Computer Sciences Commons^™

A Feasibility Study Of Crowdsourcing And Google Street View To Determine Sidewalk Accessibility, Kotaro Hara, Victoria Le, Jon Froehlich

Research Collection School Of Computing and Information Systems

We explore the feasibility of using crowd workers from Amazon Mechanical Turk to identify and rank sidewalk accessibility issues from a manually curated database of 100 Google Street View images. We examine the effect of three different interactive labeling interfaces (Point, Rectangle, and Outline) on task accuracy and duration. We close the paper by discussing limitations and opportunities for future work.

Wikis: The Perfect Platform For Library Policies And Procedures, Melanie J. Dunn

The Southeastern Librarian

The term wiki, derived from the Hawaiian adjective “wiki wiki” meaning quick or fast, was coined by Ward Cunningham who created the original WikiWikiWeb for the Portland Pattern Repository (Leuf, 2001, 15). Touted by Cunningham as “the simplest online database that could possibly work” (Cunningham, 2002, June 27) “ wiki” is alternately used to refer to both a wiki website and the software used to create and maintain it and was designed to allow multiple users to collaborate in its development (Klobas 2006, 3). Wikipedia is perhaps one of the best examples, as well as the most recognized, of wikis. …

A Probabilistic Graphical Model For Topic And Preference Discovery On Social Media, Lu Liu, Feida Zhu, Lei Zhang, Shiqiang Yang

Research Collection School Of Computing and Information Systems

Many web applications today thrive on offering services for large-scale multimedia data, e.g., Flickr for photos and YouTube for videos. However, these data, while rich in content, are usually sparse in textual descriptive information. For example, a video clip is often associated with only a few tags. Moreover, the textual descriptions are often overly specific to the video content. Such characteristics make it very challenging to discover topics at a satisfactory granularity on this kind of data. In this paper, we propose a generative probabilistic model named Preference-Topic Model (PTM) to introduce the dimension of user preferences to enhance the …

Influentials, Novelty, And Social Contagion: The Viral Power Of Average Friends, Close Communities, And Old News, Nicholas Harrigan, Palakorn Achananuparp, Ee Peng Lim

Research Collection School Of Computing and Information Systems

What is the effect of (1) popular individuals, and (2) community structures on the retransmission of socially contagious behavior? We examine a community of Twitter users over a five month period, operationalizing social contagion as ‘retweeting’, and social structure as the count of subgraphs (small patterns of ties and nodes) between users in the follower/following network. We find that popular individuals act as ‘inefficient hubs’ for social contagion: they have limited attention, are overloaded with inputs, and therefore display limited responsiveness to viral messages. We argue this contradicts the ‘law of the few’ and ‘influentials hypothesis’. We find that community …

Content Contribution For Revenue Sharing And Reputation: A Dynamic Structural Model, Qian Tang, Bin Gu, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

This study examines the incentives for content contribution in social media. We propose that exposure and reputation are the major incentives for contributors. Besides, as more and more social media Web sites offer advertising-revenue sharing with some of their contributors, shared revenue provides an extra incentive for contributors who have joined revenue-sharing programs. We develop a dynamic structural model to identify a contributor's underlying utility function from observed contribution behavior. We recognize the dynamic nature of the content-contribution decision-that contributors are forward-looking, anticipating how their decisions affect future rewards. Using data collected from YouTube, we show that content contribution is …

Talk Versus Work: Characteristics Of Developer Collaboration On The Jazz Platform, Subhajit Datta, Renuka Sindhgatta, Bikram Sengupta

Research Collection School Of Computing and Information Systems

IBM's Jazz initiative offers a state-of-the-art collaborative development environment (CDE) facilitating developer interactions around interdependent units of work. In this paper, we analyze development data across two versions of a major IBM product developed on the Jazz platform, covering in total 19 months of development activity, including 17,000+ work items and 61,000+ comments made by more than 190 developers in 35 locations. By examining the relation between developer talk and work, we find evidence that developers maintain a reasonably high level of connectivity with peer developers with whom they share work dependencies, but the span of a developer's communication goes …

Recent Advances In Integrating Owl And Rules, Matthias Knorr, David Carral Martinez, Pascal Hitzler, Adila A. Krisnadhi, Frederick Maier, Cong Wang

Computer Science and Engineering Faculty Publications

As part of the quest for a unifying logic for the Semantic Web Technology Stack, a central issue is finding suitable ways of integrating description logics based on the Web Ontology Language (OWL) with rule-based approaches based on logic programming. Such integration is difficult since naive approaches typically result in the violation of one or more desirable design principles. For example, while both OWL 2 DL and RIF Core (a dialect of the Rule Interchange Format RIF) are decidable, their naive union is not, unless carefully chosen syntactic restrictions are applied.

