Databases and Information Systems Commons^™

Two Formulas For Success In Social Media: Learning And Network Effects, Liangfei Qiu, Qian Tang, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

Recent years have witnessed an unprecedented explosion in information technology that enables dynamic diffusion of user-generated content in social networks. Online videos, in particular, have changed the landscape of marketing and entertainment, competing with premium content and spurring business innovations. In the present study, we examine how learning and network effects drive the diffusion of online videos. While learning happens through informational externalities, network effects are direct payoff externalities. Using a unique data set from YouTube, we empirically identify learning and network effects separately, and find that both mechanisms have statistically and economically significant effects on video views; furthermore, the …

Learning Relative Similarity From Data Streams: Active Online Learning Approaches, Shuji Hao, Peilin Zhao, Steven C. H. Hoi, Chunyan Miao

Research Collection School Of Computing and Information Systems

Relative similarity learning, as an important learning scheme for information retrieval, aims to learn a bi-linear similarity function from a collection of labeled instance-pairs, and the learned function would assign a high similarity value for a similar instance-pair and a low value for a dissimilar pair. Existing algorithms usually assume the labels of all the pairs in data streams are always made available for learning. However, this is not always realistic in practice since the number of possible pairs is quadratic to the number of instances in the database, and manually labeling the pairs could be very costly and time …

Social Tag Relevance Estimation Via Ranking-Oriented Neighbour Voting, Chaoran Cui, Jialie Shen, Jun Ma, Tao Lian

Research Collection School Of Computing and Information Systems

User-generated tags associated with social images are frequently imprecise and incomplete. Therefore, a fundamental challenge in tag-based applications is the problem of tag relevance estimation, which concerns how to interpret and quantify the relevance of a tag with respect to the contents of an image. In this paper, we address the key problem from a new perspective of learning to rank, and develop a novel approach to facilitate tag relevance estimation to directly optimize the ranking performance of tag-based image search. A supervision step is introduced into the neighbour voting scheme, in which tag relevance is estimated by accumulating votes …

Scheduled Approximation For Personalized Pagerank With Utility-Based Hub Selection, Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying

Research Collection School Of Computing and Information Systems

As Personalized PageRank has been widely leveraged for ranking on a graph, the efficient computation of Personalized PageRank Vector (PPV) becomes a prominent issue. In this paper, we propose FastPPV, an approximate PPV computation algorithm that is incremental and accuracy-aware. Our approach hinges on a novel paradigm of scheduled approximation: the computation is partitioned and scheduled for processing in an “organized” way, such that we can gradually improve our PPV estimation in an incremental manner and quantify the accuracy of our approximation at query time. Guided by this principle, we develop an efficient hub-based realization, where we adopt the metric …

Detect Rumors Using Time Series Of Social Context Information On Microblogging Websites, Jing Ma, Wei Gao, Zhongyu Wei, Yueming Lu, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Automatically identifying rumors from online social media especially microblogging websites is an important research issue. Most of existing work for rumor detection focuses on modeling features related to microblog contents, users and propagation patterns, but ignore the importance of the variation of these social context features during the message propagation over time. In this study, we propose a novel approach to capture the temporal characteristics of these features based on the time series of rumor's lifecycle, for which time series modeling technique is applied to incorporate various social context information. Our experiments using the events in two microblog datasets confirm …

On Robust Image Spam Filtering Via Comprehensive Visual Modeling, Jialie Shen, Deng, Robert H., Zhiyong Cheng, Liqiang Nie, Shuicheng Yan

Research Collection School Of Computing and Information Systems

The Internet has brought about fundamental changes in the way peoples generate and exchange media information. Over the last decade, unsolicited message images (image spams) have become one of the most serious problems for Internet service providers (ISPs), business firms and general end users. In this paper, we report a novel system called RoBoTs (Robust BoosTrap based spam detector) to support accurate and robust image spam filtering. The system is developed based on multiple visual properties extracted from different levels of granularity, aiming to capture more discriminative contents for effective spam image identification. In addition, a resampling based learning framework …

