Physical Sciences and Mathematics Commons^™

The Retransmission Of Rumor And Rumor Correction Messages On Twitter, Alton Y. K. Chua, Cheng-Ying Tee, Augustine Pang, Ee-Peng Lim

Research Collection Lee Kong Chian School Of Business

This article seeks to examine the relationships among source credibility, message plausibility, message type (rumor or rumor correction) and retransmission of tweets in a rumoring situation. From a total of 5,885 tweets related to the rumored death of the founding father of Singapore Lee Kuan Yew, 357 original tweets without an “RT” prefix were selected and analyzed using negative binomial regression analysis. The results show that source credibility and message plausibility are correlated with retransmission. Also, rumor correction tweets are retweeted more than rumor tweets. Moreover, message type moderates the relationship between source credibility and retransmission as well as that …

Selecting Link Resolver And Knowledge Base Software: Implications Of Interoperability, Cyndy Chisare, Jody C. Fagan, David J. Gaines, Michael Trocchia

Libraries

Link resolver software and their associated knowledge bases are essential technologies for modern academic libraries. However, because of the increasing number of possible integrations involving link resolver software and knowledge bases, a library’s vendor relationships, product choices, and consortial arrangements may have the most dramatic effects on the user experience and back-end maintenance workloads. A project team at a large comprehensive university recently investigated link resolver products in an attempt to increase efficiency of back-end workflows while maintaining or improving the patron experience. The methodology used for product comparison may be useful for other libraries.

On Self-Selection Biases In Online Product Reviews, Nan Hu, Paul A. Pavlou, Jie Zhang

Research Collection School Of Computing and Information Systems

Online product reviews help consumers infer product quality, and the mean (average) rating is often used as a proxy for product quality. However, two self-selection biases, acquisition bias (mostly consumers with a favorable predisposition acquire a product and hence write a product review) and underreporting bias (consumers with extreme, either positive or negative, ratings are more likely to write reviews than consumers with moderate product ratings), render the mean rating a biased estimator of product quality, and they result in the well-known J-shaped (positively skewed, asymmetric, bimodal) distribution of online product reviews. To better understand the nature and consequences of …

Sap: Improving Continuous Top-K Queries Over Streaming Data, Rui Zhu, Bin Wang, Xiaochun Yang, Baihua Zheng, Guoren Wang

Research Collection School Of Computing and Information Systems

Continuous top-k query over streaming data is a fundamental problem in database. In this paper, we focus on the sliding window scenario, where a continuous top-k query returns the top-k objects within each query window on the data stream. Existing algorithms support this type of queries via incrementally maintaining a subset of objects in the window and try to retrieve the answer from this subset as much as possible whenever the window slides. However, since all the existing algorithms are sensitive to query parameters and data distribution, they all suffer from expensive incremental maintenance cost. In this paper, we propose …

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

Research Collection School Of Computing and Information Systems

It becomes increasingly popular that some large online retailers such as Amazon open their platforms to allow third-party retail competitors to sell on their own platforms. We develop an analytical model to examine this retailer market place model and its business impact. We assume that a leading retailer has both valuation advantage that may come from its reputation and information advantage that may come from its brand awarenewss. We find that the availability of relatively low-cost advertising through social media or search engine can effectively reduce the leading retailer's information advantage, and thus be an important driving force for its …

Breathprint: Breathing Acoustics-Based User Authentication, Jagmohan Chauhan, Yining Hu, Suranga Sereviratne, Archan Misra, Aruna Sereviratne, Youngki Lee

Research Collection School Of Computing and Information Systems

We propose BreathPrint, a new behavioural biometric signature based on audio features derived from an individual's commonplace breathing gestures. Specifically, BreathPrint uses the audio signatures associated with the three individual gestures: sniff, normal, and deep breathing, which are sufficiently different across individuals. Using these three breathing gestures, we develop the processing pipeline that identifies users via the microphone sensor on smartphones and wearable devices. In BreathPrint, a user performs breathing gestures while holding the device very close to their nose. Using off-the-shelf hardware, we experimentally evaluate the BreathPrint prototype with 10 users, observed over seven days. We show that users …

Enabling Gesture-Based Interactions With Objects, Longfei Shangguan, Zimu Zhou, Kyle Jamieson

Research Collection School Of Computing and Information Systems

No abstract provided.

