Physical Sciences and Mathematics Commons^™

Concept Based Search Engine: Concept Creation, Aishwarya Rastogi

Master's Projects

Data on the internet is increasing exponentially every single second. There are billions and billions of documents on the World Wide Web (The Internet). Each document on the internet contains multiple concepts (an abstract or general idea inferred from specific instances).

In this paper, we show how we created and implemented an algorithm for extracting concepts from a set of documents. These concepts can be used by a search engine for generating search results to cater the needs of the user. The search result will then be more targeted than the usual keyword search.

The main problem was to extract …

A Personalized People Recommender System Using Global Search Approach, Chun-Hua Tsai, Peter Brusilovsky

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

The goal of people recommender system is to generate meaningful social suggestion to users. The abundant data are the key factor in fulfilling a recommendation task, but the cost of user data in a real-world system is high. In this paper, we propose a novel approach that integrates a global search result with a personalized people recommendation system. Our approach utilizes the user identity as a query keyword and processes the search results through five different customized parsers. This approach solves the cold-start issue in recommendation systems and leverages the crossdomain information in order to provide a better recommendation result. …

Semantic, Cognitive, And Perceptual Computing: Paradigms That Shape Human Experience, Amit P. Sheth, Pramod Anantharam, Cory Henson

Kno.e.sis Publications

Unlike machine-centric computing, in which efficient data processing takes precedence over contextual tailoring, human-centric computation provides a personalized data interpretation that most users find highly relevant to their needs. The authors show how semantic, cognitive, and perceptual computing paradigms work together to produce actionable information.

Man Vs. Machine: Investigating The Effects Of Adversarial System Use On End-User Behavior In Automated Deception Detection Interviews, Jeffrey Gainer Proudfoot, Randall Boyle, Ryan M. Schuetzler

Information Systems and Quantitative Analysis Faculty Publications

Deception is an inevitable component of human interaction. Researchers and practitioners are developing information systems to aid in the detection of deceptive communication. Information systems are typically adopted by end users to aid in completing a goal or objective (e.g., increasing the efficiency of a business process). However, end-user interactions with deception detection systems (adversarial systems) are unique because the goals of the system and the user are orthogonal. Prior work investigating systems-based deception detection has focused on the identification of reliable deception indicators. This research extends extant work by looking at how users of deception detection systems alter their …

Mobilaudio – A Multimodal Content Delivery Platform For Geo-Services, James Carswell, Keith Gardiner, Charlie Cullen

Articles

Delivering high-quality context-relevant information in a timely manner is a priority for location-based services (LBS) where applications require an immediate response based on spatial interaction. Previous work in this area typically focused on ever more accurately determining this interaction and informing the user in the customary graphical way using the visual modality. This paper describes the research area of multimodal LBS and focuses on audio as the key delivery mechanism. This new research extends familiar graphical information delivery by introducing a geoservices platform for delivering multimodal content and navigation services. It incorporates a novel auditory user interface (AUI) that enables …

Interactive Teachable Cognitive Agents: Smart Building Blocks For Multiagent Systems, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Developing a complex intelligent system by abstracting their behaviors, functionalities, and reasoning mechanisms can be tedious and time consuming. In this paper, we present a framework for developing an application or software system based on smart autonomous components that collaborate with the developer or user to realize the entire system. Inspired by teachable approaches and programming-by-demonstration methods in robotics and end-user development, we treat intelligent agents as teachable components that make up the system to be built. Each agent serves different functionalities and may have prebuilt operations to accomplish its own design objectives. However, each agent may also be equipped …

Scrum-X: An Interactive And Experiential Learning Platform For Teaching Scrum, Wee Leong Lee

Research Collection School Of Computing and Information Systems

Motivating and engaging thecurrent generation of technology-savvy students and improving the quality oflearning is becoming more challenging with traditional instructional methods.Educational games and simulations are gaining more ground, both in formal andinformal learning environments. With experiential learning, learners canenhance their management skills and ability to make decisions by analyzingdifferent scenarios and paths that the project could have taken if specificdecisions were made during the project. This paper presents Scrum-X, acomputer-based simulation game to teach Scrum, an agile project managementmethodology, to graduates and professionals with IT background. In the game,players plan, execute and manage a software development project using Scrummethodology. Players …

Image Use In Social Network Communication: A Case Study Of Tweets On The Boston Marathon Bombing, Jungwon Yoon, Eunkyung Chung

School of Information Systems and Management Faculty Publications

Introduction. This study aimed to understand how images are used in communication practices in the Twitter environment. Method. 1,428 Boston marathon bombing related Twitter messages with embedded images were collected, and content analysis was conducted. Analysis. Characteristics of image use were examined and were analysed by type of Twitter messages. Results. People used diverse types of images in Twitter messages including: direct photos, captured images, computer graphics, and maps. Depending on the content of Twitter messages, uses of images were categorised into four types: 1) to illustrate news, information, and anecdotes, 2) to disseminate visual information that cannot be provided …

