Computer Sciences Commons^™

Deep Multimodal Learning For Affective Analysis And Retrieval, Lei Pang, Shiai Zhu, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Social media has been a convenient platform for voicing opinions through posting messages, ranging from tweeting a short text to uploading a media file, or any combination of messages. Understanding the perceived emotions inherently underlying these user-generated contents (UGC) could bring light to emerging applications such as advertising and media analytics. Existing research efforts on affective computation are mostly dedicated to single media, either text captions or visual content. Few attempts for combined analysis of multiple media are made, despite that emotion can be viewed as an expression of multimodal experience. In this paper, we explore the learning of highly …

Direct Or Indirect Match? Selecting Right Concepts For Zero-Example Case, Yi-Jie Lu, Maaike De Boer, Hao Zhang, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

No abstract provided.

Multimedia Event Detection: Strong By Integration, Hao Zhang, Maaike De Boer, Yi-Jie Lu, Klamer Schutte, Chong-Wah Ngo, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

No abstract provided.

Whom Should We Sense In 'Social Sensing' - Analyzing Which Users Work Best For Social Media Now-Casting, Jisun An, Ingmar Weber

Research Collection School Of Computing and Information Systems

Given the ever increasing amount of publicly available social media data, there is growing interest in using online data to study and quantify phenomena in the offline 'real' world. As social media data can be obtained in near real-time and at low cost, it is often used for 'now-casting' indices such as levels of flu activity or unemployment. The term 'social sensing' is often used in this context to describe the idea that users act as 'sensors', publicly reporting their health status or job losses. Sensor activity during a time period is then typically aggregated in a 'one tweet, one …

A Method And System For Sentiment Classification And Emotion Classification [Us Patent 20170308523a1], Zhaoxia Wang, Rick Siow Mong Goh, Yinping Yang

Research Collection School Of Computing and Information Systems

A system and a method for classifying text messages, such as social media messages into sentiment valence categories are provided. The system comprising a module for decomposing text messages, a module for cleaning text messages, a module for producing feature data of text messages, and a module for classifying text messages into sentiment valence categories. The module for decomposing text messages is configured to: receive a text message, parse the text message into separate portions in response to parsing criteria based on sentence delimiters, wherein the separate portions are sentences, phrases and words, and rejoin at least some of the …

Not All Trips Are Equal: Analyzing Foursquare Check-Ins Of Trips And City Visitors, Wen Haw Chong, Bingtian Dai, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Location-Based Social Networks (LBSN) such as Foursquare allow users to indicate venue visits via check-ins. This results in much fine grained context-rich data, useful for studying user mobility. In this work, we use check-ins to characterize trips and visitors to two cities, where visitors are defined as having their home cities elsewhere. First, we divide trips into two duration types: long and short. We then show that trip types differ in check-in distributions over venue categories, time slots, as well as check-in intensity. Based on the trip types, we then divide visitors into long-term and short-term visitors. We compare visitor …

Codehow: Effective Code Search Based On Api Understanding And Extended Boolean Model (E), Fei Lv, Jian-Guang Lou, Shaowei Wang, Dongmei Zhang, Jainjun Zhao

Research Collection School Of Computing and Information Systems

Over the years of software development, a vast amount of source code has been accumulated. Many code search tools were proposed to help programmers reuse previously-written code by performing free-text queries over a large-scale codebase. Our experience shows that the accuracy of these code search tools are often unsatisfactory. One major reason is that existing tools lack of query understanding ability. In this paper, we propose CodeHow, a code search technique that can recognize potential APIs a user query refers to. Having understood the potentially relevant APIs, CodeHow expands the query with the APIs and performs code retrieval by applying …

Real-Time Detection Of Seat Occupancy And Hogging, Huy Hoang Nguyen, Nakul Gulati, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

In this paper, we propose a cheap and effective solution to detect if specific seats at a shared public table are occupied -- either by humans or by objects (i.e., the seats are being "hogged"). The hogging of seats, in particular, is a big problem for our campus library and required a large amount of manpower to correct (to find and clear hogged seats). We propose using two different cheap sensors, a capacitance sensor and an infrared (IR) sensor, to solve this problem. In the rest of this paper, we show how using these sensors can accurately determine if a …

