Computer Sciences Commons^™

Relatedness-Based Multi-Entity Summarization, Kalpa Gunaratna, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan, Amit Sheth, Gong Cheng

Kno.e.sis Publications

Representing world knowledge in a machine processable format is important as entities and their descriptions have fueled tremendous growth in knowledge-rich information processing platforms, services, and systems. Prominent applications of knowledge graphs include search engines (e.g., Google Search and Microsoft Bing), email clients (e.g., Gmail), and intelligent personal assistants (e.g., Google Now, Amazon Echo, and Apple’s Siri). In this paper, we present an approach that can summarize facts about a collection of entities by analyzing their relatedness in preference to summarizing each entity in isolation. Specifically, we generate informative entity summaries by selecting: (i) inter-entity facts that are similar and …

A Novel Approach For Classifying Gene Expression Data Using Topic Modeling, Soon Jye Kho, Himi Yalamanchili, Michael L. Raymer, Amit Sheth

Kno.e.sis Publications

Understanding the role of differential gene expression in cancer etiology and cellular process is a complex problem that continues to pose a challenge due to sheer number of genes and inter-related biological processes involved. In this paper, we employ an unsupervised topic model, Latent Dirichlet Allocation (LDA) to mitigate overfitting of high-dimensionality gene expression data and to facilitate understanding of the associated pathways. LDA has been recently applied for clustering and exploring genomic data but not for classification and prediction. Here, we proposed to use LDA inclustering as well as in classification of cancer and healthy tissues using lung cancer …

Information Communication Technology Management As A Gdp Growth Contributor Within Arab League Nations, Jamal Alexander Thompson

Walden Dissertations and Doctoral Studies

The general problem addressed in this study was Arab League nations' over-reliance on fossil fuels as a gross domestic product (GDP) growth driver. Arab League nations that depend primarily on fossil fuel production lack alternative resources for growth in times of fossil fuel usage or price decline. Overdependence on fossil fuels has led to minimal development in other economic sectors, primarily in skilled domestic labor, and to a high dependency on foreign skilled labor for skilled domestic jobs. The purpose of this study was to examine to what extent information communication technology (ICT) management can be a viable GDP growth …

Collaboration Strategies To Reduce Technical Debt, Jeffrey Allen Miko

Walden Dissertations and Doctoral Studies

Inadequate software development collaboration processes can allow technical debt to accumulate increasing future maintenance costs and the chance of system failures. The purpose of this qualitative case study was to explore collaboration strategies software development leaders use to reduce the amount of technical debt created by software developers. The study population was software development leaders experienced with collaboration and technical debt at a large health care provider in the state of California. The data collection process included interviews with 8 software development leaders and reviewing 19 organizational documents relating to software development methods. The extended technology acceptance model was used …

A Semantics-Based Measure Of Emoji Similarity, Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran

Kno.e.sis Publications

Emoji have grown to become one of the most important forms of communication on the web. With its widespread use, measuring the similarity of emoji has become an important problem for contemporary text processing since it lies at the heart of sentiment analysis, search, and interface design tasks. This paper presents a comprehensive analysis of the semantic similarity of emoji through embedding models that are learned over machine-readable emoji meanings in the EmojiNet knowledge base. Using emoji descriptions, emoji sense labels and emoji sense definitions, and with different training corpora obtained from Twitter and Google News, we develop and test …

Identifying Depressive Disorder In The Twitter Population, Goonmeet Bajaj, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan, Amit Sheth

Kno.e.sis Publications

Depression is a highly prevalent public health challenge and a major cause of disability across the globe.

• Annually 6.7% of Americans (that is, more than 16 million).
• Traditional approaches to curb depression involve survey·based methods via phone or online questionnaires.
• Large temporal gaps and cognitive bias.

Social media provides a method for learning users' feelings, emotions, behaviors, and decisions in real-time.

Overcoming The Adverse Impact Of Internal Subculture Communications Within Organizations, Terrence Lee Farrier

Walden Dissertations and Doctoral Studies

The need for clear and organizationally effective communications is necessary to maintain sustainability as competition increases. Current research has not addressed problems associated with senior managers' clarity and intent and the misinterpretation by midlevel managers of that intent, causing division managers to misinterpret the company plans. Unresolved miscommunications may lead to destructive subculture development. This mixed methods design focused on how to minimize the confusion that manifests between senior and midlevel management within diverse and decentralized decision support structures. The secondary purpose was to advocate for the identification of divisional misalignment and provide information for a tool to help senior …

Infodemiology For Syndromic Surveillance Of Dengue And Typhoid Fever In The Philippines, Ma. Regina Justina E. Estuar, Kennedy E. Espina