Is The Whole Greater Than The Sum Of Its Parts?, Liangyue Li, Hanghang Tong, Yong Wang, Conglei Shi, Nan Cao, Norbou Buchler

Research Collection School Of Computing and Information Systems

The PART-WHOLE relationship routinely finds itself in many disciplines, ranging from collaborative teams, crowdsourcing, autonomous systems to networked systems. From the algorithmic perspective, the existing work has primarily focused on predicting the outcomes of the whole and parts, by either separate models or linear joint models, which assume the outcome of the parts has a linear and independent effect on the outcome of the whole. In this paper, we propose a joint predictive method named PAROLE to simultaneously and mutually predict the part and whole outcomes. The proposed method offers two distinct advantages over the existing work. First (Model Generality), …

Charitable Fundraising: Gaining Donors' Trust On Online Platforms, Deserinas Sulaeman

Research Collection School Of Computing and Information Systems

Trust is crucial in the relationships between charitable fundraisers and potential donors. This study examines factors that can help fundraisers gain potential donors’ trust, which is crucial to the success of the campaigns. Examining charitable fundraising campaigns on an online platform, this study finds that trust issues can be mitigated by providing a campaign description that is more sophisticated, more informative, and with fewer errors. Additionally, setting a higher campaign funding goal tends to lead to a more successful campaign. These characteristics likely reflect a competent, committed, and passionate fundraiser. On the other hand, mere exposure to a wide set …

Processing Long Queries Against Short Text: Top-K Advertisement Matching In News Stream Applications, Dongxiang Zhang, Yuchen Li, Ju Fan, Lianli Gao, Fumin Shen, Heng Tao Shen

Research Collection School Of Computing and Information Systems

Many real applications in real-time news stream advertising call for efficient processing of long queriesagainst short text. In such applications, dynamic news feeds are regarded as queries to match against anadvertisement (ad) database for retrieving the k most relevant ads. The existing approaches to keywordretrieval cannot work well in this search scenario when queries are triggered at a very high frequency.To address the problem, we introduce new techniques to significantly improve search performance. First,we devise a two-level partitioning for tight upper bound estimation and a lazy evaluation scheme to delayfull evaluation of unpromising candidates, which can bring three to four …

Towards Unobtrusive Mental Well-Being Monitoring For Independent-Living Elderly, Sinh Huynh, Hwee-Pink Tan, Youngki Lee

Research Collection School Of Computing and Information Systems

It is essential to proactively detect mental health problems such as loneliness and depression in the independently-living elderly for timely intervention by caregivers. In this paper, we introduce an unobtrusive sensor-enabled monitoring system that has been deployed to 50 government housing ats with the independent-living elderly for two years. Then, we also present our initial findings from the 6-month sensor data between August 2015 and April 2016 as well as the survey data to measure the subjective well-being indicator. Our study showed the promising results that "room-level movements within a house" and "going out" behavior captured by our simple sensor …

Exploiting Android System Services Through Bypassing Service Helpers, Yachong Gu, Yao Cheng, Lingyun Ying, Yemian Lu, Qi Li, Purui Su

Research Collection School Of Computing and Information Systems

Android allows applications to communicate with system service via system service helper so that applications can use various functions wrapped in the system services. Meanwhile, system services leverage the service helpers to enforce security mechanisms, e.g. input parameter validation, to protect themselves against attacks. However, service helpers can be easily bypassed, which poses severe security and privacy threats to system services, e.g., privilege escalation, function execution without users’ interactions, system service crash, and DoS attacks. In this paper, we perform the first systematic study on such vulnerabilities and investigate their impacts. We develop a tool to analyze all system services …

Compress: A Comprehensive Framework Of Trajectory Compression In Road Networks, Yunheng Han, Weiwei Sun, Baihua Zheng

Research Collection School Of Computing and Information Systems

More and more advanced technologies have become available to collect and integrate an unprecedented amount of data from multiple sources, including GPS trajectories about the traces of moving objects. Given the fact that GPS trajectories are vast in size while the information carried by the trajectories could be redundant, we focus on trajectory compression in this article. As a systematic solution, we propose a comprehensive framework, namely, COMPRESS (Comprehensive Paralleled Road-Network-Based Trajectory Compression), to compress GPS trajectory data in an urban road network. In the preprocessing step, COMPRESS decomposes trajectories into spatial paths and temporal sequences, with a thorough justification …

An Exploratory Study Of Functionality And Learning Resources Of Web Apis On Programmableweb, Yuan Tian, Pavneet Singh Kochhar, David Lo

Research Collection School Of Computing and Information Systems

Web APIs provide various functionalities that can be leveraged by developers in building their applications. ProgrammableWeb, which is the largest and most active web API and mashup collection, provides a record of thousands of web APIs and mashups. However, important properties about these large number of web APIs, such as their functionality and support/resources for learning, have never been studied by the existing research work. In this study, we perform an exploratory analysis on functionality and learning resources of 9,883 web APIs and 4,315 mashups listed on ProgrammableWeb, and find that: (1) web APIs provide a wide range of functionalities …

The Dark Side Of Banning Hacking Technique Discussion, Qiu-Hong Wang, Ting Zhang Le

Research Collection School Of Computing and Information Systems

Prior studies have evidenced the effectiveness of more severe and broader enforcement in deterringcybercrimes. This study addresses the other side of the story. Our data analysis shows that theenforcement against the production / distribution / possession of computer misuse tools tends toincrease the contribution on detection and protection related posts in online hacker forums. Butthis enforcement may discourage those contributors who had originally actively contributed to theprotection discussions. Thus government regulations have to be cautiously justify the incentives ofmultiple parties in the cybersecurity context.

