Databases and Information Systems Commons^™

Self-Organizing Neural Networks Integrating Domain Knowledge And Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Jacek M. Zurada

Research Collection School Of Computing and Information Systems

The use of domain knowledge in learning systems is expected to improve learning efficiency and reduce model complexity. However, due to the incompatibility with knowledge structure of the learning systems and real-time exploratory nature of reinforcement learning (RL), domain knowledge cannot be inserted directly. In this paper, we show how self-organizing neural networks designed for online and incremental adaptation can integrate domain knowledge and RL. Specifically, symbol-based domain knowledge is translated into numeric patterns before inserting into the self-organizing neural networks. To ensure effective use of domain knowledge, we present an analysis of how the inserted knowledge is used by …

A Nested Recursive Logit Model For Route Choice Analysis, Tien Mai, Mogens Fosgerau, Emma Frejinger

Research Collection School Of Computing and Information Systems

We propose a route choice model that relaxes the independence from irrelevant alternatives property of the logit model by allowing scale parameters to be link specific. Similar to the recursive logit (RL) model proposed by Fosgerau et al. (2013), the choice of path is modeled as a sequence of link choices and the model does not require any sampling of choice sets. Furthermore, the model can be consistently estimated and efficiently used for prediction.A key challenge lies in the computation of the value functions, i.e. the expected maximum utility from any position in the network to a destination. The value …

Advances In Knowledge Discovery And Data Mining Part Ii, Tru Cao, Ee Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Wai-Lok Cheung, Hiroshi Motoda

Research Collection School Of Computing and Information Systems

No abstract provided.

Beyond Traits: Social Context Based Personality Model, Jaroslaw Kochanowicz, Ah-Hwee Tan, Daniel Thalmann

Research Collection School Of Computing and Information Systems

The relation between individual’s personality and environmental context is a key issue in psychology, recently also in character simulations. This paper contributes to both domains by proposing a socio-cognitive, contextual personality model - a new voice in a century old problem of personality, but also an approach to simulating groups of more humanlike agents. After analyzing the influence of popularity of ‘trait personality models’ on psychology and computer simulation, we propose Social Context based Personality model - a continuation and specification of the Cognitive-Affective Personality System theory. The discussion, model and implementation are provided, followed by an example application in …

Mining Patterns Of Unsatisfiable Constraints To Detect Infeasible Paths, Sun Ding, Hee Beng Kuan Tan, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

Detection of infeasible paths is required in many areas including test coverage analysis, test case generation, security vulnerability analysis, etc. Existing approaches typically use static analysis coupled with symbolic evaluation, heuristics, or path-pattern analysis. This paper is related to these approaches but with a different objective. It is to analyze code of real systems to build patterns of unsatisfiable constraints in infeasible paths. The resulting patterns can be used to detect infeasible paths without the use of constraint solver and evaluation of function calls involved, thus improving scalability. The patterns can be built gradually. Evaluation of the proposed approach shows …

Breaking The News: First Impressions Matter On Online News, Julio Reis, Fabr´Icio Benevenuto, Pedro Olmo, Raquel Prates, Haewoon Kwak, Jisun An

Research Collection School Of Computing and Information Systems

A growing number of people are changing the way they consume news, replacing the traditional physical newspapers and magazines by their virtual online versions or/and weblogs. The interactivity and immediacy present in online news are changing the way news are being produced and exposed by media corporations. News websites have to create effective strategies to catch people’s attention and attract their clicks. In this paper we investigate possible strategies used by online news corporations in the design of their news headlines. We analyze the content of 69,907 headlines produced by four major global media corporations during a minimum of eight …

Report On The Fg 2015 Video Person Recognition Evaluation, J.R. Beveridge, H. Zhang, B.A. Draper, P.J. Flynn, Z. Feng, P. Huber, J. Kittler, Zhiwu Huang, Li S., Li Y., M. Kan, R. Wang, S. Shan, X. Chen, Li H., G. Hua, V. Struc, J. Krizaj, C. Ding, D. Tao

Research Collection School Of Computing and Information Systems

This report presents results from the Video Person Recognition Evaluation held in conjunction with the 11th IEEE International Conference on Automatic Face and Gesture Recognition. Two experiments required algorithms to recognize people in videos from the Point-and-Shoot Face Recognition Challenge Problem (PaSC). The first consisted of videos from a tripod mounted high quality video camera. The second contained videos acquired from 5 different handheld video cameras. There were 1401 videos in each experiment of 265 subjects. The subjects, the scenes, and the actions carried out by the people are the same in both experiments. Five groups from around the world …

Map: A Computational Model For Adaptive Persuasion, Yilin Kang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

While a variety of persuasion agents have been created and applied in different domains such as marketing, military training and health industry, there is a lack of a model which provides a unified framework for different persuasion strategies. Specifically, persuasion is not adaptable to the individuals’ personal states in different situations. Grounded in the Elaboration Likelihood Model (ELM), this paper presents a computational model called Model for Adaptive Persuasion (MAP) for virtual agents. MAP is a semi-connected network model which enables an agent to adapt its persuasion strategies through feedback. We have implemented and evaluated a MAP-based virtual nurse agent …

Discovering The Rise And Fall Of Software Engineering Ideas From Scholarly Publication Data, Subhajit Datta, Santonu Sarkar, Sajeev A. S. M., Nishant Kumar