Choosing Your Weapons: On Sentiment Analysis Tools For Software Engineering Research, Robbert Jongeling, Subhajit Datta, Alexander Serebrenik

Research Collection School Of Computing and Information Systems

Recent years have seen an increasing attention to social aspects of software engineering, including studies of emotions and sentiments experienced and expressed by the software developers. Most of these studies reuse existing sentiment analysis tools such as SentiStrength and NLTK. However, these tools have been trained on product reviews and movie reviews and, therefore, their results might not be applicable in the software engineering domain. In this paper we study whether the sentiment analysis tools agree with the sentiment recognized by human evaluators (as reported in an earlier study) as well as with each other. Furthermore, we evaluate the impact …

The Importance Of Being Isolated: An Empirical Study On Chromium Reviews, Subhajit Datta, Devarshi Bhatt, Manish Jain, Proshanta Sarkar, Santonu Sarkar

Research Collection School Of Computing and Information Systems

As large scale software development has become more collaborative, and software teams more globally distributed, several studies have explored how developer interaction influences software development outcomes. The emphasis so far has been largely on outcomes like defect count, the time to close modification requests etc. In the paper, we examine data from the Chromium project to understand how different aspects of developer discussion relate to the closure time of reviews. On the basis of analyzing reviews discussed by 2000+ developers, our results indicate that quicker closure of reviews owned by a developer relates to higher reception of information and insights …

Structural Constraints For Multipartite Entity Resolution With Markov Logic Network, Tengyuan Ye, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Multipartite entity resolution seeks to match entity mentions across several collections. An entity mention is presumed unique within a collection, and thus could match at most one entity mention in each of the other collections. In addition to domain-specific features considered in entity resolution, there are a number of domain-invariant structural contraints that apply in this scenario, including one-to-one assignment as well as cross-collection transitivity. We propose a principled solution to the multipartite entity resolution problem, building on the foundation of Markov Logic Network (MLN) that combines probabilistic graphical model and first-order logic. We describe how the domain-invariant structural constraints …

Face Recognition On Large-Scale Video In The Wild With Hybrid Euclidean-And-Riemannian Metric Learning, Zhiwu Huang, R. Wang, S. Shan, X Chen

Research Collection School Of Computing and Information Systems

Face recognition on large-scale video in the wild is becoming increasingly important due to the ubiquity of video data captured by surveillance cameras, handheld devices, Internet uploads, and other sources. By treating each video as one image set, set-based methods recently have made great success in the field of video-based face recognition. In the wild world, videos often contain extremely complex data variations and thus pose a big challenge of set modeling for set-based methods. In this paper, we propose a novel Hybrid Euclidean-and-Riemannian Metric Learning (HERML) method to fuse multiple statistics of image set. Specifically, we represent each image …

Assessing Developer Contribution With Repository Mining-Based Metrics, Jalerson Lima, Christoph Treude, Fernando Figueira Filho, Uirá Kulesza

Research Collection School Of Computing and Information Systems

Productivity as a result of individual developers' contributions is an important aspect for software companies to maintain their competitiveness in the market. However, there is no consensus in the literature on how to measure productivity or developer contribution. While some repository mining-based metrics have been proposed, they lack validation in terms of their applicability and usefulness from the individuals who will use them to assess developer contribution: team and project leaders. In this paper, we propose the design of a suite of metrics for the assessment of developer contribution, based on empirical evidence obtained from project and team leaders. In …

Information Technology & Sustainability: An Empirical Study Of The Value Of The Building Automation System, Daphne Marie Simmonds

USF Tampa Graduate Theses and Dissertations

This study examines the environmental and economic effects of green information technology (IT). Green IT describes two sets of IT innovations: one set includes innovations that are implemented to reduce the environmental impact of IT services in organizations; and the other IT to reduce the environmental impact of other organizational processes. The two sets respond to the call for more environmentally friendly or “greener” organizational processes.