Semantic Memory Modeling And Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

Semantic memory plays a critical role in reasoning and decision making. It enables an agent to abstract useful knowledge learned from its past experience. Based on an extension of fusion adaptive resonance theory network, this paper presents a novel self-organizing memory model to represent and learn various types of semantic knowledge in a unified manner. The proposed model, called fusion adaptive resonance theory for multimemory learning, incorporates a set of neural processes, through which it may transfer knowledge and cooperate with other long-term memory systems, including episodic memory and procedural memory. Specifically, we present a generic learning process, under which …

Learning To Find Topic Experts In Twitter Via Different Relations, Wei Wei, Gao Cong, Chunyan Miao, Feida Zhu, Guohui Li

Research Collection School Of Computing and Information Systems

Expert finding has become a hot topic along with the flourishing of social networks, such as micro-blogging services like Twitter. Finding experts in Twitter is an important problem because tweets from experts are valuable sources that carry rich information (e.g., trends) in various domains. However, previous methods cannot be directly applied to Twitter expert finding problem. Recently, several attempts use the relations among users and Twitter Lists for expert finding. Nevertheless, these approaches only partially utilize such relations. To this end, we develop a probabilistic method to jointly exploit three types of relations (i.e., follower relation, user-list relation and list-list …

Campus-Scale Mobile Crowd-Tasking: Deployment And Behavioral Insights, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Nikita Jaiman, Randy Tandriansiyah, Cen Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta

Research Collection School Of Computing and Information Systems

Mobile crowd-tasking markets are growing at an unprecedented rate with increasing number of smartphone users. Such platforms differ from their online counterparts in that they demand physical mobility and can benefit from smartphone processors and sensors for verification purposes. Despite the importance of such mobile crowd-tasking markets, little is known about the labor supply dynamics and mobility patterns of the users. In this paper we design, develop and experiment with a realwporld mobile crowd-tasking platform, called TA$Ker. Our contributions are two-fold: (a) We develop TA$Ker, a system that allows us to empirically study the worker responses to push vs. pull …

A Business Zone Recommender System Based On Facebook And Urban Planning Data, Jovian Lin, Richard Jayadi Oentaryo, Ee Peng Lim, Casey Vu, Adrian Wei Liang Vu, Philips Kokoh And Prasetyo

Research Collection School Of Computing and Information Systems

We present ZoneRec—a zone recommendation system for physical businesses in an urban city,which uses both public business data from Facebook and urban planning data. The systemconsists of machine learning algorithms that take in a business’ metadata and outputs a list ofrecommended zones to establish the business in. We evaluate our system using data of foodbusinesses in Singapore and assess the contribution of different feature groups to therecommendation quality.

Multiagent-Based Route Guidance For Increasing The Chance Of Arrival On Time, Zhiguang Cao, Hongliang Guo, Jie Zhang, Ulrich Fastenrath

Research Collection School Of Computing and Information Systems

Transportation and mobility are central to sustainable urban development, where multiagent-based route guidance is widely applied. Traditional multiagent-based route guidance always seeks LET (least expected travel time) paths. However, drivers usually have specific expectations, i.e., tight or loose deadlines, which may not be all met by LET paths. We thus adopt and extend the probability tail model that aims to maximize the probability of reaching destinations before deadlines. Specifically, we propose a decentralized multiagent approach, where infrastructure agents locally collect intentions of concerned vehicle agents and formulate route guidance as a route assignment problem, to guarantee their arrival on time. …

Online Cross-Modal Hashing For Web Image Retrieval, Liang Xie, Jialie Shen, Lei Zhu

Research Collection School Of Computing and Information Systems

Cross-modal hashing (CMH) is an efficient technique for the fast retrieval of web image data, and it has gained a lot of attentions recently. However, traditional CMH methods usually apply batch learning for generating hash functions and codes. They are inefficient for the retrieval of web images which usually have streaming fashion. Online learning can be exploited for CMH. But existing online hashing methods still cannot solve two essential problems: Efficient updating of hash codes and analysis of cross-modal correlation. In this paper, we propose Online Cross-modal Hashing (OCMH) which can effectively address the above two problems by learning the …

Online Multi-Modal Distance Metric Learning With Application To Image Retrieval, Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Chunyan Miao, Zhi-Yong Liu

Research Collection School Of Computing and Information Systems

Distance metric learning (DML) is an important technique to improve similarity search in content-based image retrieval. Despite being studied extensively, most existing DML approaches typically adopt a single-modal learning framework that learns the distance metric on either a single feature type or a combined feature space where multiple types of features are simply concatenated. Such single-modal DML methods suffer from some critical limitations: (i) some type of features may significantly dominate the others in the DML task due to diverse feature representations; and (ii) learning a distance metric on the combined high-dimensional feature space can be extremely time-consuming using the …