Powerforecaster: Predicting Smartphone Power Impact Of Continuous Sensing Applications At Pre-Installation Time, Chulhong Min, Youngki Lee, Chungkuk Yoo, Seungwoo Kang, Sangwon Choi, Pillsoon Park, Inseok Hwang, Younghyun Ju, Seungpyo Choi, Junehwa Song

Research Collection School Of Computing and Information Systems

Today's smartphone application (hereinafter 'app') markets miss a key piece of information, power consumption of apps. This causes a severe problem for continuous sensing apps as they consume significant power without users' awareness. Users have no choice but to repeatedly install one app after another and experience their power use. To break such an exhaustive cycle, we propose PowerForecaster, a system that provides users with power use of sensing apps at pre-installation time. Such advanced power estimation is extremely challenging since the power cost of a sensing app largely varies with users' physical activities and phone use patterns. We observe …

Security And Privacy Of Electronic Health Information Systems: Editorial, Elisa Bertino, Robert H. Deng, Xinyi Huang, Jianying Zhou

Research Collection School Of Computing and Information Systems

Digital technologies have dramatically transformed our daily lives by bringing countless conveniences and benefits. As an evolving concept, electronic health information has become the focus of attention in both academia and industry. By leveraging modern digital technologies like the internet and the cloud, electronic health information systems will be a key enabling technology in improving the quality and convenience of patient care, encouraging patient participation in their care, reducing medical errors, improving practice efficiencies, and saving time and cost. The complexity of electronic health information systems, however, raises several new security and privacy issues. It is thus critical to investigate …

Where Are The Passengers? A Grid-Based Gaussian Mixture Model For Taxi Bookings, Meng-Fen Chiang, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Taxi bookings are events where requests for taxis are made by passengers either over voice calls or mobile apps. As the demand for taxis changes with space and time, it is important to model both the space and temporal dimensions in dynamic booking data. Several applications can benefit from a good taxi booking model. These include the prediction of number of bookings at certain location and time of the day, and the detection of anomalous booking events. In this paper, we propose a Grid-based Gaussian Mixture Model (GGMM) with spatio-temporal dimensions that groups booking data into a number of spatio-temporal …

Intelligshop: Enabling Intelligent Shopping In Malls Through Location-Based Augmented Reality, Aditi Adhikari, Vincent W. Zheng, Hong Cao, Miao Lin, Yuan Fang, Kevin Chen-Chuan Chang

Research Collection School Of Computing and Information Systems

Shopping experience is important for both citizens and tourists. We present IntelligShop, a novel location-based augmented reality application that supports intelligent shopping experience in malls. As the key functionality, IntelligShop provides an augmented reality interface-people can simply use ubiquitous smartphones to face mall retailers, then IntelligShop will automatically recognize the retailers and fetch their online reviews from various sources (including blogs, forums and publicly accessible social media) to display on the phones. Technically, IntelligShop addresses two challenging data mining problems, including robust feature learning to support heterogeneous smartphones in localization and learning to query for automatically gathering the retailer content …

Modelling Cascades Over Time In Microblogs, Xie Wei, Feida Zhu, Siyuan Liu, Ke Wang

Research Collection School Of Computing and Information Systems

One of the most important features of microblogging services such as Twitter is how easy it is to re-share a piece of information across the network through various user connections, forming what we call a "cascade". Business applications such as viral marketing have driven a tremendous amount of research effort predicting whether a certain cascade will go viral. Yet the rarity of viral cascades in real data poses a challenge to all existing prediction methods. One solution is to simulate cascades that well fit the real viral ones, which requires our ability to tell how a certain cascade grows over …

Cost-Sensitive Online Classification With Adaptive Regularization And Its Applications, Peilin Zhao, Furen Zhuang, Min Wu, Xiao-Li Li, Hoi, Steven C. H.

