Digital Commons Network^™

A Proposed Syntax For Minimotif Semantics, Version 1., Jay Vyas, Ronald J. Nowling, Mark W. Maciejewski, Sanguthevar Rajasekaran, Michael R. Gryk, Martin R. Schiller

Life Sciences Faculty Research

BACKGROUND:

One of the most important developments in bioinformatics over the past few decades has been the observation that short linear peptide sequences (minimotifs) mediate many classes of cellular functions such as protein-protein interactions, molecular trafficking and post-translational modifications. As both the creators and curators of a database which catalogues minimotifs, Minimotif Miner, the authors have a unique perspective on the commonalities of the many functional roles of minimotifs. There is an obvious usefulness in standardizing functional annotations both in allowing for the facile exchange of data between various bioinformatics resources, as well as the internal clustering of sets of …

Measuring Method Complexity: Uml Versus Bpmn, Jan Recker, Michael Zur Muehlen, Keng Siau, John Erickson, Marta Indulska

Research Collection School Of Computing and Information Systems

Graphical models are used to depict relevant aspects of real-world domains intended to be supported by an information system. Various approaches for modeling exist and approaches such as object-oriented and process-oriented modeling methods are in widespread use. These modeling methods differ in their expressive power as well as in their complexity of use, thereby leading to an important investment decision for organizations seeking to conduct modeling projects. In this paper, we used an established approach for evaluating the complexity of conceptual modeling methods and compared two important industry standards for modeling, Unified Modeling Language and Business Process Modeling Notation, based …

Multi-Task Transfer Learning For Weakly-Supervised Relation Extraction, Jing Jiang

Research Collection School Of Computing and Information Systems

Creating labeled training data for relation extraction is expensive. In this paper, we study relation extraction in a special weakly-supervised setting when we have only a few seed instances of the target relation type we want to extract but we also have a large amount of labeled instances of other relation types. Observing that different relation types can share certain common structures, we propose to use a multi-task learning method coupled with human guidance to address this weakly-supervised relation extraction problem. The proposed framework models the commonality among different relation types through a shared weight vector, enables knowledge learned from …

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

Computer Science Faculty Research & Creative Works

Text documents play significant roles in decision making and scientific research. Under federal regulations, documents (e.g., pathology records) containing personally identifiable information cannot be shared freely, unless properly sanitized. Generally speaking, document sanitization consists of finding and hiding personally identifiable information. The first task has received much attention from the research community, but the main strategy for the second task has been to simply remove personal identifiers and very sensitive information (e.g., diseases and treatment). It is not hard to see that if important information (e.g., diagnoses and personal medical histories) is completely removed from pathology records, these records are …

Extracting Paraphrases Of Technical Terms From Noisy Parallel Software Corpus, Xiaoyin Wang, David Lo, Jing Jiang, Lu Zhang, Hong Mei

Research Collection School Of Computing and Information Systems

In this paper, we study the problem of extracting technical paraphrases from a parallel software corpus, namely, a collection of duplicate bug reports. Paraphrase acquisition is a fundamental task in the emerging area of text mining for software engineering. Existing paraphrase extraction methods are not entirely suitable here due to the noisy nature of bug reports. We propose a number of techniques to address the noisy data problem. The empirical evaluation shows that our method significantly improves an existing method by upto 58%

The Potential Use Of Slow-Down Technology To Improve Pronounciation Of English For International Communication, Bunny Richardson

Doctoral

The focus of this research is on oral communication between L1 (first language) and L2 (second language) English users - to determine whether an algorithm which slows down speech can increase the intelligibility of speech between interlocutors for EIC (English for International Communication). The slow-down facility is a CALL tool which slows down speech without tonal distortion. It allows English language learners more processing time to hear individual phonemes as produced in the stream of connected speech, to help them hear and produce phonemes more accurately and thus more intelligibly. The study involved five tests, all concerned with the intelligibility …

Large-Scale Near-Duplicate Web Video Search: Challenge And Opportunity, Wan-Lei Zhao, Song Tan, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

The massive amount of near-duplicate and duplicate web videos has presented both challenge and opportunity to multimedia computing. On one hand, browsing videos on Internet becomes highly inefficient for the need to repeatedly fast-forward videos of similar content. On the other hand, the tremendous amount of somewhat duplicate content also makes some traditionally difficult vision tasks become simple and easy. For example, annotating pictures can be as simple as recycling the tags of Internet images retrieved from image search engines. Such tasks, of either to eliminate or to recycle near-duplicates, can usually be achieved by the nearest neighbor search of …