Exploring Heterogeneous Features For Query-Focused Summarization Of Categorized Community Answers, Wei Wei, Zhaoyan Ming, Liqiang Nie, Guohui Li, Jianjun Li, Feida Zhu, Tianfeng Shang, Changyin Luo

Research Collection School Of Computing and Information Systems

Community-based question answering (cQA) is a popular type of online knowledge-sharing web service where users ask questions and obtain answers contributed by others. To enhance knowledge sharing, cQA also provides users with a retrieval function to access the historical question-answer pairs (QAs). However, it is still ineffective in that the retrieval result is typically a ranking list of potentially relevant QAs, rather than a succinct and informative answer. To alleviate the problem, this paper proposes a three-level scheme, which aims to generate a query-focused summary-style answer in terms of two factors, i.e., novelty and redundancy. Specifically, we first retrieve a …

Efficient Collective Spatial Keyword Query Processing On Road Networks, Yunjun Gao, Jingwen Zhao, Baihua Zheng, Gang Chen

Research Collection School Of Computing and Information Systems

The collective spatial keyword query (CSKQ), an important variant of spatial keyword queries, aims to find a set of the objects that collectively cover users' queried keywords, and those objects are close to the query location and have small inter-object distances. Existing works only focus on the CSKQ problem in the Euclidean space, although we observe that, in many real-life applications, the closeness of two spatial objects is measured by their road network distance. Thus, existing methods cannot solve the problem of network-based CSKQ efficiently. In this paper, we study the problem of collective spatial keyword query processing on road …

Online Advertising, Retail Platform Openness, And Long Tail Sellers, Jianqing Chen, Zhiling Guo

Research Collection School Of Computing and Information Systems

No abstract provided.

Negative Factor: Improving Regular-Expression Matching In Strings, Xiaochun Yang, Tao Qiu, Bin Wang, Baihua Zheng, Yaoshu Wang, Chen Li

Research Collection School Of Computing and Information Systems

The problem of finding matches of a regular expression (RE) on a string exists in many applications such as text editing, biosequence search, and shell commands. Existing techniques first identify candidates using substrings in the RE, then verify each of them using an automaton. These techniques become inefficient when there are many candidate occurrences that need to be verified. In this paper we propose a novel technique that prunes false negatives by utilizing negative factors, which are substrings that cannot appear in an answer. A main advantage of the technique is that it can be integrated with many existing algorithms …

Copyright Law And The Supply Of Creative Work: Evidence From The Movies, Ivan Paak Liang Png, Qiu-Hong Wang

Research Collection School Of Computing and Information Systems

There is almost no empirical evidence on the extent to whichcopyright law works in the sense of increasing the production of creative work.Here, we study the impact of two major changes in copyright law – the extensionof copyright term and the European Rental Directive – on the production ofmovies. In a panel of 23 OECD countries, among which 19 extendedcopyright term at various times between 1991–2005, we found no statisticallyrobust evidence that copyright term extension was associated with higher movie production.In a panel of 17 European countries between 1991–2005, wefound no statistically robust evidence that compliance with the RentalDirective was …

Mobile App Tagging, Ning Chen, Steven C. H. Hoi, Shaohua Li, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

Mobile app tagging aims to assign a list of keywords indicating core functionalities, main contents, key features or concepts of a mobile app. Mobile app tags can be potentially useful for app ecosystem stakeholders or other parties to improve app search, browsing, categorization, and advertising, etc. However, most mainstream app markets, e.g., Google Play, Apple App Store, etc., currently do not explicitly support such tags for apps. To address this problem, we propose a novel auto mobile app tagging framework for annotating a given mobile app automatically, which is based on a search-based annotation paradigm powered by machine learning techniques. …

Online Learning Of Arima For Time Series Prediction, Chenghao Liu, Hoi, Steven C. H., Peilin Zhao, Jianling Sun

Research Collection School Of Computing and Information Systems

Autoregressive integrated moving average (ARIMA) is one of the most popular linear models for time series forecasting due to its nice statistical properties and great flexibility. However, its parameters are estimated in a batch manner and its noise terms are often assumed to be strictly bounded, which restricts its applications and makes it inefficient for handling large-scale real data. In this paper, we propose online learning algorithms for estimating ARIMA models under relaxed assumptions on the noise terms, which is suitable to a wider range of applications and enjoys high computational efficiency. The idea of our ARIMA method is to …

Accurate Online Video Tagging Via Probabilistic Hybrid Modeling, Jialie Shen, Meng Wang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Accurate video tagging has been becoming increasingly crucial for online video management and search. This article documents a novel framework called comprehensive video tagger (CVTagger) to facilitate accurate tag-based video annotation. The system applies both multimodal and temporal properties combined with a novel classification framework with hierarchical structure based on multilayer concept model and regression analysis. The advanced architecture enables effective incorporation of both video concept dependency and temporal dynamics. Using a large-scale test collection containing 50,000 YouTube videos, a set of empirical studies have been carried out and experimental results demonstrate various advantages of CVTagger over the state-of-the-art techniques.