Research Collection School Of Computing and Information Systems

For researchers and practitioners of a relatively young discipline like software engineering, an enduring concern is to identify the acorns that will grow into oaks -- ideas remaining most current in the long run. Additionally, it is interesting to know how the ideas have risen in importance, and fallen, perhaps to rise again. We analyzed a corpus of 19,000+ papers written by 21,000+ authors across 16 software engineering publication venues from 1975 to 2010, to empirically determine the half-life of software engineering research topics. We adapted existing measures of half-life as well as defined a specific measure based on publication …

Moving Average Reversion Strategy For On-Line Portfolio Selection, Bin Li, Steven C. H. Hoi, Doyen Sahoo, Zhi-Yong Liu

Research Collection School Of Computing and Information Systems

On-line portfolio selection, a fundamental problem in computational finance, has attracted increasing interest from artificial intelligence and machine learning communities in recent years. Empirical evidence shows that stock's high and low prices are temporary and stock prices are likely to follow the mean reversion phenomenon. While existing mean reversion strategies are shown to achieve good empirical performance on many real datasets, they often make the single-period mean reversion assumption, which is not always satisfied, leading to poor performance in certain real datasets. To overcome this limitation, this article proposes a multiple-period mean reversion, or so-called "Moving Average Reversion" (MAR), and …

Characterizing Silent Users In Social Media Communities, Wei Gong, Ee-Peng Lim, Feida Zhu

Research Collection School Of Computing and Information Systems

Silent users often constitute a significant proportion of an online user-generated content system. In the context of social media such as Twitter, users can opt to be silent all or most of the time. They are often called the invisible participants or lurkers. As lurkers contribute little to the online content, existing analysis often overlooks their presence and voices. However, we argue that understanding lurkers is important in many applications such as recommender systems, targeted advertising, and social sensing. This research therefore seeks to characterize lurkers in social media and propose methods to profile them. We examine 18 weeks of …

Big Data And Smart Cities, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Data Mining Temporal Work Patterns Of Programming Student Populations, Dale E. Parson, Lori Bogumil, Allison Seidel

Computer Science and Information Technology Faculty

This paper reports the second stage of a study of the correlations between the temporal work patterns of computer programming students and their success or failure as measured by programming project assignment grades and related metrics. The first stage confirmed the importance for most students of getting an early start on a programming project, and it also uncovered the fact that some student groups perform well with late starts, suggesting the likelihood that they engage in the productive practice of active procrastination. The second most important factor for success is the average length of assignment work sessions. Session lengths from …

How The University Of California Runs One Repository For Ten Campuses, Katie Fortney

Inaugural CSU IR Conference, 2015

Katie Fortney, JD, MLIS, Copyright Policy & Education Officer, Office of Scholarly Communication, University of California http://osc.universityofcalifornia.edu/

Implementing Metaarchive And Lockss At Digital Commons @Cal Poly, Michele Wyngard

Inaugural CSU IR Conference, 2015

Michele Wyngard, Digital Repository Coordinator, CSU Cal Poly

Using Google Tag Manager And Google Analytics, (Code{4}Lib Journal), Suzanna Conrad

Inaugural CSU IR Conference, 2015

Suzanna Conrad, Digital Initiatives Librarian, Cal Poly Pomona

What’S New Since The April 2013 Stim Ir Subcommittee Report To Cold: Hydra, Islandora And Dspace, Aaron Collier, Suzanna Conrad, Carmen Mitchell, Joan Parker, Andrew Weiss, Jeremy C. Shellhase

Inaugural CSU IR Conference, 2015

Aaron Collier, Digital Repository Services Manager, Chancellor’s Office
Suzanna Conrad, Digital Initiatives Librarian, Cal Poly Pomona
Carmen Mitchell, Institutional Repository Librarian, CSU San Marcos
Joan Parker, Librarian, Moss Landing Marine Laboratories
Andrew Weiss, Digital Services Librarian, CSU Northridge

Jeremy Shellhase, Head of Information Services & Systems Department, Humboldt State University

The State Of Scholarworks, Aaron Collier

Inaugural CSU IR Conference, 2015

Aaron Collier, Digital Repository Services Manager, Chancellor’s Office

Check Exception Automation (Cea) System, Aashima Arora

Masters Theses & Doctoral Dissertations

Check Exception Automation (CEA) System is a web application which provides the facility to create and resolve the check exception that occurs after the check is successfully deposited to the American Bank. Checks can be deposited via different channels such as ATM, Cash Vault (which is a kind of check dropping box) and via mobile. There are a number of exceptions that may occur after depositing the check such as missing signature, wrong amount, altered check, duplicate check and missing amount. The older check exception resolution process was manual process. The goal of this project is to automate the check …

Intensity And Resolution Enhancement Of Local Regions For Object Detection And Tracking In Wide Area Surveillance, Evan Krieger, Vijayan K. Asari, Saibabu Arigela, Theus H. Aspiras

Electrical and Computer Engineering Faculty Publications

Object tracking in wide area motion imagery is a complex problem that consists of object detection and target tracking over time. This challenge can be solved by human analysts who naturally have the ability to keep track of an object in a scene. A computer vision solution for object tracking has the potential to be a much faster and efficient solution. However, a computer vision solution faces certain challenges that do not affect a human analyst. To overcome these challenges, a tracking process is proposed that is inspired by the known advantages of a human analyst.

First, the focus of …