Holism And Human History, Martin Zwick

Complex Systems Faculty Publications and Presentations

This paper uses a systems-theoretic model to structure an account of human history. According to the model, a process, after its beginning and early development, often reaches a critical stage where it encounters some limitation. If the limitation is overcome, development does not face a comparable challenge until a second critical juncture is reached, where obstacles to further advance are more severe. At the first juncture, continued development requires some complexity-managing innovation; at the second, it needs some event of systemic integration in which the old organizing principle of the process is replaced by a new principle. Overcoming the first …

The Effects Of Introspection On Computer Security Policies, Stephanie A. Trudeau

Dartmouth College Undergraduate Theses

What does it mean to be an expert? And what makes an expert more capable than a non-expert when it comes to evaluating and articulating their impressions about something as commonly practiced as food tasting? How do we explain those behaviors that humans perform very well, but don't quite know why? Studies have shown that there exists a class of activities that we as humans execute well intuitively, but that we perform much worse upon introspection. Evidence supports the claim that the act of introspection actually causes us to do more poorly at these tasks. My goal is to apply …

Applying Computational Models Of Spatial Prepositions To Visually Situated Dialog, John D. Kelleher, Fintan Costello

Articles

This article describes the application of computational models of spatial prepositions to visually situated dialog systems. In these dialogs, spatial prepositions are important because people often use them to refer to entities in the visual context of a dialog. We first describe a generic architecture for a visually situated dialog system and highlight the interactions between the spatial cognition module, which provides the interface to the models of prepositional semantics, and the other components in the architecture. Following this, we present two new computational models of topological and projective spatial prepositions. The main novelty within these models is the fact …

Language Modeling Approaches To Information Retrieval, Protima Banerjee, Hyoil Han

Computer Sciences and Electrical Engineering Faculty Research

This article surveys recent research in the area of language modeling (sometimes called statistical language modeling) approaches to information retrieval. Language modeling is a formal probabilistic retrieval framework with roots in speech recognition and natural language processing. The underlying assumption of language modeling is that human language generation is a random process; the goal is to model that process via a generative statistical model.

In this article, we discuss current research in the application of language modeling to information retrieval, the role of semantics in the language modeling framework, cluster-based language models, use of language modeling for XML retrieval and …

On The Role Of Assertions For Conceptual Modeling As Enablers Of Composable Simulation Solutions, Robert Dennis King

Computational Modeling & Simulation Engineering Theses & Dissertations

This research provides a much needed systematic review of the roles that assertions play in model composability and simulation interoperability. In doing so, this research contributes a partial solution to one of the problems of model composability and simulation interoperability—namely, why do simulation systems fail to achieve the maximum level of interoperability possible? It demonstrates the importance of the assertions that are made during model development and simulation implementation, particularly as they reflect the unique viewpoint of each developer or user. It hypothesizes that it is possible to detect composability conflicts by means of a four-step process developed by the …

Qualcomm V. Broadcom: Implications For Electronic Discovery, Milton H. Luoma, Vicki M. Luoma

Australian Digital Forensics Conference

Electronic discovery has been the source of difficult challenges for courts, lawyers, and litigants from the beginning. The methods, document formats, and scope of electronic discovery have all contributed to the difficulties encountered. The seminal case in the United States that underscores the nature of the difficulties and challenges facing lawyers and courts in electronic discovery is Qualcomm v. Broadcom. While the case has been cited as an example of the ethical issues facing lawyers who do not follow the rules of discovery, the lessons go well beyond ethical issues. All major common law countries, including Australia, New Zealand, United …

The Importance Of Being Neural-Symbolic - A Wilde Position, Pascal Hitzler, Kai-Uwe Kuhnberger

Computer Science and Engineering Faculty Publications

We argue that Neural-Symbolic Integration is a topic of central importance for the advancement of Artificial General Intelligence.

