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Articles 3091 - 3120 of 7250
Full-Text Articles in Databases and Information Systems
On Analyzing Job Hop Behavior And Talent Flow Networks, Richard J. Oentaryo, Xavier Jayaraj Siddarth Ashok, Ee-Peng Lim, Philips Kokoh Prasetyo
On Analyzing Job Hop Behavior And Talent Flow Networks, Richard J. Oentaryo, Xavier Jayaraj Siddarth Ashok, Ee-Peng Lim, Philips Kokoh Prasetyo
Research Collection School Of Computing and Information Systems
Analyzing job hopping behavior is important for theunderstanding of job preference and career progression of working individuals.When analyzed at the workforce population level, job hop analysis helps to gaininsights of talent flow and organization competition. Traditionally, surveysare conducted on job seekers and employers to study job behavior. While surveysare good at getting direct user input to specially designed questions, they areoften not scalable and timely enough to cope with fast-changing job landscape.In this paper, we present a data science approach to analyze job hops performedby about 490,000 working professionals located in a city using their publiclyshared profiles. We develop several …
Collaborative Topic Regression With Denoising Autoencoder For Content And Community Co-Representation, Trong T. Nguyen, Hady W. Lauw
Collaborative Topic Regression With Denoising Autoencoder For Content And Community Co-Representation, Trong T. Nguyen, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Personalized recommendation of items frequently faces scenarios where we have sparse observations on users' adoption of items. In the literature, there are two promising directions. One is to connect sparse items through similarity in content. The other is to connect sparse users through similarity in social relations. We seek to integrate both types of information, in addition to the adoption information, within a single integrated model. Our proposed method models item content via a topic model, and user communities via an autoencoder model, while bridging a user's community-based preference to her topic-based preference. Experiments on public real-life data showcase the …
Indexable Bayesian Personalized Ranking For Efficient Top-K Recommendation, Dung D. Le, Hady W. Lauw
Indexable Bayesian Personalized Ranking For Efficient Top-K Recommendation, Dung D. Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Top-k recommendation seeks to deliver a personalized recommendation list of k items to a user. The dual objectives are (1) accuracy in identifying the items a user is likely to prefer, and (2) efficiency in constructing the recommendation list in real time. One direction towards retrieval efficiency is to formulate retrieval as approximate k nearest neighbor (kNN) search aided by indexing schemes, such as locality-sensitive hashing, spatial trees, and inverted index. These schemes, applied on the output representations of recommendation algorithms, speed up the retrieval process by automatically discarding a large number of potentially irrelevant items when given a user …
Answerbot: Automated Generation Of Answer Summary To Developers’ Technical Questions, Bowen Xu, Zhenchang Xing, Xin Xia, David Lo
Answerbot: Automated Generation Of Answer Summary To Developers’ Technical Questions, Bowen Xu, Zhenchang Xing, Xin Xia, David Lo
Research Collection School Of Computing and Information Systems
The prevalence of questions and answers on domain-specific Q&A sites like Stack Overflow constitutes a core knowledge asset for software engineering domain. Although search engines can return a list of questions relevant to a user query of some technical question, the abundance of relevant posts and the sheer amount of information in them makes it difficult for developers to digest them and find the most needed answers to their questions. In this work, we aim to help developers who want to quickly capture the key points of several answer posts relevant to a technical question before they read the details …
Sourcevote: Fusing Multi-Valued Data Via Inter-Source Agreements, Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Mahmoud Barhamgi, Lina Yao, Anne H.H. Ngu
Sourcevote: Fusing Multi-Valued Data Via Inter-Source Agreements, Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Mahmoud Barhamgi, Lina Yao, Anne H.H. Ngu
Research Collection School Of Computing and Information Systems
Data fusion is a fundamental research problem of identifying true values of data items of interest from conflicting multi-sourced data. Although considerable research efforts have been conducted on this topic, existing approaches generally assume every data item has exactly one true value, which fails to reflect the real world where data items with multiple true values widely exist. In this paper, we propose a novel approach,SourceVote, to estimate value veracity for multi-valued data items. SourceVote models the endorsement relations among sources by quantifying their two-sided inter-source agreements. In particular, two graphs are constructed to model inter-source relations. Then two aspects …
