Digital Commons Network^™

Ontology-Based Business Process Customization For Composite Web Services, Qianhui (Althea) Liang, Xindong Wu, E. K. Park, T. Khoshgoftaar, C. Chi

Research Collection School Of Computing and Information Systems

A key goal of the Semantic Web is to shift social interaction patterns from a producer-centric paradigm to a consumer-centric one. Treating customers as the most valuable assets and making the business models work better for them are at the core of building successful consumer-centric business models. It follows that customizing business processes constitutes a major concern in the realm of a knowledge-pull-based human semantic Web. This paper conceptualizes the customization of service-based business processes leveraging the existing knowledge of Web services and business processes. We represent this conceptualization as a new Extensible Markup Language (XML) markup language Web Ontology …

Quality-Aware Collaborative Question Answering: Methods And Evaluation, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang

Research Collection School Of Computing and Information Systems

Community Question Answering (QA) portals contain questions and answers contributed by hundreds of millions of users. These databases of questions and answers are of great value if they can be used directly to answer questions from any user. In this research, we address this collaborative QA task by drawing knowledge from the crowds in community QA portals such as Yahoo! Answers. Despite their popularity, it is well known that answers in community QA portals have unequal quality. We therefore propose a quality-aware framework to design methods that select answers from a community QA portal considering answer quality in addition to …

A Formal Concept Analysis Approach To Association Rule Mining: The Quicl Algorithms, David T. Smith

CCAC Theses and Dissertations

Association rule mining (ARM) is the task of identifying meaningful implication rules exhibited in a data set. Most research has focused on extracting frequent item (FI) sets and thus fallen short of the overall ARM objective. The FI miners fail to identify the upper covers that are needed to generate a set of association rules whose size can be exploited by an end user. An alternative to FI mining can be found in formal concept analysis (FCA), a branch of applied mathematics. FCA derives a concept lattice whose concepts identify closed FI sets and connections identify the upper covers. However, …

Appropriate Prosodic Variation Is Valued By Users, Rafael Escalante-Ruiz

Open Access Theses & Dissertations

Spoken dialog systems today do not vary the prosody of their utterances, although prosody is known to have many useful expressive functions. In a corpus of memory quizzes, I identified eleven dimensions of prosodic variation, each with its own expressive function. I identified the situations in which each was used, and how to detect these situations from the dialog context and the prosody of the interlocutor's previous utterance. I implemented the resulting response rules and had 21 users interact with two versions of the system. Overall they preferred the version in which the prosodic forms of the acknowledgments were chosen …

An Optimization Approach For The Cascade Vulnerability Problem, Christian Servin

Open Access Theses & Dissertations

In inter-connected systems, where several computers share information with each other, problems may arise when inappropriate information starts to flow through. For example, let us consider a simple scenario of a university composed of three departments: payroll, financial aid, and academic services. We know that the payroll department deals with sensitive information, such as social security numbers, dates of birth, amounts of wages, etc. The financial aid department may use information that payroll owns. Similarly, the academic department communicates with the financial aid department. An intruder can take advantage of this network connectivity and create an inappropriate flow of information …

Synthesizing Correlated Rss News Articles Based On A Fuzzy Equivalence Relation, Yiu-Kai D. Ng, Maria Soledad Pera

Faculty Publications

Tens of thousands of news articles are posted on-line each day, covering topics from politics to science to current events. To better cope with this overwhelming volume of information, RSS (news) feeds are used to categorize newly posted articles. Nonetheless, most RSS users must filter through many articles within the same or different RSS feeds to locate articles pertaining to their particular interests. Due to the large number of news articles in individual RSS feeds, there is a need for further organizing articles to aid users in locating non-redundant, informative, and related articles of interest quickly. In this paper, we …

Toward Social Search: From Explicit To Implicit Collaboration To Predict Users' Interests, Luca Longo, Stephen Barrett

Conference papers

Inspection methods and cheap self-reporting procedures have been significantly employed in the field of Human- Computer Interaction for assessing the usability of interfaces, systems and technologies. However, there is a tendency to overlook aspects related to the context and features of the users during the usability assessment process. This research introduces the concept of mental workload as an aid to enhance usability measurement. A user-study has been designed and executed in the context of human-web interaction. The aim was to investigate the relationship between the perception of usability of three popular web-sites, and the mental workload imposed by a set …