Large-Scale Spatial Data Management On Modern Parallel And Distributed Platforms, Simin You

Dissertations, Theses, and Capstone Projects

Rapidly growing volume of spatial data has made it desirable to develop efficient techniques for managing large-scale spatial data. Traditional spatial data management techniques cannot meet requirements of efficiency and scalability for large-scale spatial data processing. In this dissertation, we have developed new data-parallel designs for large-scale spatial data management that can better utilize modern inexpensive commodity parallel and distributed platforms, including multi-core CPUs, many-core GPUs and computer clusters, to achieve both efficiency and scalability. After introducing background on spatial data management and modern parallel and distributed systems, we present our parallel designs for spatial indexing and spatial join query …

Task-Based User Profiling For Query Refinement (Toque), Chao Xu

Dissertations

The information needs of search engine users vary in complexity. Some simple needs can be satisfied by using a single query, while complicated ones require a series of queries spanning a period of time. A search task, consisting of a sequence of search queries serving the same information need, can be treated as an atomic unit for modeling user’s search preferences and has been applied in improving the accuracy of search results. However, existing studies on user search tasks mainly focus on applying user’s interests in re-ranking search results. Only few studies have examined the effects of utilizing search tasks …

Software Interoperability And The Pods Openhds System, Benjamin S. Heasly Ms

All Student Scholarship

This work addressed challenges of software system interoperability faced by the Open Health and Demographics Surveillance System (OpenHDS). OpenHDS is a distributed application for demographic data collection which was used during a public health intervention in Equatorial Guinea. Specific challenges faced during this intervention included offline data collection and synchronization, changing data collection and software requirements, data size and system performance, and correction of software and data collection errors. This work produced in a new system, the PODS OpenHDS System, which applied four design themes in order to address these challenges: Polymorphism, developer Operations, Declarative style, and Self-description.

Creating A Better World With Information And Communication Technologies: Health Equity, Sajda Qureshi

Information Systems and Quantitative Analysis Faculty Publications

When news broke on 23rd July 2014, that a case of the deadly virus Ebola had been confirmed in Lagos, home to about 21 million people and a major transportation hub, the World held its breath. If not contained, this virus could spread quickly killing a multitude of people around the World. By 15th October, cases of Ebola had been recorded around the World: Liberia reported 4249 cases with 2458 deaths, Sierra Leone reported 3252 cases with 1183 deaths, Guinea 1472 cases with 843 deaths, Nigeria reported 20 cases with 8 deaths, the USA reported 3 cases and 1 death, …

Building And Safety Department Android Mobile Application, Nary Simms

Mathematics and Computer Science Capstones

Research has found that Americans spend 4.5 hours watching television, 1.5 hours listening to the radio, about half an hour reading print and spend a whooping five plus hours per day in digital media (online, mobile, other). Out of these five hours, two hours and twenty minutes are spent on a mobile device (phone or tablet), which is a massive increase of about 575 percent from the twenty-four minutes that was reported in 2010. Flurry, an analytic app company, released data about their tracking of more than 300,000 apps in 2013, and they found the average time spent per day …

Archive - A Data Management Program, James H. Devilbiss, C. Steven Whisnant, Yasmeen Shorish

Yasmeen Shorish

To meet funding agency requirements, a portable data management solution is presented for small research groups. The database created is simple, searchable, robust, and can reside across multiple hard drives. Employing a standard metadata schema for all data, the database ensures a high level of standardization, findability, and organization. The software is written in Perl, runs on UNIX, and presents a web-based user interface. It uses a fast, portable log-in scheme, making it easy to export to other locations. As research continues to move towards more open data sharing and reproducibility, this database solution is agile enough to accommodate external …

An Immersive Telepresence System Using Rgb-D Sensors And Head-Mounted Display, Xinzhong Lu, Ju Shen, Saverio Perugini, Jianjun Yang

Saverio Perugini

We present a tele-immersive system that enables people to interact with each other in a virtual world using body gestures in addition to verbal communication. Beyond the obvious applications, including general online conversations and gaming, we hypothesize that our proposed system would be particularly beneficial to education by offering rich visual contents and interactivity. One distinct feature is the integration of egocentric pose recognition that allows participants to use their gestures to demonstrate and manipulate virtual objects simultaneously. This functionality enables the instructor to effectively and efficiently explain and illustrate complex concepts or sophisticated problems in an intuitive manner. The …