We report on recent advances and ongoing work by …

A Tableau Algorithm For Description Logics With Nominal Schema, Adila Krisnadhi, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We present a tableau algorithm for the description logic ALCOV. This description logic is obtained by extending the description logic ALCO with the expressive nominal schema construct that enables DL-safe datalog with predicates of arbitrary arity to be covered within the description logic framework. The tableau algorithm provides a basis to implement a delayed grounding strategy which was not facilitated by earlier versions of decision procedures for satisfiability in expressive description logics with nominal schemas.

Observatory Of Trends In Software Related Microblogs, Achananuparp Palakorn, Nelman Lubis Ibrahim, Yuan Tian, David Lo, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Microblogging has recently become a popular means to disseminate information among millions of people. Interestingly, software developers also use microblog to communicate with one another. Different from traditional media, microblog users tend to focus on recency and informality of content. Many tweet contents are relatively more personal and Opinionated, compared to that of traditional news report. Thus, by analyzing microblogs, one could get the up-to-date information about what people are interested in or feel toward a particular topic. In this paper, we describe our microblog observatory that aggregates more than 70,000 Twitter feeds, captures software-related tweets, and computes trends from …

Automatic Classification Of Software Related Microblogs, Philips Kokoh Prasetyo, David Lo, Achananuparp Palakorn, Yuan Tian, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Millions of people, including those in the software engineering communities have turned to microblogging services, such as Twitter, as a means to quickly disseminate information. A number of past studies by Treude et al., Storey, and Yuan et al. have shown that a wealth of interesting information is stored in these microblogs. However, microblogs also contain a large amount of noisy content that are less relevant to software developers in engineering software systems. In this work, we perform a preliminary study to investigate the feasibility of automatic classification of microblogs into two categories: relevant and irrelevant to engineering software systems. …

Reconciling Owl And Non-Monotonic Rules For The Semantic Web, Matthias Knorr, Pascal Hitzler, Frederick Maier

Computer Science and Engineering Faculty Publications

We propose a description logic extending SROIQ (the description logic underlying OWL 2 DL) and at the same time encompassing some of the most prominent monotonic and nonmonotonic rule languages, in particular Datalog extended with the answer set semantics. Our proposal could be considered a substantial contribution towards fulfilling the quest for a unifying logic for the Semantic Web. As a case in point, two non-monotonic extensions of description logics considered to be of distinct expressiveness until now are covered in our proposal. In contrast to earlier such proposals, our language has the 'look and feel' of a description logic …

Analysis Of Median Household Income Differences Between Election Day-Vbm And Eip Voters, Mark Salling, Norman Robbins

All Maxine Goodman Levin School of Urban Affairs Publications

Analysis of early in-person (EIP) voting in 2008 in Cuyahoga County shows that African-American, white, and Hispanic voters who used EIP voting had significantly lower incomes than members of those same groups who voted on election day or by mail. This result applies to those voting EIP on weekdays, extended weekday hours, weekends, and the three days before election day.

Using Attribute Behavior Diversity To Build Accurate Decision Tree Committees For Microarray Data, Qian Han, Guozhu Dong

Kno.e.sis Publications

DNA microarrays (gene chips), frequently used in biological and medical studies, measure the expressions of thousands of genes per sample. Using microarray data to build accurate classifiers for diseases is an important task. This paper introduces an algorithm, called Committee of Decision Trees by Attribute Behavior Diversity (CABD), to build highly accurate ensembles of decision trees for such data. Since a committee's accuracy is greatly influenced by the diversity among its member classifiers, CABD uses two new ideas to "optimize" that diversity, namely (1) the concept of attribute behavior–based similarity between attributes, and (2) …