Sentiment Classification Of Reviews Using Sentiwordnet, Bruno Ohana, Brendan Tierney

Conference papers

Sentiment classification concerns the use of automatic methods for predicting the orientation of subjective content on text documents, with applications on a number of areas including recommender and advertising systems, customer intelligence and information retrieval. SentiWordNet is an opinion lexicon derived from the WordNet database where each term is associated with numerical scores indicating positive and negative sentiment information. This research presents the results of applying the SentiWordNet lexical resource to the problem of automatic sentiment classification of film reviews. Our approach comprises counting positive and negative term scores to determine sentiment orientation, and an improvement is presented by building …

Chaos And Uncertainty, M. Thulasidas

Research Collection School Of Computing and Information Systems

The end of 2008 in the finance industry can be summarized in two words – chaos and uncertainty. The subprime crisis, where everybody lost; the dizzying commodity price movements; the pink slip syndrome; the spectacular bank busts; and the gargantuan bail-outs all vouch for it.

The Effects Of Technology On Literacy(S), Thomas Glen Petersen

Masters Theses

"One of the challenges when measuring the effects of technology on literacy(s) is finding a control group where technology; does not play a major role in the culture. The Amish successfully live in a Technocracy where mechanical/electronic tools are used only when absolutely necessary; the Amish are not dependent on them for survival. The crux of the Amish philosophy is humility, serving the community and serving God. Ironically, they have suffered tremendous repercussions for adopting a wholesome, selfless lifestyle which is contrary to most popular world views, regardless of religious or spiritual views"--Purpose, page 40.

Computer-Aided Reasoning About Knowledge And Justifications, Natalia Novak

Dissertations, Theses, and Capstone Projects

In the first Chapter we compare two well-known type-based computer frameworks for computer aided logical reasoning and verification: MetaPRL and Coq. In particular, we implement in MetaPRL the Calculus of Inductive Constructions which is the theoretical base for Coq. This work has shown the common points of MetaPRL and Coq, and revealed their principal methodological differences. A possible application of this work is a possibility to perform re-validation in MetaPRL of the existing library of Coq proofs which could help to build more trust in the latter.

Chapter 2 is the main contribution of the dissertation. It contains the description …

Expressiveness And Effectiveness Of Program Comprehension: Thoughts On Future Research Directions, Jonathan I. Maletic, Huzefa Kagdi

Computer Science Faculty Research & Creative Works

A number of research challenges in the area of program comprehension are presented. the expressiveness and effectiveness of program comprehension are discussed, and research directions are organized along these two axes. Both fundament research issues are raised along with new applications for program comprehension methods. the work advocates the investigation of better measures, further empirical studies, and controlled experiments to assess the effectiveness of program comprehension techniques © 2008 IEEE.

Ontology Generation, Information Harvesting And Semantic Annotation For Machine-Generated Web Pages, Cui Tao

Theses and Dissertations

The current World Wide Web is a web of pages. Users have to guess possible keywords that might lead through search engines to the pages that contain information of interest and browse hundreds or even thousands of the returned pages in order to obtain what they want. This frustrating problem motivates an approach to turn the web of pages into a web of knowledge, so that web users can query the information of interest directly. This dissertation provides a step in this direction and a way to partially overcome the challenges. Specifically, this dissertation shows how to turn machine-generated web …

Nowhere To Hide: Finding Plagiarized Documents Based On Sentence Similarity, Nathaniel Gustafson, Yiu-Kai D. Ng, Maria Soledad Pera

Faculty Publications

Plagiarism is a serious problem that infringes copyrighted documents/materials, which is an unethical practice and decreases the economic incentive received by authors (owners) of the original copies. Unfortunately, plagiarism is getting worse due to the increasing number of online publications on the Web, which facilitates locating and paraphrasing information. In solving this problem, we propose a novel plagiarism-detection method, called SimPaD, which (i) establishes the degree of resemblance between any two documents D1 and D2 based on their sentence-to-sentence similarity computed by using pre-defined word-correlation factors, and (ii) generates a graphical view of sentences that are similar (or the same) …

Growing Fields Of Interest: Using An Expand And Reduce Strategy For Domain Model Extraction, Christopher Thomas, Pankaj Mehra, Roger Brooks, Amit P. Sheth

