Databases and Information Systems Commons^™

Graduate Advisor System, Richard Brian Pallow

Theses Digitization Project

The purpose of this project is to update the architecture and design of the California State University San Bernardino Graduate Advisor System. This system allows potential students into the Master of Science degree program in Computer Science to complete their application online.

Taxaminer: An Experimentation Framework For Automated Taxonomy Bootstrapping, Vipul Kashyap, Cartic Ramakrishnan, Christopher Thomas, Amit P. Sheth

Kno.e.sis Publications

Construction of domain ontologies on the semantic web is a human and resource intensive process, efforts to reduce which are crucial for the Semantic Web to scale. We present a framework for automated taxonomy construction, that involves: (a) generation of a cluster hierarchy from a document corpus using statistical clustering and NLP techniques; (b) extraction of a topic hierarchy from this cluster hierarchy; and (c) assignment of labels to nodes in the topic hierarchy. Metrics for estimating topic hierarchy quality and parameters of an experimentation framework are identified. MEDLINE was the document corpus and MeSH thesaurus was the gold standard.

Ranking Complex Relationships On The Semantic Web, Boanerges Aleman-Meza, Christian Halaschek-Wiener, I. Budak Arpinar, Cartic Ramakrishnan, Amit P. Sheth

Kno.e.sis Publications

Industry and academia are both focusing their attention on information retrieval over semantic metadata extracted from the Web, and it is increasingly possible to analyze such metadata to discover interesting relationships. However, just as document ranking is a critical component in today's search engines, the ranking of complex relationships would be an important component in tomorrow's semantic Web engines. This article presents a flexible ranking approach to identify interesting and relevant relationships in the semantic Web. The authors demonstrate the scheme's effectiveness through an empirical evaluation over a real-world data set.

Variational Bayesian Image Modelling, Li Chen, Feng Jiao, Dale Schuurmans, Shaojun Wang

Kno.e.sis Publications

We present a variational Bayesian framework for performing inference, density estimation and model selection in a special class of graphical models—Hidden Markov Random Fields (HMRFs). HMRFs are particularly well suited to image modelling and in this paper, we apply them to the problem of image segmentation. Unfortunately, HMRFs are notoriously hard to train and use because the exact inference problems they create are intractable. Our main contribution is to introduce an efficient variational approach for performing approximate inference of the Bayesian formulation of HMRFs, which we can then apply to the density estimation and model selection problems that arise when …

How To Overcome The Knowledge Paradox: Activate Knowledge Identity, Not Just Organize Information, Sajda Qureshi, Peter Keen

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

A paradox appears to thwart traditional knowledge sharing efforts in organizations: the greater the benefit of a piece of knowledge to an organization the less likely that it will be shared. This paper suggests that in order to mobilize knowledge where there is demand for it, it has to be activated. This paper considers the knowledge identity of the person whose knowledge is to be activated and uses these identities to analyze a case study in which highly distributed knowledge is activated. The analysis reveals activation effects needed to mobilize each of the knowledge identities.

Framework For Semantic Web Process Composition, Kaarthik Sivashanmugam, John A. Miller, Amit P. Sheth, Kunal Verma

Kno.e.sis Publications

Web services have the potential to revolutionize e-commerce by enabling businesses to interact with each other on the fly. To date, however, Web processes using Web services have been created mostly at the syntactic level. Current composition standards focus on building processes based on the interface description of the participating services. This rigid approach, with its strong coupling between the process and the interface of the participating services, does not allow businesses to dynamically change partners and services. As shown in this article, Web process composition techniques can be enhanced by using semantic process templates to capture the semantic requirements …

Tontogen: A Synthetic Data Set Generator For Semantic Web Applications, Matthew Perry

Kno.e.sis Publications

No abstract provided.

Web-Based Independent Study Program, Darryl Dwaine Scroggins

Theses Digitization Project

The Web-based Independent Study Program (WISP) is an on-line database program used to create and store educational records for members of Dikaios. (Dikaios is a Christian educators association that offers an independent study program.) The database allows home educators to create, store, edit, view, and print the forms and records that are required by Dakaios administrators and by the state of California. Further, the database helps students and home educators monitor student progress towards meeting high school graduation requirements.

Senior Health Care System, Meng-Chun Ling

Theses Digitization Project

Senior Health Care System (SHCS) is created for users to enter participants' conditions and store information in a central database. When users are ready for quarterly assessments the system generates a simple summary that can be reviewed, modified, and saved as part of the summary assessments, which are required by Federal and California law.

Graduate Advising System: Application Component, Kyle Rene Rotte

Theses Digitization Project

This project utilized PHP to write an application component for the Graduate Advising System (GRADS) computer program used by the Computer Science Department at California State University, San Bernardino. This application component allows the applicant to apply to the Computer Science program and to track the progress of his or her application. It allows people writing recommendations on the student's behalf to submit the recommendations via GRADS. It allows the Graduate Assistant to monitor the status of the application. It allows the Coordinator to review and evaluate the submitted application/ recommendation package.