Visual Word Proximity And Linguistics For Semantic Video Indexing And Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Bag-of-visual-words (BoW) has recently become a popular representation to describe video and image content. Most existing approaches, nevertheless, neglect inter-word relatedness and measure similarity by bin-to-bin comparison of visual words in histograms. In this paper, we explore the linguistic and ontological aspects of visual words for video analysis. Two approaches, soft-weighting and constraint-based earth mover’s distance (CEMD), are proposed to model different aspects of visual word linguistics and proximity. In soft-weighting, visual words are cleverly weighted such that the linguistic meaning of words is taken into account for bin-to-bin histogram comparison. In CEMD, a cross-bin matching algorithm is formulated such …

Why Gujarat Needs Much Better Higher Education & Research To Succeed In Knowledge Economy & What We Can Do About It?, Amit P. Sheth, Kamlesh Lulla, Sanjay Chaudhary

Kno.e.sis Publications

This white paper distills the deliberations on the role of higher education and research as a key enabler of a Knowledge based Society. In particular it discusses (a) the importance of higher quality PhDs for building a knowledge society, (b) the initiatives and progress in competing economies in higher education and research, (c) where Gujarat stands in comparison, and (d) some recommendations on what Gujarat can do to enable timely progress towards building a knowledge based society and economy. These deliberations were conducted in conjunction with the International Conference on 'Reconnecting Gujarati Diaspora with its Homeland: Contribution to its Development …

Ontologies And Rules, Pascal Hitzler, Bijan Parsia

Computer Science and Engineering Faculty Publications

Ontologies and rules are two established paradigms in knowledge modelling, and play an important role for the Semantic Web. In this chapter, we present an introduction to common approaches for combining OWL ontologies and rules. In particular, we cover the Semantic Web Rules Language SWRL and Description Logic Programs DLP, and give pointers to the literature.

User-Generated Content On Social Media Challenges, Opportunities, Meenakshi Nagarajan

Kno.e.sis Publications

Understanding and exploiting user generated (textual) content (UGC) on social media is at the forefront of information management challenges today. The variety of UGC in detailed blog commentaries, collaborative wiki-content, online conversations, short messages in micro-blogs etc., are powering several personalization, monetization, crowd/business intelligence applications, and also providing an electronic microscope on social phenomena at an extraordinary scale. Certain characteristics of UGC however, necessitate key computational linguistic interventions before systems can tap into this data. A large portion of language found on social media is in the Informal English domain a blend of abbreviations, slang and context dependent terms delivered …

Semantics-Empowered Social Computing, Amit P. Sheth, Meenakshi Nagarajan

Kno.e.sis Publications

In this article, we discuss some of the challenges in marking-up or annotating UGC, a first step toward the realization of the social semantic Web. Using examples from real- world UGC, we show how domain knowledge can effectively complement statistical natural language processing techniques for metadata creation.

Folklore And The Internet: Vernacular Expression In A Digital World, Trevor J. Blank

All USU Press Publications

Folklore and the Internet is a pioneering examination of the folkloric qualities of the World Wide Web, e-mail, and related digital media. It shows that folk culture, sustained by a new and evolving vernacular, has been a key, since the Internetýs beginnings, to language, practice, and interaction online. Users of many sorts continue to develop the Internet as a significant medium for generating, transmitting, documenting, and preserving folklore. In a set of new, insightful essays, contributors Trevor J. Blank, Simon J. Bronner, Robert Dobler, Russell Frank, Gregory Hansen, Robert Glenn Howard, Lynne S. McNeill, Elizabeth Tucker, and William Westerman showcase …

Rules And Insights: Connecting The Mathematical And Linguistic Abilities Of C.S. Lewis, Kim Regnier Jongerius

ACMS Journal 2008-2009

While most biographical works on C.S. Lewis give passing reference to Lewis' problems with elementary mathematics, few have made an attempt at diagnosing the difficulty or exploring its impact on his writing. A careful study of family correspondence, however, makes it clear that his learning difficulties were not with mathematics alone and suggests connections between attitudes toward and abilities in both mathematics and language. This paper will make these connections clear and will illustrate their ties to Lewis' effective mathematical references.

A Generic Framework For Arabic To English Machine Translation Of Simplex Sentences Using The Role And Reference Grammar Linguistic Model, Yasser Salem

Other Resources

No abstract provided.

