural information-seeking tasks without disrupting the flow of interaction.
Personalization By Program Slicing, Saverio Perugini, Naren Ramakrishnan
Personalization By Program Slicing, Saverio Perugini, Naren Ramakrishnan
Saverio Perugini
Personalization involves customizing information access to the end-user. As any new area of computer science research it lacks formal models to guide the design of systems. In this paper, we present a modeling methodology, based on generative programming, for personalizing interactions with hierarchical websites. The methodology entails modeling a user’s interaction with a site in a program and applying program slicing to personalize the interaction. While preserving interactivity, this approach does not require the designer to anticipate all possible user interactions a priori and provide interfaces for each. Moreover, it provides a theoretical, systematic, and implementation-neutral way to design systems …
The Good, Bad And The Indifferent: Explorations In Recommender System Health, Benjamin J. Keller, Sun-Mi Kim, N. Srinivas Vemuri, Naren Ramakrishnan, Saverio Perugini
The Good, Bad And The Indifferent: Explorations In Recommender System Health, Benjamin J. Keller, Sun-Mi Kim, N. Srinivas Vemuri, Naren Ramakrishnan, Saverio Perugini
Saverio Perugini
Our work is based on the premise that analysis of the connections exploited by a recommender algorithm can provide insight into the algorithm that could be useful to predict its performance in a fielded system. We use the jumping connections model defined by Mirza et al. [6], which describes the recommendation process in terms of graphs. Here we discuss our work that has come out of trying to understand algorithm behavior in terms of these graphs. We start by describing a natural extension of the jumping connections model of Mirza et al., and then discuss observations that have come from …
Personalization By Website Transformation: Theory And Practice, Saverio Perugini
Personalization By Website Transformation: Theory And Practice, Saverio Perugini
Saverio Perugini
We present an analysis of a progressive series of out-of-turn transformations on a hierarchical website to personalize a user’s interaction with the site. We formalize the transformation in graph-theoretic terms and describe a toolkit we built that enumerates all of the traversals enabled by every possible complete series of these transformations in any site and computes a variety of metrics while simulating each traversal therein to qualify the relationship between a site’s structure and the cumulative effect of support for the transformation in a site. We employed this toolkit in two websites. The results indicate that the transformation enables users …
Staging Transformations For Multimodal Web Interaction Management, Michael Narayan, Christopher Williams, Saverio Perugini, Naren Ramakrishnan
Staging Transformations For Multimodal Web Interaction Management, Michael Narayan, Christopher Williams, Saverio Perugini, Naren Ramakrishnan
Saverio Perugini
Multimodal interfaces are becoming increasingly ubiquitous with the advent of mobile devices, accessibility considerations, and novel software technologies that combine diverse interaction media. In addition to improving access and delivery capabilities, such interfaces enable flexible and personalized dialogs with websites, much like a conversation between humans. In this paper, we present a software framework for multimodal web interaction management that supports mixed-initiative dialogs between users and websites. A mixed-initiative dialog is one where the user and the website take turns changing the flow of interaction. The framework supports the functional specification and realization of such dialogs using staging transformations – …
A Content-Sensitive Wiki Help System, Eswara Satya Pavan Rajesh Pinapala
A Content-Sensitive Wiki Help System, Eswara Satya Pavan Rajesh Pinapala
Master's Projects
Context-sensitive help is a software application component that enables users to open help pertaining to their state, location, or the action they are performing within the software. Context-sensitive “wiki” help, on the other hand, is help powered by a wiki system with all the features of context-sensitive help. A context-sensitive wiki help system aims to make the context-sensitive help collaborative; in addition to seeking help, users can directly contribute to the help system. I have implemented a context-sensitive wiki help system into Yioop, an open source search engine and software portal created by Dr. Chris Pollett, in order to measure …
Facilitating Natural Conversational Agent Interactions: Lessons From A Deception Experiment, Ryan M. Schuetzler, Mark Grimes, Justin Scott Giboney, Joesph Buckman
Facilitating Natural Conversational Agent Interactions: Lessons From A Deception Experiment, Ryan M. Schuetzler, Mark Grimes, Justin Scott Giboney, Joesph Buckman
Information Systems and Quantitative Analysis Faculty Proceedings & Presentations
This study reports the results of a laboratory experiment exploring interactions between humans and a conversational agent. Using the ChatScript language, we created a chat bot that asked participants to describe a series of images. The two objectives of this study were (1) to analyze the impact of dynamic responses on participants’ perceptions of the conversational agent, and (2) to explore behavioral changes in interactions with the chat bot (i.e. response latency and pauses) when participants engaged in deception. We discovered that a chat bot that provides adaptive responses based on the participant’s input dramatically increases the perceived humanness and …
Use Of Secure Messaging By United States Veterans And Significant Others, Claudia S. Derman
Use Of Secure Messaging By United States Veterans And Significant Others, Claudia S. Derman
Theses and Dissertations
ABSTRACT
USE OF SECURE MESSAGING BY UNITED STATES VETERANS AND SIGNIFICANT OTHERS
By
Claudia S. Derman
The University of Wisconsin-Milwaukee, 2014
Under the Supervision of Professor Karen H. Morin, PhD, RN, ANEF, FAAN
The purpose of this study was to describe the topics discussed using secure messaging (SM), the pattern of use of SM, and whether the themes discussed and/or the pattern of use varied based on gender and age of the SM user. Secure messaging is an example of a technology that focuses on patient-centered communication. Secure messaging allows patients to communicate with their clinicians using the Internet and …
Three Essays On Opinion Mining Of Social Media Texts, Shuyuan Deng
Three Essays On Opinion Mining Of Social Media Texts, Shuyuan Deng
Theses and Dissertations
This dissertation research is a collection of three essays on opinion mining of social media texts. I explore different theoretical and methodological perspectives in this inquiry. The first essay focuses on improving lexicon-based sentiment classification. I propose a method to automatically generate a sentiment lexicon that incorporates knowledge from both the language domain and the content domain. This method learns word associations from a large unannotated corpus. These associations are used to identify new sentiment words. Using a Twitter data set containing 743,069 tweets related to the stock market, I show that the sentiment lexicons generated using the proposed method …