From Semantic Search & Integration To Analytics, Amit P. Sheth

Kno.e.sis Publications

Semantics is seen as the key ingredient in the next phase of the Web infrastructure as well as the next generation of enterprise content management. Ontology is the centerpiece of the most prevalent semantic technologies and provides the basis of representing, acquiring, and utilizing knowledge. With the availability of several commercial products and many research tools, specifications and increasing adoption of Semantic Web standards such as RDF for metadata and OWL for ontology representation, ontology-driven techniques and systems have already enabled a new generation of industry strength semantic applications. In particular, Semagix's Freedom has powered applications in leading verticals such …

The Edam Project: Mining Atmospheric Aerosol Datasets, Raghu Ramakrishnan, James J. Schauer, Lei Chen, Zheng Huang, Martin M. Shafer, Deborah S. Gross, David R. Musicant

Chemistry Faculty Work

Data mining has been a very active area of research in the database, machine learning, and mathematical programming communities in recent years. EDAM (Exploratory Data Analysis and Management) is a joint project between researchers in Atmospheric Chemistry and Computer Science at Carleton College and the University of Wisconsin-Madison that aims to develop data mining techniques for advancing the state of the art in analyzing atmospheric aerosol datasets. There is a great need to better understand the sources, dynamics, and compositions of atmospheric aerosols. The traditional approach for particle measurement, which is the collection of bulk samples of particulates on filters, …

The "Best K" For Entropy-Based Categorical Data Clustering, Keke Chen, Ling Liu

Kno.e.sis Publications

With the growing demand on cluster analysis for categorical data, a handful of categorical clustering algorithms have been developed. Surprisingly, to our knowledge, none has satisfactorily addressed the important problem for categorical clustering – how can we determine the best K number of clusters for a categorical dataset? Since categorical data does not have the inherent distance function as the similarity measure, traditional cluster validation techniques based on the geometry shape and density distribution cannot be applied to answer this question. In this paper, we investigate the entropy property of the categorical data and propose a BkPlot method for determining …

Jess – A Java Security Scanner For Eclipse, Russell Spitler

Honors Theses

Secure software is the responsibility of every developer. In order to help a developer with this responsibility there are many automated source code security auditors. These tools perform a variety of functions, from finding calls to insecure functions to poorly generated random numbers. These programs have existed for years and perform the security audit with varying degrees of success.

Largely missing in the world of programming is such a security auditor for the Java programming language. Currently, Fortify Software produces the only Java source code security auditor; this is a commercially available package.

This void is what inspired JeSS, Java …

A Generative Programming Approach To Interactive Information Retrieval: Insights And Experiences, Saverio Perugini, Naren Ramakrishnan

Computer Science Faculty Publications

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 …

Recommender Systems Research, Saverio Perugini

Computer Science Faculty Publications

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 …

The Good, Bad And The Indifferent: Explorations In Recommender System Health, Benjamin J. Keller, Sun-Mi Kim, N. Srinivas Vemuri, Naren Ramakrishnan, Saverio Perugini

Computer Science Faculty Publications

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 …

A Uniform Approach To Logic Programming Semantics, Pascal Hitzler, Matthias Wendt

Computer Science and Engineering Faculty Publications

Part of the theory of programming and nonymonotonic reasoning concerns the study of fixed-point semantics for these paradigms. Several different semantics have been proposed during the last two decades, and some have been more successful and acknowledged than others. The rationales behind those various semantics have been manifold, depending on one's point of view, which may be that of a programmer or inspired by commonsense reasoning, and consequently the constructions which lead to these semantics are technically very diverse, and the exact relationships between them have not yet been fully understood. In this paper, we present a conceptually new method, …

Dlp - An Introduction, Denny Vrandecic, Pascal Hitzler, Rudi Studer

Computer Science and Engineering Faculty Publications

DLP - Description Logic Programs - is the name for the common language that is able to integrate knowledge bases described in Description Logic with Logic Programs. In this introduction, we offer a very short overview of DLP, the motivation for it, the benefits it offers and how to use it.

Glyde - An Expressive Xml Standard For The Representation Of Glycan, Satya S. Sahoo, Christopher Thomas, Amit P. Sheth, Cory Andrew Henson, William S. York

Kno.e.sis Publications

The amount of glycomics data being generated is rapidly increasing as a result of improvements in analytical and computational methods. Correlation and analysis of this large, distributed data set requires an extensible and flexible representational standard that is also ‘understood’ by a wide range of software applications. An XML-based data representation standard that faithfully captures essential structural details of a glycan moiety along with additional information (such as data provenance) to aid the interpretation and usage of glycan data, will facilitate the exchange of glycomics data across the scientific community. To meet this need, we introduce GLYcan Data Exchange (GLYDE) …

Semantic Web & Semantic Web Services: Applications In Healthcare And Scientific Research, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Discovering Informative Subgraphs In Rdf Graphs, William H. Milnor, Cartic Ramakrishnan, Matthew Perry, Amit P. Sheth, John A. Miller, Krzysztof Kochut