Kno.e.sis Publications

Domain hierarchies are widely used as models underlying information retrieval tasks. Formal ontologies and taxonomies enrich such hierarchies further with properties and relationships associated with concepts and categories but require manual effort; therefore they are costly to maintain, and often stale. Folksonomies and vocabularies lack rich category structure and are almost entirely devoid of properties and relationships. Classification and extraction require the coverage of vocabularies and the alterability of folksonomies and can largely benefit from category relationships and other properties. With Doozer, a program for building conceptual models of information domains, we want to bridge the gap between the vocabularies …

An Analysis Of Document Retrieval And Clustering Using An Effective Semantic Distance Measure, Nathan Scott Davis

Theses and Dissertations

As large amounts of digital information become more and more accessible, the ability to effectively find relevant information is increasingly important. Search engines have historically performed well at finding relevant information by relying primarily on lexical and word based measures. Similarly, standard approaches to organizing and categorizing large amounts of textual information have previously relied on lexical and word based measures to perform grouping or classification tasks. Quite often, however, these processes take place without respect to semantics, or word meanings. This is perhaps due to the fact that the idea of meaningful similarity is naturally qualitative, and thus difficult …

Evaluating Online Health Information: Beyond Readability Formulas, Gondy Leroy, Stephen Helmreich, James Cowie, Trudi Miller '08, Wei Zheng '08

CGU Faculty Publications and Research

Although understanding health information is important, the texts provided are often difficult to understand. There are formulas to measure readability levels, but there is little understanding of how linguistic structures contribute to these difficulties. We are developing a toolkit of linguistic metrics that are validated with representative users and can be measured automatically. In this study, we provide an overview of our corpus and how readability differs by topic and source. We compare two documents for three groups of linguistic metrics. We report on a user study evaluating one of the differentiating metrics: the percentage of function words in a …

Relationship Web: Trailblazing, Analytics And Computing For Human Experience, Amit P. Sheth

Kno.e.sis Publications

This panel presentation was give at the 27th International Conference on Conceptual Modeling (ER 2008), Barcelona, Spain, October 20-23, 2008.

Using Vagueness Measures To Re-Rank Documents Retrieved By A Fuzzy Set Information Retrieval Model, Stephen Lynn, Yiu-Kai D. Ng

Faculty Publications

Traditional information retrieval (IR) systems evaluate user queries and retrieve/rank documents based on matching keywords in user queries with words in documents. These exact word-matching and ranking approaches ignore too many relevant documents that do not contain the exact keywords as specified in a user query. Instead of considering these traditional approaches, we propose to retrieve documents using a fuzzy set IR model and rank retrieved documents for any vague query using the “vagueness score” of the documents based on the word senses as defined in WordNet. Using the vagueness scores, we rank the most highest “relevant” documents of a …

Using English Information In Non-English Web Search, Wei Gao, Wei Gao, Ming Zhou

Research Collection School Of Computing and Information Systems

The leading web search engines have spent a decade building highly specialized ranking functions for English web pages. One of the reasons these ranking functions are effective is that they are designed around features such as PageRank, automatic query and domain taxonomies, and click-through information, etc. Unfortunately, many of these features are absent or altered in other languages. In this work, we show how to exploit these English features for a subset of Chinese queries which we call linguistically non-local (LNL). LNL Chinese queries have a minimally ambiguous English translation which also functions as a good English query. We first …

Selection Of Concept Detectors For Video Search By Ontology-Enriched Semantic Spaces, Xiao-Yong Wei, Chong-Wah Ngo, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

This paper describes the construction and utilization of two novel semantic spaces, namely Ontology-enriched Semantic Space (OSS) and Ontology-enriched Orthogonal Semantic Space (OS2), to facilitate the selection of concept detectors for video search. These two semantic spaces are enriched with ontology knowledge, while emphasizing consistent and uniform comparison of ontological relatedness among concepts for query-to-concept mapping. OS2, in addition to being a linear space like OSS, also guarantees orthogonality of the semantic space. Compared with other ontology reasoning measures, both spaces are capable of providing platforms that offer a global view of concept inter-relatedness, by allowing evaluation of concept similarity …