Well-Tuned Algorithms For The Team Orienteering Problem With Time Windows, Aldy Gunawan, Hoong Chuin Lau, Kun Lu, Lu Kun

Research Collection School Of Computing and Information Systems

The Team Orienteering Problem with Time Windows (TOPTW) is the extension of the Orienteering Problem (OP) where each node is limited by a predefined time window during which the service has to start. The objective of the TOPTW is to maximize the total collected score by visiting a set of nodes with a limited number of paths. We propose two algorithms, Iterated Local Search and a hybridization of Simulated Annealing and Iterated Local Search (SAILS), to solve the TOPTW. As indicated in multiple research works on algorithms for the OP and its variants, determining appropriate parameter values in a statistical …

Evidence-Based-Review-Of-Academic-Web-Search-Engines-Preprint.Pdf, Jody C. Fagan 5609471

Jody C Fagan

Sliding Window Based Feature Extraction And Traffic Clustering For Green Mobile Cyberphysical Systems, Jiao Zhang, Li Zhou, Angran Xiao, Sai Zeng, Haitao Zhao, Jibo Wei

Publications and Research

Both the densification of small base stations and the diversity of user activities bring huge challenges for today’s heterogeneous networks, either heavy burdens on base stations or serious energy waste. In order to ensure coverage of the network while reducing the total energy consumption, we adopt a green mobile cyberphysical system (MCPS) to handle this problem. In this paper, we propose a feature extractionmethod using sliding window to extract the distribution feature of mobile user equipment (UE), and a case study is presented to demonstrate that the method is efficacious in reserving the clustering distribution feature. Furthermore, we present traffic …

Adding Differential Privacy In An Open Board Discussion Board System, Pragya Rana

Master's Projects

This project implements a privacy system for statistics generated by the Yioop search and discussion board system. Statistical data for such a system consists of various counts, sums, and averages that might be displayed for groups, threads, etc. When statistical data is made publicly available, there is no guarantee of preserving the privacy of an individual. Ideally, any data extracted should not reveal any sensitive information about an individual. In order to help achieve this, we implemented a Differential Privacy mechanism for Yioop. Differential privacy preserves privacy up to some controllable parameters of the number of items or individuals being …

An Open Source Discussion Group Recommendation System, Sarika Padmashali

Master's Projects

A recommendation system analyzes user behavior on a website to make suggestions about what a user should do in the future on the website. It basically tries to predict the “rating” or “preference” a user would have for an action. Yioop is an open source search engine, wiki system, and user discussion group system managed by Dr. Christopher Pollett at SJSU. In this project, we have developed a recommendation system for Yioop where users are given suggestions about the threads and groups they could join based on their user history. We have used collaborative filtering techniques to make recommendations and …

Document Classification Using Machine Learning, Ankit Basarkar

Master's Projects

To perform document classification algorithmically, documents need to be represented such that it is understandable to the machine learning classifier. The report discusses the different types of feature vectors through which document can be represented and later classified. The project aims at comparing the Binary, Count and TfIdf feature vectors and their impact on document classification. To test how well each of the three mentioned feature vectors perform, we used the 20-newsgroup dataset and converted the documents to all the three feature vectors. For each feature vector representation, we trained the Naïve Bayes classifier and then tested the generated classifier …

Reducing Query Latency For Information Retrieval, Swapnil Satish Kamble

Master's Projects

As the world is moving towards Big Data, NoSQL (Not only SQL) databases are gaining much more popularity. Among the other advantages of NoSQL databases, one of their key advantage is that they facilitate faster retrieval for huge volumes of data, as compared to traditional relational databases. This project deals with one such popular NoSQL database, Apache HBase. It performs quite efficiently in cases of retrieving information using the rowkey (similar to a primary key in a SQL database). But, in cases where one needs to get information based on non-rowkey columns, the response latency is higher than what we …

Headline Generation Using Deep Neural Networks, Dhruven Vora

Master's Projects

News headline generation is one of the important text summarization tasks. Human generated news headlines are generally intended to catch the eye rather than provide useful information. There have been many approaches to generate meaningful headlines by either using neural networks or using linguistic features. In this report, we are proposing a novel approach based on integrating Hedge Trimmer, which is a grammar based extractive summarization system with a deep neural network abstractive summarization system to generate meaningful headlines. We analyze the results against current recurrent neural network based headline generation system.