Kno.e.sis Publications

Discovering patterns in graphs has long been an area of interest. In most contemporary approaches to such pattern discovery either quantitative anomalies or frequency of substructure is used to measure the interestingness of a pattern. In this paper we address the issue of discovering informative sub-graphs within RDF graphs. We motivate our work with an example related to Semantic Search. A user might pose a question of the form: ' What are the most relevant ways in which entity X is related to entity Y?' the response to which is a subgraph connecting X to Y. Relevance of the …

Adaptive Decision Support For Academic Course Scheduling Using Intelligent Software Agents, Prithviraj Dasgupta, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Publications

Academic course scheduling is a complex operation that requires the interaction between different users including instructors and course schedulers to satisfy conflicting constraints in an optimal manner. Traditionally, this problem has been addressed as a constraint satisfaction problem where the constraints are stationary over time. In this paper, we address academic course scheduling as a dynamic decision support problem using an agent-enabled adaptive decision support system. In this paper, we describe the Intelligent Agent Enabled Decision Support (IAEDS) system, which employs software agents to assist humans in making strategic decisions under dynamic and uncertain conditions. The IAEDS system has a …

Social Indicators In Cleveland's Ward 17, Mark Salling, Sharon Bliss, Joseph Ahern

All Maxine Goodman Levin School of Urban Affairs Publications

No abstract provided.

Towards Persistent Resource Identification With The Uniform Resource Name, Luke Brown

Theses : Honours

The exponential growth of the Internet, and the subsequent reliance on the resources it connects, has exposed a clear need for an Internet identifier which remains accessible over time. Such identifiers have been dubbed persistent identifiers owing to the promise of reliability they imply. Persistent naming systems exist at present, however it is the resolution of these systems into what Kunze, (2003) calls "persistent actionable identifiers" which is the focus of this work. Actionable identifiers can be thought of as identifiers which are accessible in a simple fashion such as through a web browser or through a specific application. This …

Ontology-Assisted Mining Of Rdf Documents, Tao Jiang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Resource description framework (RDF) is becoming a popular encoding language for describing and interchanging metadata of web resources. In this paper, we propose an Apriori-based algorithm for mining association rules (AR) from RDF documents. We treat relations (RDF statements) as items in traditional AR mining to mine associations among relations. The algorithm further makes use of a domain ontology to provide generalization of relations. To obtain compact rule sets, we present a generalized pruning method for removing uninteresting rules. We illustrate a potential usage of AR mining on RDF documents for detecting patterns of terrorist activities. Experiments conducted based on …

Exploring Bit-Difference For Approximate Knn Search In High-Dimensional Databases, Bin Cui, Heng Tao Shen, Jialie Shen, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

In this paper, we develop a novel index structure to support effcient approximate k-nearest neighbor (KNN) query in high-dimensional databases. In high-dimensional spaces, the computational cost of the distance (e.g., Euclidean distance) between two points contributes a dominant portion of the overall query response time for memory processing. To reduce the distance computation, we first propose a structure (BID) using BIt-Difference to answer approximate KNN query. The BID employs one bit to represent each feature vector of point and the number of bit-difference is used to prune the further points. To facilitate real dataset which is typically skewed, we enhance …

Linear Correlation Discovery In Databases: A Data Mining Approach, Cecil Chua, Roger Hsiang-Li Chiang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Very little research in knowledge discovery has studied how to incorporate statistical methods to automate linear correlation discovery (LCD). We present an automatic LCD methodology that adopts statistical measurement functions to discover correlations from databases’ attributes. Our methodology automatically pairs attribute groups having potential linear correlations, measures the linear correlation of each pair of attribute groups, and confirms the discovered correlation. The methodology is evaluated in two sets of experiments. The results demonstrate the methodology’s ability to facilitate linear correlation discovery for databases with a large amount of data.

Applying Scenario-Based Design And Claim Analysis To The Design Of A Digital Library Of Geography Examination Resources, Yin-Leng Theng, Dion Hoe-Lian Goh, Ee Peng Lim, Zehua Liu, Ming Yin, Natalie Lee-San Pang, Patricia Bao-Bao Wong

Research Collection School Of Computing and Information Systems

This paper describes the application of Carroll’s scenario-based design and claims analysis as a means of refinement to the initial design of a digital library of geographical resources (GeogDL) to prepare Singapore students to take a national examination in geography. GeogDL is built on top of G-Portal, a digital library providing services over geospatial and georeferenced Web content. Beyond improving the initial design of GeogDL, a main contribution of the paper is making explicit the use of Carroll’s strong theory-based but undercapitalized scenario-based design and claims analysis that inspired recommendations for the refinement of GeogDL. The paper concludes with an …

Systems Analysis And Design: Should We Be Researching What We Teach?, A. Bajaj, D. Batra, A. Hevner, J. Parsons, Keng Siau

Research Collection School Of Computing and Information Systems

A guiding premise of academic scholarship is that knowledge gained from first-hand research experience is disseminated to students via the classroom. However, that valuable connection is lost when professors are not researching what they teach. In this paper, we explore issues of mismatch between teaching and research in the Information Systems (IS) discipline. Specifically, while systems analysis and design (SA&D) is an integral topic in IS curricula, this topic is the research specialty of few IS professors. This situation is reflected by the low number of research publications in this area; particularly in the leading mainstream IS journals. We characterize …