Bootstrapping Events And Relations From Text, Ting Liu

Legacy Theses & Dissertations (2009 - 2024)

Information Extraction (IE) is a technique for automatically extracting structured data from text documents. One of the key analytical tasks is extraction of important and relevant information from textual sources. While information is plentiful and readily available, from the Internet, news services, media, etc., extracting the critical nuggets that matter to business or to national security is a cognitively demanding and time consuming task. Intelligence and business analysts spend many hours poring over endless streams of text documents pulling out reference to entities of interest (people, locations, organizations) as well as their relationships as reported in text. Such extracted "information …

Non-Programmers Identifying Functionality In Unfamiliar Code: Strategies And Barriers, Paul Gross, Caitlin Kelleher

All Computer Science and Engineering Research

Source code on the web is a widely available and potentially rich learning resource for non-programmers. However, unfamiliar code can be daunting to end-users without programming experience. This paper describes the results of an exploratory study in which we asked non-programmers to find and modify the code responsible for specific functionality within unfamiliar programs. We present two interacting models of how non-programmers approach this problem: the Task Process Model and the Landmark-Mapping model. Using these models, we describe code search strategies non-programmers employed and the difficulties they encountered. Finally, we propose guidelines for future programming environments that support non-programmers in …

Integration Of A Gis Learning System Into Civil Engineering Curricula: An Evaluation, Basanta Tandon

Masters Theses

"An evaluation of a web-based e-learning system to facilitate integration of Geographical Information Systems (GIS) into the Civil Engineering curriculum was conducted. The principal goals of the evaluation were to examine the effectiveness of the learning system and to develop a preliminary model to describe how students interact with the learning system. Quantitative and qualitative data were collected from 80 students who participated in a geotechnical engineering laboratory session, which covered soil borrow sites. Students rated the laboratory session as significantly more effective for learning, a nd more motivational than the class text. They also rated the lab significantly more …

An Automata Based Text Analysis System, Yue Lu

Master's Projects

This report describes and implements an automata based text analysis system. We have collected some of the writing samples. Each sample establishes a tree, and uses the ALERGIA algorithm to merge all compatible nodes in order to get a merged stochastic finite automaton. We store these automatons which demonstrate writing style of the sample texts in the hard drive. For a new testing piece, we can test if it has similar writing style compared to those sample texts.

An Adaptive Steganography Scheme For Voice Over Ip, Hui Tian, Ke Zhou, Hong Jiang, Yongfeng Huang, Jin Liu, Dan Feng

School of Computing: Conference and Workshop Papers

This paper presents an adaptive steganography scheme for Voice over IP (VoIP). Differing from existing steganography techniques for VoIP, this scheme enhances the embedding transparency by taking into account the similarity between Least Significant Bits (LSBs) and embedded messages. Moreover, we introduce the notion of Partial Similarity Value (PSV). By properly setting the threshold PSV, we can adaptively balance the embedding transparency and capacity. We evaluate the effectiveness of this scheme with G.729a as the codec of the cover speech in StegTalk, a covert communication system based on VoIP. The experimental results demonstrate that our technique provides better performance than …

An Adaptive Steganography Scheme For Voice Over Ip, Hui Tian, Ke Zhou, Hong Jiang, Yongfeng Huang, Jin Liu, Dan Feng

School of Computing: Conference and Workshop Papers

This paper presents an adaptive steganography scheme for Voice over IP (VoIP). Differing from existing steganography techniques for VoIP, this scheme enhances the embedding transparency by taking into account the similarity between Least Significant Bits (LSBs) and embedded messages. Moreover, we introduce the notion of Partial Similarity Value (PSV). By properly setting the threshold PSV, we can adaptively balance the embedding transparency and capacity. We evaluate the effectiveness of this scheme with G.729a as the codec of the cover speech in StegTalk, a covert communication system based on VoIP. The experimental results demonstrate that our technique provides better performance than …

Mrcraig: Mapreduce And Ensemble Classifiers For Parallelizing Data Classification Problems, Glenn Jahnke

Master's Projects

In this paper, a novel technique for parallelizing data-classification problems is applied to finding genes in sequences of DNA. The technique involves various ensem- ble classification methods such as Bagging and Select Best. It then distributes the classifier training and prediction using MapReduce. A novel sequence classification voting algorithm is evaluated in the Bagging method, as well as compared against the Select Best method.

A Semiotic Analysis Of Unified Modeling Language Graphical Notations, Keng Siau, Yuhong Tian

Research Collection School Of Computing and Information Systems

Unified modeling language (UML) is the standard modeling language for object-oriented system development. Despite its status as a standard, UML has a fuzzy formal specification and a weak theoretical foundation. Semiotics, the study of signs, provides a good theoretical foundation for UML research because graphical notations (or visual signs) of UML are subjected to the principles of signs. In our research, we use semiotics to study the effectiveness of graphical notations in UML. We hypothesized that the use of iconic signs as UML graphical notations leads to representation that is more accurately interpreted and that arouses fewer connotations than the …