A Chatbot Framework For Yioop, Harika Nukala

Master's Projects

Over the past few years, messaging applications have become more popular than Social networking sites. Instead of using a specific application or website to access some service, chatbots are created on messaging platforms to allow users to interact with companies’ products and also give assistance as needed. In this project, we designed and implemented a chatbot Framework for Yioop. The goal of the Chatbot Framework for Yioop project is to provide a platform for developers in Yioop to build and deploy chatbot applications. A chatbot is a web service that can converse with users using artificial intelligence in messaging platforms. …

Named Entity Recognition And Classification For Natural Language Inputs At Scale, Shreeraj Dabholkar

Master's Projects

Natural language processing (NLP) is a technique by which computers can analyze, understand, and derive meaning from human language. Phrases in a body of natural text that represent names, such as those of persons, organizations or locations are referred to as named entities. Identifying and categorizing these named entities is still a challenging task, research on which, has been carried out for many years. In this project, we build a supervised learning based classifier which can perform named entity recognition and classification (NERC) on input text and implement it as part of a chatbot application. The implementation is then scaled …

Lightweight Data Aggregation Scheme Against Internal Attackers In Smart Grid Using Elliptic Curve Cryptography, Debiao He, Sherali Zeadally, Huaqun Wang, Qin Liu

Information Science Faculty Publications

Recent advances of Internet and microelectronics technologies have led to the concept of smart grid which has been a widespread concern for industry, governments, and academia. The openness of communications in the smart grid environment makes the system vulnerable to different types of attacks. The implementation of secure communication and the protection of consumers’ privacy have become challenging issues. The data aggregation scheme is an important technique for preserving consumers’ privacy because it can stop the leakage of a specific consumer’s data. To satisfy the security requirements of practical applications, a lot of data aggregation schemes were presented over the …

Recognition, Internalization, Growth: Intuitive Design For Archival Representation, Jaime L. Ganzel

Graduate Student Symposium

Although there is a pressing need for archival description and access systems to be more intuitive and user-friendly, the uniqueness of archival records presents significant barriers to establishing simplistic and standardized conventions for the representation of archival materials. Indecipherable finding aids and access tools prevent new and inexperienced researchers from accessing the unique information and documentation held in archives. This article aims to help open the archival record to new and non-traditional archival users, support individual development of archival literacy skills, and cultivate a greater level of archival awareness in our society by developing a usable model for archivists to …

Software Development For Home Energy Audits: Reducing Energy Consumption In Harrisonburg Through Technology, Brantley E. Gilbert

Senior Honors Projects, 2010-2019

Fossil fuels play a vital role in our daily lives. Oil, natural gas, and coal powers our cars, heats our homes and water, and are used by power companies to generate the massive amounts of electricity used every day by the United States. However, this reliance on a finite source of energy is not sustainable. Fossil fuels such as these are non-renewable resources whose production will eventually be unable to keep up with the rate of consumption. Furthermore, the extraction of the stored energy in these fuels through combustion releases harmful substances into the environment, including toxins and greenhouse gases …

Mining Of Primary Healthcare Patient Data With Selective Multimorbid Diseases, Annette Megerdichian Azad

Electronic Thesis and Dissertation Repository

Despite a large volume of research on the prognosis, diagnosis and overall burden of multimorbidity, very little is known about socio-demographic characteristics of multimorbid patients. This thesis aims to analyze the socio-demographic characteristics of patients with multiple chronic conditions (multimorbidity), focusing on patient groups sharing the same combination of diseases. Several methods were explored to analyze the co-occurrence of multiple chronic diseases as well as the associations between socio-demographics and chronic conditions. These methods include disease pair distributions over gender, age groups and income level quintiles, Multimorbidity Coefficients for measuring the concurrence of disease pairs and triples, and k-modes clustering …

Mining Helpdesk Databases For Professional Development Topic Discovery, Joel T. Lowsky

All Theses And Dissertations

This single-site, instrumental case study created and tested a methodological road map by which academic institutions can use text data mining techniques to derive technology skillset weaknesses and professional development topics from the site’s technical support helpdesk database. The methods employed were described in detail and applied to the helpdesk database of an independent, co-educational boarding high school in the northeastern United States. Standard text data mining procedures, including the formation of a wordlist (frequently occurring terms), and the creation and application of clustering (automated data grouping) and classification (automated data labeling) models generated meaningful and revealing themes from the …