I developed and tested a preliminary model. The model applied the resource based view (RBV) of the firm (Wernerfelt 1984) the stakeholder theory (Freeman 1984) and included four constructs: (1) BAS implementation; environmental …

Spatiotemporal Sensing And Informatics For Complex Systems Monitoring, Fault Identification And Root Cause Diagnostics, Gang Liu

USF Tampa Graduate Theses and Dissertations

In order to cope with system complexity and dynamic environments, modern industries are investing in a variety of sensor networks and data acquisition systems to increase information visibility. Multi-sensor systems bring the proliferation of high-dimensional functional Big Data that capture rich information on the evolving dynamics of natural and engineered processes. With spatially and temporally dense data readily available, there is an urgent need to develop advanced methodologies and associated tools that will enable and assist (i) the handling of the big data communicated by the contemporary complex systems, (ii) the extraction and identification of pertinent knowledge about the environmental …

A Comparison Of A Multistate Inpatient Ehr Database To The Hcup Nationwide Inpatient Sample., Jonathan P Deshazo, Mark A Hoffman

Manuscripts, Articles, Book Chapters and Other Papers

BACKGROUND: The growing availability of electronic health records (EHRs) in the US could provide researchers with a more detailed and clinically relevant alternative to using claims-based data.

METHODS: In this study we compared a very large EHR database (Health Facts©) to a well-established population estimate (Nationwide Inpatient Sample). Weighted comparisons were made using t-value and relative difference over diagnoses and procedures for the year 2010.

RESULTS: The two databases have a similar distribution pattern across all data elements, with 24 of 50 data elements being statistically similar between the two data sources. In general, differences that were found are consistent …

Are We Making A Better World With Information And Communication Technology For Development (Ict4d) Research? Findings From The Field And Theory Building, Sajda Qureshi

Information Systems and Quantitative Analysis Faculty Publications

As Information and Communication Technologies (ICTs) continue to penetrate people’s lives the world over, there is a sense that understanding the role of ICTs in the context of development needs to be conceptualized theoretically while making empirical contributions that add to what we know (Avgerou, 2008; Davison, 2012; Sein and Harindranath, 2004; Sahay and Walsham, 1995). Other scholars have pointed to the importance of this research for the field of Information Systems (ISs) in offering broader contributions. Avgerou (2008) suggests that in the era of globalization such research offers contributions in ISs beyond “organizational organizational and national boundaries and support …

A Design For An Identity Resolution Service As An Extension Of The Entity Identity Information Management Model, Fumiko Kobayashi

Theses and Dissertations

This research describes the design of an identity resolution service (IRS), which provides extensions and enhancements to the current EIIM model. The IRS provides a set of application programming interfaces (API) which allow identity resolution (IR) to be performed interactively. Interactive IR is a logical extension to the existing EIIM model. It will separate the IR function from the EIIM batch update process. The new (IR) function: 1) Operates interactively 2) Has its own probabilistic matching rules defined separately from the identity rules used in the EIIM update process 3) Has the ability to return a confidence rating alongside a …

Using Content-Level Structures For Summarizing Microblog Repost Trees, Jing Li, Wei Gao, Zhongyu Wei, Baolin Peng, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

A microblog repost tree provides strong clues on how an event described therein develops. To help social media users capture the main clues of events on microblogging sites, we propose a novel repost tree summarization framework by effectively differentiating two kinds of messages on repost trees called leaders and followers, which are derived from contentlevel structure information, i.e., contents of messages and the reposting relations. To this end, Conditional Random Fields (CRF) model is used to detect leaders across repost tree paths. We then present a variant of random-walk-based summarization model to rank and select salient messages based on the …

Multi-Factor Duplicate Question Detection In Stack Overflow, Yun Zhang, David Lo, Xin Xia, Jian Ling Sun