Research Collection School Of Computing and Information Systems

Cost-Sensitive Online Classification is recently proposed to directly online optimize two well-known cost-sensitive measures: (i) maximization of weighted sum of sensitivity and specificity, and (ii) minimization of weighted misclassification cost. However, the previous existing learning algorithms only utilized the first order information of the data stream. This is insufficient, as recent studies have proved that incorporating second order information could yield significant improvements on the prediction model. Hence, we propose a novel cost-sensitive online classification algorithm with adaptive regularization. We theoretically analyzed the proposed algorithm and empirically validated its effectiveness with extensive experiments. We also demonstrate the application of the …

Cnl: Collective Network Linkage Across Heterogeneous Social Platforms, Ming Gao, Ee-Peng Lim, David Lo, Feida Zhu, Philips Kokoh Prasetyo, Aoying Zhou

Research Collection School Of Computing and Information Systems

The popularity of social media has led many users to create accounts with different online social networks. Identifying these multiple accounts belonging to same user is of critical importance to user profiling, community detection, user behavior understanding and product recommendation. Nevertheless, linking users across heterogeneous social networks is challenging due to large network sizes, heterogeneous user attributes and behaviors in different networks, and noises in user generated data. In this paper, we propose an unsupervised method, Collective Network Linkage (CNL), to link users across heterogeneous social networks. CNL incorporates heterogeneous attributes and social features unique to social network users, handles …

Experience Report: An Industrial Experience Report On Test Outsourcing Practices, Xin Xia, David Lo, Pavneet Singh Kochhar, Zhenchang Xing, Xinyu Wang, Shanping Li

Research Collection School Of Computing and Information Systems

Nowadays, many companies contract their testing functionalities out to third-party IT outsourcing companies. This process referred to as test outsourcing is common in the industry, yet it is rarely studied in the research community. In this paper, to bridge the gap, we performed an empirical study on test outsourcing with 10 interviewees and 140 survey respondents. We investigated various research questions such as the types, the process, and the challenges of test outsourcing, and the differences between test outsourcing and in-house testing. We found customer satisfaction, tight project schedule, and domain unfamiliarity are the top-3 challenges faced by the testers. …

Should Fixing These Failures Be Delegated To Automated Program Repair?, Le Dinh Xuan Bach, Le Bui Tien Duy, David Lo

Research Collection School Of Computing and Information Systems

Program repair constitutes one of the major components of software maintenance that usually incurs a significant cost in software production. Automated program repair is supposed to help in reducing the software maintenance cost by automatically fixing software defects. Despite the recent advances in automated software repair, it is still very costly to wait for repair tools to produce valid repairs of defects. This paper addresses the following question: "Will an automated program repair technique find a repair for a defect within a reasonable time?". To answer this question, we build an oracle that can predict whether fixing a failure should …

Building 3d-Printed Widgets To Incorporate Into Prototypes, David E. Brandt

Theses and Dissertations

Creating interactive prototypes can be a long and difficult process. It requires expertise in various fields. Prior work in developing interactive prototypes minimize time required to make a prototype, but generally sacrifice fidelity for fluidity. Advances in 3D printing create new opportunities to prototype with greater fidelity and fluidity. We investigate the use of several kinds of sensors, including IR photo interrupters, IR photo reflectors, push button switches, and potentiometers, to create interactive prototypes. We first design a library of 3D printable interaction components, buttons, sliders, and knobs using those sensors then we develop software to transform interaction events into …

Cvic: Cluster Validation Using Instance-Based Confidences, Dean M. Lebaron

Theses and Dissertations

As unlabeled data becomes increasingly available, the need for robust data mining techniques increases as well. Clustering is a common data mining tool which seeks to find related, independent patterns in data called clusters. The cluster validation problem addresses the question of how well a given clustering fits the data set. We present CVIC (cluster validation using instance-based confidences) which assigns confidence scores to each individual instance, as opposed to more traditional methods which focus on the clusters themselves. CVIC trains supervised learners to recreate the clustering, and instances are scored based on output from the learners which corresponds to …

Data Selection Using Topic Adaptation For Statistical Machine Translation, Hitokazu Matsushita

Theses and Dissertations

Statistical machine translation (SMT) requires large quantities of bitexts (i.e., bilingual parallel corpora) as training data to yield good quality translations. While obtaining a large amount of training data is critical, the similarity between training and test data also has a significant impact on SMT performance. Many SMT studies define data similarity in terms of domain-overlap, and domains are defined to be synonymous with data sources. Consequently, the SMT community has focused on domain adaptation techniques that augment small (in-domain) datasets with large datasets from other sources (hence, out-of-domain, per the definition). However, many training datasets consist of topically diverse …

Flexible Gating Of Contextual Influences In Natural Vision, Odelia Schwartz

Mathematics Colloquium Series

An appealing hypothesis suggests that neurons represent inputs in a coordinate system that is matched to the statistical structure of images in the natural environment. I discuss theoretical work on unsupervised learning of statistical regularities in natural images. In the model, Bayesian inference amounts to a generalized form of divisive normalization, a canonical computation that has been implicated in many neural areas. In our framework, divisive normalization is flexible: it is recruited only when the image is inferred to contain dependencies, and muted otherwise. I particularly focus on recent work in which we have applied this approach to understanding spatial …

Study Solar Activity In The Backside Of The Sun, Catherine A. Gibbs

Von Braun Symposium Student Posters

No abstract provided.