Department of Information Systems & Computer Science Faculty Publications

Finding determinants of disease outbreaks before its occurrence is necessary in reducing its impact in populations. The supposed advantage of obtaining information brought by automated systems fall short because of the inability to access real-time data as well as interoperate fragmented systems, leading to longer transfer and processing of data. As such, this study presents the use of realtime latent data from social media, particularly from Twitter, to complement existing disease surveillance efforts. By being able to classify infodemiological (health-related) tweets, this study is able to produce a range of possible disease incidences of Dengue and Typhoid Fever within the …

Reducing Technology Costs For Small Real Estate Businesses Using Cloud And Mobility, Linda Anne-Marie Mcintosh

Walden Dissertations and Doctoral Studies

Increased client accessibility strategies, awareness of technology cost, and factors of third-party data security capabilities are elements small real estate business (SREB) owners need to know before adopting cloud and mobility technology. The purpose of this multiple case study was to explore the strategies SREB owners use to implement cloud and mobility products to reduce their technology costs. The target population consisted of 3 SREB owners who had experience implementing cloud and mobility products in their businesses in the state of Texas. The conceptual framework of this research study was the technology acceptance model theory. Semistructured interviews were conducted and …

Evaluating Sociotechnical Factors Associated With Telecom Service Provisioning: A Case Study, Fahad Iqbal

Walden Dissertations and Doctoral Studies

Provisioning Internet services remains an area of concern for Internet service providers. Despite investments to improve resources and technology, the understanding of sociotechnical factors that influence the service-provisioning life cycle remains limited. The purpose of this case study was to evaluate the influence of sociotechnical factors associated with telecom service provisioning and to explore the critical success and failure factors, specifically in the telecommunication industry of Kuwait. Guided by sociotechnical systems theory, this qualitative exploratory case study approach examined a purposeful sample of 19 participants comprising of managers, engineers, and technicians who had the knowledge and experience of the service-provisioning …

Viewed By Too Many Or Viewed Too Little: Using Information Dissemination For Audience Segmentation, Bernard J. Jansen, Soon-Gyu Jung, Joni Salminen, Jisun An, Haewoon Kwak

Research Collection School Of Computing and Information Systems

The identification of meaningful audience segments, such as groups of users, consumers, readers, audience, etc., has important applicability in a variety of domains, including for content publishing. In this research, we seek to develop a technique for determining both information dissemination and information discrimination of online content in order to isolate audience segments. The benefits of the technique include identification of the most impactful content for analysis. With 4,320 online videos from a major news organization, a set of audience attributes, and more than 58 million interactions from hundreds of thousands of users, we isolate the key pieces of content …

Fine-Grained Sentiment Analysis Of Social Media With Emotion Sensing, Zhaoxia Wang, Chee Seng Chong, Landy Lan, Yinping Yang, Beng-Seng Ho, Joo Chuan Tong

Research Collection School Of Computing and Information Systems

Social media is arguably the richest source of human generated text input. Opinions, feedbacks and critiques provided by internet users reflect attitudes and sentiments towards certain topics, products, or services. The sheer volume of such information makes it effectively impossible for any group of persons to read through. Thus, social media sentiment analysis has become an important area of work to make sense of the social media talk. However, most existing sentiment analysis techniques focus only on the aggregate level, classifying sentiments broadly into positive, neutral or negative, and lack the capabilities to perform fine-grained sentiment analysis. This paper describes …

The Transition Experiences Of International Graduate Students In Clark University School Of Professional Studies, Xuesong Huang, Mingyang Lian, Dang Trung, Jay Sheth, Yuwei Yang, Irina Klimenko

School of Professional Studies

In the last decade, the School of Professional Studies at Clark University has witnessed a sharp increase in international students. More and more international students in the millennial generation have entered the School of Professional Studies pursuing one of the two-year graduate programs: Master of Science in Professional Studies, Master of Science in Public Administration, and Master of Science in Information Technology. In the past, working adult student dominant the program. These students already had a career outside the classrooms before them came to study. The millennial international students have generated new adjustment problems. Some of the transition issues of …

Preliminary Investigation Of Walking Motion Using A Combination Of Image And Signal Processing, Bradley Schneider, Tanvi Banerjee

Kno.e.sis Publications

We present the results of analyzing gait motion in first-person video taken from a commercially available wearable camera embedded in a pair of glasses. The video is analyzed with three different computer vision methods to extract motion vectors from different gait sequences from four individuals for comparison against a manually annotated ground truth dataset. Using a combination of signal processing and computer vision techniques, gait features are extracted to identify the walking pace of the individual wearing the camera as well as validated using the ground truth dataset. Our preliminary results indicate that the extraction of activity from the video …

Hashtag Recommendation With Topical Attention-Based Lstm, Yang Li, Ting Liu, Jing Jiang, Liang Zhang