The Patrol Scheduling Problem, Hoong Chuin Lau, Aldy Gunawan

Research Collection School Of Computing and Information Systems

This paper presents the problem of scheduling security teams to patrol a mass rapid transit rail network of a large urban city. The main objective of patrol scheduling is to deploy security teams to stations at varying time periods of the network subject to rostering as well as security-related constraints. We present a mathematical programming model for this problem. We then discuss the aspect of injecting randomness by varying the start times, the break times for each team as well as the number of visits required for each station according to their reported vulnerability. Finally, we present results for the …

(Hidden) Social Influences In Switching Mobile Service Platforms, Virpi K. Tuunainen, Tuure Tuunanen, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

During the past few years, the mobile industry has gone through a radical change from business focusing on excellence in device manufacturing and supply chain management to ecosystems around successful focal players, such as Apple and Google, controlling these service platforms. In order to compete in this environment, these firms need to understand what makes a consumer switch between these mobile service platforms. To that end, we conducted an inductive qualitative study with university students from Finland and USA as subjects (142 altogether), delving into how and why consumers switch mobile phones, and what are the factors affecting their decisions. …

Toward Large-Scale Agent Guidance In An Urban Taxi Service, Agussurja Lucas, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Empty taxi cruising represents a wastage of resources in the context of urban taxi services. In this work, we seek to minimize such wastage. An analysis of a large trace of taxi operations reveals that the services’ inefficiency is caused by drivers’ greedy cruising behavior. We model the existing system as a continuous time Markov chain. To address the problem, we propose that each taxi be equipped with an intelligent agent that will guide the driver when cruising for passengers. Then, drawing from AI literature on multiagent planning, we explore two possible ways to compute such guidance. The first formulation …

Twitris+: Social Media Analytics Platform For Effective Coordination, Gary Alan Smith, Amit P. Sheth, Ashutosh Sopan Jadhav, Hemant Purohit, Lu Chen, Michael Cooney, Pavan Kapanipathi, Pramod Anantharam, Pramod Koneru, Wenbo Wang

Kno.e.sis Publications

Twitris+ is a Semantic Social Media analytics platform to provide technologies for analyzing large-scale social media streams across Spatio-Temporal-Thematic (STT) and People-Content-Network (PCN) dimensions. It provides holistic situational awareness from one interface and enables organizational actors to engage in well-coordinated ways for desired tasks during emergency response.

“Advancing With The Times: Industrial Design Protection In The Era Of Virtual Migration”, Horacio E. Gutiérrez

IP Theory

No abstract provided.

Prosody-Based Query-By-Example Spoken Utterance Retrieval, Steven D. Werner, Nigel G. Ward

COURI Symposium Abstracts, Summer 2012

Current spoken dialogue retrieval systems are almost entirely lexically based, using automatic transcription by imperfect speech recognition technology. Once audio is reduced to text, little more than existing text search methods are used to retrieve results. However, spoken dialogue contains rich latent prosodic information about dialogue activities - such as agreeing, arguing, deciding, planning, storytelling, showing surprise - and this extra information can often be relevant to the searchers aims. Searching for similar speech acts rather then similar words enables similar contextual results, returning points where the speaker had the same sentiment during a topic. Previous research yielded 76 dimensions …

The Latent Maximum Entropy Principle, Shaojun Wang, Dale Schuurmans, Yunxin Zhao

Kno.e.sis Publications

We present an extension to Jaynes’ maximum entropy principle that incorporates latent variables. The principle of latent maximum entropy we propose is different from both Jaynes’ maximum entropy principle and maximum likelihood estimation, but can yield better estimates in the presence of hidden variables and limited training data. We first show that solving for a latent maximum entropy model poses a hard nonlinear constrained optimization problem in general. However, we then show that feasible solutions to this problem can be obtained efficiently for the special case of log-linear models---which forms the basis for an efficient approximation to the latent maximum …

What Kind Of #Communication Is Twitter? A Psycholinguistic Perspective On Communication In Twitter For The Purpose Of Emergency Coordination, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John Flach

Kno.e.sis Publications

The present research aims to detect coordinated citizen response within social media traffic to assist emergency response. We use domain-independent linguistic properties as the first step in narrowing the candidate set of messages for domain-dependent and computationally intensive analysis.