Embedded System Design Of A Real-Time Parking Guidance System, Omkar Dokur

USF Tampa Graduate Theses and Dissertations

The primary objective of this work is to design a parking guidance system to reliably detect entering/exiting vehicles to a parking garage in a cost-efficient manner. Existing solutions (inductive loops, RFID based systems, and video image processors) at shopping malls, universities, airports etc., are expensive due to high installation and maintenance costs. There is a need for a parking guidance system that is reliable, accurate, and cost-effective. The proposed parking guidance system is designed to optimize the use of parking spaces and to reduce wait times. Based on a literature review we identify that the ultrasonic sensor is suitable to …

Developing A Compiler For A Regular Expression Based Policy Specification Language, Cory Michael Juhlin

USF Tampa Graduate Theses and Dissertations

Security policy specification languages are a response to today's complex and vulnerable software climate. These languages allow an individual or organization to restrict and modify the behavior of third-party applications such that they adhere to the rules specified in the policy. As software grows in complexity, so do the security policies that govern them. Existing policy specification languages have not adapted to the growing complexity of the software they govern and as a result do not scale well, often resulting in code that is overly complex or unreadable. Writing small, isolated policies as separate modules and combining them is known …

The Digital Incunabula: Rock • Paper • Pixels, Patrick Aievoli

Zea E-Books Collection

“The Digital Incunabula is Patrick Aievoli’s personal sonnet through media, interaction and communication design. He carefully crafts each evolutionary step into ripples that are supported by his own storied professional and academic experiences. It’s full of facts, terms and historical information which makes it perfect for anyone looking to flat out learn!” ● James Pannafino, Professor, Millersville University & Interaction Design

“This is a serious work that will find a broad community of readers. The depth and breadth of Aievoli’s experience in the publication industry give his voice and ideas credibility in the extreme. This book will inspire deep reflection.” …

Information Security Newsletter

Offices & Divisions: Division of Information Technology Services (Archived)

No abstract provided.

Cloudy With A Chance Of Sunshine, Or The Future Of Magazine Publishing, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

EIC George K. Thiruvathukal describes how the cloud can revolutionize printing and how the publishing world in particular can benefit.

Blindcanseeql: Improved Blind Sql Injection For Db Schema Discovery Using A Predictive Dictionary From Web Scraped Word Based Lists, Ryan Wheeler

USF Tampa Graduate Theses and Dissertations

SQL Injections are still a prominent threat on the web. Using a custom built tool, BlindCanSeeQL (BCSQL), we will explore how to automate Blind SQL attacks to discover database schema using fewer requests than the standard methods, thus helping avoid detection from overloading a server with hits. This tool uses a web crawler to discover keywords that assist with autocompleting schema object names, along with improvements in ASCII bisection to lower the number of requests sent to the server. Along with this tool, we will discuss ways to prevent and protect against such attacks.

Visualizing Fantasy Fiction: Design Of A Class In Digital Scholarship And Visualization, Including Research, Organization And Digital Visualization, That Does Not Require Programming Or It Support, Charles W. Kann

Computer Science Faculty Publications

This paper outlines a course to integrate digital visualizations into undergraduate research. These visualizations will include mapping and timelines of events, and the ability to hyperlink the events, characters, and story lines in a fantasy fiction story such as Lord of the Rings or A Game of Thrones. The digital scholarship will involve the methodology for collecting, organizing, and representing the data for the visualizations.

The topic for the visualizations in this paper is fantasy fiction; however the methods to develop these visualizations will be applicable to many academic disciplines, including the humanities and social sciences.

The paper outlines …

Information Security Newsletter

Offices & Divisions: Division of Information Technology Services (Archived)

No abstract provided.