Research Collection School Of Computing and Information Systems

Microblogging services allow users to create hashtags to categorize their posts. In recent years,the task of recommending hashtags for microblogs has been given increasing attention. However,most of existing methods depend on hand-crafted features. Motivated by the successful use oflong short-term memory (LSTM) for many natural language processing tasks, in this paper, weadopt LSTM to learn the representation of a microblog post. Observing that hashtags indicatethe primary topics of microblog posts, we propose a novel attention-based LSTM model whichincorporates topic modeling into the LSTM architecture through an attention mechanism. Weevaluate our model using a large real-world dataset. Experimental results show that …

Efficient Online Summarization Of Large-Scale Dynamic Networks, Qiang Qu, Siyuan Liu, Feida Zhu, Christian S. Jensen

Research Collection School Of Computing and Information Systems

Information diffusion in social networks is often characterized by huge participating communities and viral cascades of high dynamicity. To observe, summarize, and understand the evolution of dynamic diffusion processes in an informative and insightful way is a challenge of high practical value. However, few existing studies aim to summarize networks for interesting dynamic patterns. Dynamic networks raise new challenges not found in static settings, including time sensitivity, online interestingness evaluation, and summary traceability, which render existing techniques inadequate. We propose dynamic network summarization to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or …

‘Tweetboard’ – A Case Study Of Developing A Micro-Blogging Platform For Higher Education, Shao Cheh Joyce Hsu, Gan, Benjamin, Jin Lee, Shu Hui Sheryl Lim, Xie Yan Jeremy Lim, Thomas Menkhoff, Si Xian Sherman Tan, Charles Jason Woodard, Qiu Cheng Yap

Research Collection School Of Computing and Information Systems

This paper reports experiences made at an Asian university in developing a social media platform based on Twitter in the context of a final year capstone project where information systems management students get an opportunity to solve ‘a real-world problem for a real client’. In this case study, the challenge was provided by a faculty member’s request for an interactive social media application which engages less outspoken students in class via a social medium they are familiar with: Twitter. We reconstruct the project’s evolution; describe the main features of the application called ‘TweetBoard’ and share lessons learned in developing a …

From Footprint To Evidence: An Exploratory Study Of Mining Social Data For Credit Scoring, Guangming Guo, Feida Zhu, Enhong Chen, Qi Liu, Le Wu, Chu Guan

Research Collection School Of Computing and Information Systems

With the booming popularity of online social networks like Twitter and Weibo, online user footprints are accumulating rapidly on the social web. Simultaneously, the question of how to leverage the large-scale user-generated social media data for personal credit scoring comes into the sight of both researchers and practitioners. It has also become a topic of great importance and growing interest in the P2P lending industry. However, compared with traditional financial data, heterogeneous social data presents both opportunities and challenges for personal credit scoring. In this article, we seek a deep understanding of how to learn users’ credit labels from social …

Domain Identification For Intention Posts On Online Social Media, Thai Le Luong, Quoc Tuan Truong, Hai-Trieu Dang, Xuan Hieu Phan

Research Collection School Of Computing and Information Systems

Today, more and more Internet users are willing to share their feeling, activities, and even their intention about what they plan to do on online social media. We can easily see posts like "I plan to buy an apartment this year", or "We are looking for a tour for 3 people to Nha Trang" on online forums or social networks. Recognizing those user intents on online social media is really useful for targeted advertising. However fully understanding user intents is a complicated and challenging process which includes three major stages: user intent filtering, intent domain identification, and intent parsing and …

Towards A Computational Model Of Frame Of Reference Alignment In Swedish Dialogue, Simon Dobnik, Christine Howes, Kim Demaret, John D. Kelleher

Conference papers

In this paper we examine how people negotiate, interpret and repair the frame of reference (FoR) in online text based dialogues discussing spatial scenes in Swedish. We describe work-in-progress in which participants are given different perspectives of the same scene and asked to locate several objects that are only shown on one of their pictures. This task requires participants to coordinate on FoR in order to identify the missing objects. This study has implications for situated dialogue systems.

Media Reinvented, Geoff Tan

Asian Management Insights

The brave new world of digital media.

Spiteful, One-Off, And Kind: Predicting Customer Feedback Behavior On Twitter, Agus Sulistya, Abhishek Sharma, David Lo

Research Collection School Of Computing and Information Systems

Social media provides a convenient way for customers to express their feedback to companies. Identifying different types of customers based on their feedback behavior can help companies to maintain their customers. In this paper, we use a machine learning approach to predict a customer’s feedback behavior based on her first feedback tweet. First, we identify a few categories of customers based on their feedback frequency and the sentiment of the feedback. We identify three main categories: spiteful, one-off, and kind. Next, we build a model to predict the category of a customer given her first feedback. We use profile and …

On Profiling Bots In Social Media, Richard J. Oentaryo, Arinto Murdopo, Philips K. Prasetyo, Ee Peng Lim