Research Collection School Of Computing and Information Systems

Stack Overflow is a popular on-line question and answer site for software developers to share their experience and expertise. Among the numerous questions posted in Stack Overflow, two or more of them may express the same point and thus are duplicates of one another. Duplicate questions make Stack Overflow site maintenance harder, waste resources that could have been used to answer other questions, and cause developers to unnecessarily wait for answers that are already available. To reduce the problem of duplicate questions, Stack Overflow allows questions to be manually marked as duplicates of others. Since there are thousands of questions …

Mobisurround: An Auditory User Interface For Geo-Service Delivery, Keith Gardiner, Charlie Cullen, James Carswell

Conference papers

This paper describes original research carried out in the area of Location-Based Services (LBS) with an emphasis on Auditory User Interfaces (AUI) for content delivery. Previous work in this area has focused on accurately determining spatial interactions and informing the user mainly by means of the visual modality. mobiSurround is new research that builds upon these principles with a focus on multimodal content delivery and navigation and in particular the development of an AUI. This AUI enables the delivery of rich media content and natural directions using audio. This novel approach provides a hands free method for navigating a space …

Automatic Emotion Identification From Text, Wenbo Wang

Kno.e.sis Publications

Emotions are both prevalent in and essential to most aspects of our lives. They in- fluence our decision-making, affect our social relationships and shape our daily behavior. With the rapid growth of emotion-rich textual content, such as microblog posts, blog posts, and forum discussions, there is a growing need to develop algorithms and techniques for identifying people’s emotions expressed in text. It has valuable implications for the studies of suicide prevention, employee productivity, well-being of people, customer relationship management, etc. However, emotion identification is quite challenging partly due to the following reasons: i) It is a multi-class classification problem that …

Era Of Big Data: Danger Of Descrimination, Andra Gumbus, Frances Grodzinsky

WCBT Faculty Publications

We live in a world of data collection where organizations and marketers know our income, our credit rating and history, our love life, race, ethnicity, religion, interests, travel history and plans, hobbies, health concerns, spending habits and millions of other data points about our private lives. This data, mined for our behaviors, habits, likes and dislikes, is referred to as the “creep factor” of big data [1]. It is estimated that data generated worldwide will be 1.3 zettabytes (ZB) by 2016. The rise of computational power plus cheaper and faster devices to capture, collect, store and process data, translates into …

Real-Time Targeted Influence Maximization For Online Advertisements, Yuchen Li, Dongxiang Zhang, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

Advertising in social network has become a multi-billion dollar industry. A main challenge is to identify key influencers who can effectively contribute to the dissemination of information. Although the influence maximization problem, which finds a seed set of k most influential users based on certain propagation models, has been well studied, it is not target-aware and cannot be directly applied to online advertising. In this paper, we propose a new problem, named Keyword-Based Targeted Influence Maximization (KB-TIM), to find a seed set that maximizes the expected influence over users who are relevant to a given advertisement. To solve the problem, …

Developing Java Programs On Android Mobile Phones Using Speech Recognition, Santhrushna Gande

Electronic Theses, Projects, and Dissertations

Nowadays Android operating system based mobile phones and tablets are widely used and had millions of users around the world. The popularity of this operating system is due to its multi-tasking, ease of access and diverse device options. “Java Programming Speech Recognition Application” is an Android application used for handicapped individuals who are not able or have difficultation to type on a keyboard. This application allows the user to write a compute program (in Java Language) by dictating the words and without using a keyboard. The user needs to speak out the commands and symbols required for his/her program. The …

Bioinformatics Approaches To Single-Cell Analysis In Developmental Biology, Dicle Yalcin, Zeynep M. Hakguder, Hasan H. Otu

Department of Electrical and Computer Engineering: Faculty Publications

Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging …

Cobweb: A Robust Map Update System Using Gps Trajectories, Zhangqing Shan, Hao Wu, Weiwei Sun, Baihua Zheng