Exploring The Impact Of Knowledge And Social Environment On Influenza Prevention And Transmission In Midwestern United States High School Students, William L. Romine, Tanvi Banerjee, William S. Barrow, William R. Folk

Kno.e.sis Publications

We used data from a convenience sample of 410 Midwestern United States students from six secondary schools to develop parsimonious models for explaining and predicting precautions and illness related to influenza. Scores for knowledge and perceptions were obtained using two-parameter Item Response Theory (IRT) models. Relationships between outcome variables and predictors were verified using Pearson and Spearman correlations, and nested [student within school] fixed effects multinomial logistic regression models were specified from these using Akaike’s Information Criterion (AIC). Neural network models were then formulated as classifiers using 10-fold cross validation to predict precautions and illness. Perceived barriers against taking precautions …

Detecting Anomalous Twitter Users By Extreme Group Behaviors, Hanbo Dai, Ee-Peng Lim, Feida Zhu, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Twitter has enjoyed tremendous popularity in the recent years. To help categorizing and search tweets, Twitter users assign hashtags to their tweets. Given that hashtag assignment is the primary way to semantically categorizing and search tweets, it is highly susceptible to abuse by spammers and other anomalous users [1]. Popular hashtags such as #Obama and #ladygaga could be hijacked by having them added to unrelated tweets with the intent of misleading many other users or promoting specific agenda to the users. The users performing this act are known as the hashtag hijackers. As the hijackers usually abuse common sets of …

Topic Discovery From Tweet Replies, Bingtian Dai, Ee Peng Lim, Philips Kokoh Prasetyo

Research Collection School Of Computing and Information Systems

Twitter is a popular online social information network service which allows people to read and post messages up to 140 characters, known as “tweets”. In this paper, we focus on the tweets between pairs of individuals, i.e., the tweet replies, and propose a generative model to discover topics among groups of twitter users. Our model has then been evaluated with a tweet dataset to show its effectiveness.

Finding Bursty Topics From Microblogs, Qiming Diao, Jing Jiang, Feida Zhu, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Microblogs such as Twitter reflect the general public’s reactions to major events. Bursty topics from microblogs reveal what events have attracted the most online attention. Although bursty event detection from text streams has been studied before, previous work may not be suitable for microblogs because compared with other text streams such as news articles and scientific publications, microblog posts are particularly diverse and noisy. To find topics that have bursty patterns on microblogs, we propose a topic model that simultaneousy captures two observations: (1) posts published around the same time are more likely to have the same topic, and (2) …

Identifying And Attributing Similar Traces With Greatest Common Factor Analysis, Fred Cohen

Journal of Digital Forensics, Security and Law

This paper presents an algorithm for comparing large numbers of traces to each other and identifying and presenting groups of traces with similar features. It is applied to forensic analysis in which groups of similar traces are automatically identified and presented so that attribution and other related claims may be asserted, and independently confirmed or refuted. The approach of this paper is to identify an approximate algorithm that will find a large subset of greatest common factor similar groups of arbitrary factors in far less time and space than an exact algorithm using examiner-provided selection criteria for factor definition.

Iexplore: A Provenance-Based Application For Exploring Biomedical Knowledge, Vinh Nguyen, Olivier Bodenreider, Thomas Rindflesch, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

W3c Semantic Sensor Networks: Ontologies, Applications, And Future Directions, Cory Andrew Henson

Kno.e.sis Publications

Plenary Talk discussing the W3C Semantic Sensor Network, including the ontology, applications, and future directions.

The Effects Of Diagrams And Relational Complexity On User Performance In Conditional Probability Problems In A Non-Learning Context, Vincent J. Kellen

College of Computing and Digital Media Dissertations

Many disciplines in everyday life depend on improved performance in conditional probability problems. Most adults struggle with conditional probability problems and several prior studies have shown participant accuracy is less than 50%. This study examined user performance when aided with computer-generated Venn and Euler type diagrams in a non-learning context. Despite the prevalence of research into diagrams and extensive research into conditional probability problem solving, this study is one of the only studies to apply theories of working memory to predict user performance in conditional probability problems with diagrams. Following relational complexity theory, this study manipulated problem complexity in computer …

Topical Anomaly Detection From Twitter Streams, Pramod Anantharam, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.