Research Collection School Of Computing and Information Systems

The popularity of social media platforms such as Twitter has led to the proliferation of automated bots, creating both opportunities and challenges in information dissemination, user engagements, and quality of services. Past works on profiling bots had been focused largely on malicious bots, with the assumption that these bots should be removed. In this work, however, we find many bots that are benign, and propose a new, broader categorization of bots based on their behaviors. This includes broadcast, consumption, and spam bots. To facilitate comprehensive analyses of bots and how they compare to human accounts, we develop a systematic profiling …

Introduction To Ships Satellite Tracking Systems, Dimov Stojce Ilcev

UBT International Conference

This paper introduces the current and new Satellite solutions for local and global tracking of ships for enhanced Ship Traffic Control (STC) and Ship Traffic Management (STM) at sea, in sea passages, approaching to the anchorages and inside of seaports. All transportation systems and especially for maritime applications require far more sophisticated technology solutions and equipment for modern Satellite ship tracking than current standalone the US GPS or Russian GLONAS positioning systems. The existing and forthcoming Global Ship Tracking (GST), Satellite Data Link (SDL) and Local Ship Tracking (LST) systems with Space and Ground Segment infrastructures for all three systems …

Cloud Computing And Enterprise Data Reliability, Luan Gashi

UBT International Conference

Cloud services offer many benefits from information and communication technology that to be credible must first be secured. To use the potential of cloud computing, data is transferred, processed and stored in the infrastructures of these service providers. This indicates that the owners of data, particularly enterprises, have puzzled when storing their data is done outside the scope of their control.

Research conducted on this topic show how this should be addressed unequivocally. The provided information on the organization of cloud computing models, services and standards, with a focus on security aspects in protecting enterprise data where emphasis shows how …

Security Analysis Of Wireless Ban In E-Health, Romina Muka, Sule Yildrim-Yayilgan, Kozeta Sevrani

UBT International Conference

The Wireless Body Area Network (WBAN) has gained popularity as a new technology for e-Health, and is considered as one of the key research areas in computer science and healthcare applications. WBAN collects patients’ data, monitors constantly their physiological parameters, using small implantable or wearable sensors, and communicates these data using wireless communication techniques in short range. WBAN is playing a huge role in improving the quality of healthcare. Still, due to sensitive and concurrent nature of e-Heath systems, current research has showed that designers must take into considerations the security and privacy protection of the data collected by a …

Analysis Of The Mobile Market In 2014 In Macedonia, Recommendations For Better Development And Improved Quality Of Mobile Services, Arsov Boris, Trajkovski Vasko

UBT International Conference

In order to regulate the electronic communications market in a systematic way, the Agency for Electronic Communications, as a regulatory body in the field of electronic communications, has strongly set issues and targets to be achieved. The Agency has guidelines how to achieve the issues of a competitive market where conditions for using the electronic communications services with best quality and best prices are going to be created for the end users.

Descriptive Analysis Of Characteristics: A Case Study Of A Phone Call Network Graph, Orgeta Gjermëni, Miftar Ramosaco

UBT International Conference

Nowadays, systematic collection of data has necessitated a detailed statistical analysis as a necessary tool to make a mathematical characterization of them with the purpose of gathering information about the present or the future. Our aim in this paper is to analyze a landline phone call network graph from the perspective of descriptive analysis. We explore the characteristics and structural properties of the network graph constructed using an anonymous collection of data gathered from a Call Data Records of a telecommunication operator center located in south of Albania. The R statistical computing platform is used for network graph analysis.

Circuit Design For Green Communications – Methods, Tools And Examples, Galia Marinova, Zdravka Tchobanova

UBT International Conference

The paper makes an overview of the existing methods applied for circuit design with low power consumption objective. It considers Computer-Aided Design (CAD) tools and modules for power consumption estimation at the design stage. For analog and mixed analog-digital circuit design, the power estimation options in ORCAD Design Suit with PSpice and Analog Filter Wizard are studied. For digital communication systems the study covers the power estimation, analysis and optimization in ISE and Vivado systems, Xilinx Power Estimator (XPE) tool and spreadsheet, the XPower Analyzer, as well as similar tools proposed by ALTERA - PowerPlay Early Power Estimator and QUARTUS …

A Summary Of Classification And Regression Tree With Application, Adem Meta

UBT International Conference

Classification and regression tree (CART) is a non-parametric methodology that was introduced first by Breiman and colleagues in 1984. CART is a technique which divides populations into meaningful subgroups that allows the identification of groups of interest. CART as a classification method constructs decision trees. Depending on information that is available about the dataset, a classification tree or a regression tree can be constructed. The first part of this paper describes the fundamental principles of tree construction, pruning procedure and different splitting algorithms. The second part of the paper answers the questions why or why not the CART method should …