Research Collection School Of Computing and Information Systems

The accuracy and completeness of a digital map plays a critical role in determining the quality of most location-based services. Unfortunately, road networks change frequently. Consequently, we study the issue of automatic map update in this paper. We propose a system called COBWEB which takes all the unmatched trajectories as input and generates the missing road segments with both the geometry properties and topology features well preserved. We conduct a comprehensive experimental study via real trajectory data generated by roughly 15,000 taxis in Singapore within a 5-month period. Compared with existing work, COBWEB demonstrates a better and more stable performance …

Towards Opinion Summarization From Online Forums, Ding Ying, Jing Jiang

Research Collection School Of Computing and Information Systems

Summarizing opinions expressed in online forums can potentially benefit many people. However, special characteristics of this problem may require changes to standard text summarization techniques. In this work, we present our initial attempt at extractive summarization of opinionated online forum threads. Given the nature of user generated content in online discussion forums, we hypothesize that besides relevance, text quality and subjectivity also play important roles in deciding which sentences are good summary sentences. We therefore construct an annotated corpus to facilitate our study of extractive summarization of online discussion forums. We define a set of features to capture relevance, text …

A Survey On Artificial Intelligence-Based Modeling Techniques For High Speed Milling Processes, Amin Jahromi Torabi, Meng Joo Er, Xiang Li, Beng Siong Lim, Lianyin Zhai, Richard Jayadi Oentaryo, Gan Oon Peen, Jacek M. Zurada

Research Collection School Of Computing and Information Systems

The process of high speed milling is regarded as one of the most sophisticated and complicated manufacturing operations. In the past four decades, many investigations have been conducted on this process, aiming to better understand its nature and improve the surface quality of the products as well as extending tool life. To achieve these goals, it is necessary to form a general descriptive reference model of the milling process using experimental data, thermomechanical analysis, statistical or artificial intelligence (AI) models. Moreover, increasing demands for more efficient milling processes, qualified surface finishing, and modeling techniques have propelled the development of more …

Latent Factors Meet Homophily In Diffusion Modelling, Duc Minh Luu, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Diffusion is an important dynamics that helps spreading information within an online social network. While there are already numerous models for single item diffusion, few have studied diffusion of multiple items, especially when items can interact with one another due to their inter-similarity. Moreover, the well-known homophily effect is rarely considered explicitly in the existing diffusion models. This work therefore fills this gap by proposing a novel model called Topic level Interaction Homophily Aware Diffusion (TIHAD) to include both latent factor level interaction among items and homophily factor in diffusion. The model determines item interaction based on latent factors and …

Using Content-Level Structures For Summarizing Microblog Repost Trees, Jing Li, Wei Gao, Zhongyu Wei, Baolin Peng, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

A microblog repost tree provides strong clues on how an event described therein develops. To help social media users capture the main clues of events on microblogging sites, we propose a novel repost tree summarization framework by effectively differentiating two kinds of messages on repost trees called leaders and followers, which are derived from contentlevel structure information, i.e., contents of messages and the reposting relations. To this end, Conditional Random Fields (CRF) model is used to detect leaders across repost tree paths. We then present a variant of random-walk-based summarization model to rank and select salient messages based on the …

Candy Crushing Your Sleep, Kasthuri Jeyarajah, Meeralakshi Radhakrishnan, Steven C. H. Hoi, Archan Misra

Research Collection School Of Computing and Information Systems

Growing interest in quantified self has led to the popularity of lifelogging applications. In particular, health and wellness related applications have seen an upsurge with the advent of wearables such as the Fitbit. In this paper, we focus on the quality of sleep that directly impacts the overall wellness of individuals. In particular, in this work, we present a first of its kind study that (1) unobtrusively quantifies the quality of sleep and (2) seeks to identify attributing aspects of our daily lives such as an individual's usage of apps throughout the day and his/her physical environment that may affect …