Video Event Detection Using Motion Relativity And Visual Relatedness, Feng Wang, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Event detection plays an essential role in video content analysis. However, the existing features are still weak in event detection because: i) most features just capture what is involved in an event or how the event evolves separately, and thus cannot completely describe the event; ii) to capture event evolution information, only motion distribution over the whole frame is used which proves to be noisy in unconstrained videos; iii) the estimated object motion is usually distorted by camera movement. To cope with these problems, in this paper, we propose a new motion feature, namely Expanded Relative Motion Histogram of Bag-ofVisual-Words …

Fusing Semantics, Observability, Reliability And Diversity Of Concept Detectors For Video Search, Xiao-Yong Wei, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Effective utilization of semantic concept detectors for large-scale video search has recently become a topic of intensive studies. One of main challenges is the selection and fusion of appropriate detectors, which considers not only semantics but also the reliability of detectors, observability and diversity of detectors in target video domains. In this paper, we present a novel fusion technique which considers different aspects of detectors for query answering. In addition to utilizing detectors for bridging the semantic gap of user queries and multimedia data, we also address the issue of "observability gap" among detectors which could not be directly inferred …

Ontology-Based Visual Word Matching For Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper proposes a novel approach to exploit the ontological relationship of visual words by linguistic reasoning. A visual word ontology is constructed to facilitate the rigorous evaluation of linguistic similarity across visual words. The linguistic similarity measurement enables cross-bin matching of visual words, compromising the effectiveness and speed of conventional keypoint matching and bag-of-word approaches. A constraint EMD is proposed and experimented to efficiently match visual words. Empirical findings indicate that the proposed approach offers satisfactory performance to near-duplicate retrieval, while still enjoying the merit of speed efficiency compared with other techniques.

Word Sense Disambiguation In Biomedical Ontologies With Term Co-Occurrence Analysis And Document Clustering, Bill Andreopoulos, Dimitra Alexopoulou, Michael Schroeder

Faculty Publications, Computer Science

With more and more genomes being sequenced, a lot of effort is devoted to their annotation with terms from controlled vocabularies such as the GeneOntology. Manual annotation based on relevant literature is tedious, but automation of this process is difficult. One particularly challenging problem is word sense disambiguation. Terms such as |development| can refer to developmental biology or to the more general sense. Here, we present two approaches to address this problem by using term co-occurrences and document clustering. To evaluate our method we defined a corpus of 331 documents on development and developmental biology. Term co-occurrence analysis achieves an …

T-Plausibility: Semantic Preserving Text Sanitization, Wei Jiang, Mummoorthy Murugesan, Chris Clifton, Luo Si

Department of Computer Science Technical Reports

No abstract provided.

Collecting Open Source Intelligence Via Tailored Information Delivery Systems, William Sousan, Qiuming Zhu, Ryan Nickell, William Mahoney, Peter Hospodka

Computer Science Faculty Publications

The Internet offers a plethora of freely available information for possible use in Open Source Intelligence (OSINT) operations. However, along with this information come challenges in finding relevant information and overcoming information overload. This paper presents the results of an ongoing research in a Tailored Information Delivery Services (TIDS) system that aids users in retrieving relevant information through various open intelligence sources. The TIDS provides a semantics-based query constructor that operates in a “What You Get is What You Need (WYGIWYN^TM)” fashion and builds ontology based information tagging, theme extractor, and contextual model.

Text Analytics For Semantic Computing - The Good, The Bad And The Ugly, Meenakshi Nagarajan, Cartic Ramakrishnan, Amit P. Sheth

Kno.e.sis Publications

This tutorial was give at the Second IEEE International Conference on Semantic Computing Santa Clara, CA, USA - August 4-7, 2008.

Similarity Assessment Techniques, Michael A. Zang, Adam Gray, Michael Hobbs, Jens G. Pohl

Collaborative Agent Design (CAD) Research Center

This paper serves as a layman’s introduction to similarity assessment techniques, their distinction from contemporary computing paradigms, and their real-world applications. The following content derives from the experience gained by the authors in applying similarity assessment techniques to resolve the real-world problems of CDM customers, in particular those faced by the United States Transportation Command (USTRANSCOM).

A Simplex Model For Layered Niche Networks, Philip Fraundorf

Physics Faculty Works

No abstract provided.