Tweet Geolocation: Leveraging Location, User And Peer Signals, Wen-Haw Chong, Ee Peng Lim
Tweet Geolocation: Leveraging Location, User And Peer Signals, Wen-Haw Chong, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Which venue is a tweet posted from? We referred this as fine-grained geolocation. To solve this problem effectively, we develop novel techniques to exploit each posting user's content history. This is motivated by our finding that most users do not share their visitation history, but have ample content history from tweet posts. We formulate fine-grained geolocation as a ranking problem whereby given a test tweet, we rank candidate venues. We propose several models that leverage on three types of signals from locations, users and peers. Firstly, the location signals are words that are indicative of venues. We propose a location-indicative …
Interactive Social Recommendation, Xin Wang, Steven C. H. Hoi, Chenghao Liu, Martin Ester
Interactive Social Recommendation, Xin Wang, Steven C. H. Hoi, Chenghao Liu, Martin Ester
Research Collection School Of Computing and Information Systems
Social recommendation has been an active research topic over the last decade, based on the assumption that social information from friendship networks is beneficial for improving recommendation accuracy, especially when dealing with cold-start users who lack sufficient past behavior information for accurate recommendation. However, it is nontrivial to use such information, since some of a person's friends may share similar preferences in certain aspects, but others may be totally irrelevant for recommendations. Thus one challenge is to explore and exploit the extend to which a user trusts his/her friends when utilizing social information to improve recommendations. On the other hand, …
Unsupervised Topic Hypergraph Hashing For Efficient Mobile Image Retrieval, Lei Zhu, Jialie Shen, Liang Xie, Zhiyong Cheng
Unsupervised Topic Hypergraph Hashing For Efficient Mobile Image Retrieval, Lei Zhu, Jialie Shen, Liang Xie, Zhiyong Cheng
Research Collection School Of Computing and Information Systems
Hashing compresses high-dimensional features into compact binary codes. It is one of the promising techniques to support efficient mobile image retrieval, due to its low data transmission cost and fast retrieval response. However, most of existing hashing strategies simply rely on low-level features. Thus, they may generate hashing codes with limited discriminative capability. Moreover, many of them fail to exploit complex and high-order semantic correlations that inherently exist among images. Motivated by these observations, we propose a novel unsupervised hashing scheme, called topic hypergraph hashing (THH), to address the limitations. THH effectively mitigates the semantic shortage of hashing codes by …
Selective Value Coupling Learning For Detecting Outliers In High-Dimensional Categorical Data, Guansong Pang, Hongzuo Xu, Cao Longbing, Wentao Zhao
Selective Value Coupling Learning For Detecting Outliers In High-Dimensional Categorical Data, Guansong Pang, Hongzuo Xu, Cao Longbing, Wentao Zhao
Research Collection School Of Computing and Information Systems
This paper introduces a novel framework, namely SelectVC and its instance POP, for learning selective value couplings (i.e., interactions between the full value set and a set of outlying values) to identify outliers in high-dimensional categorical data. Existing outlier detection methods work on a full data space or feature subspaces that are identified independently from subsequent outlier scoring. As a result, they are significantly challenged by overwhelming irrelevant features in high-dimensional data due to the noise brought by the irrelevant features and its huge search space. In contrast, SelectVC works on a clean and condensed data space spanned by selective …
Sourcevote: Fusing Multi-Valued Data Via Inter-Source Agreements, Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Mahmoud Barhamgi, Lina Yao, Anne H.H. Ngu
Sourcevote: Fusing Multi-Valued Data Via Inter-Source Agreements, Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Mahmoud Barhamgi, Lina Yao, Anne H.H. Ngu
Research Collection School Of Computing and Information Systems
Data fusion is a fundamental research problem of identifyingtrue values of data items of interest from conflicting multi-sourceddata. Although considerable research efforts have been conducted on thistopic, existing approaches generally assume every data item has exactlyone true value, which fails to reflect the real world where data items withmultiple true values widely exist. In this paper, we propose a novel approach,SourceVote, to estimate value veracity for multi-valued data items.SourceVote models the endorsement relations among sources by quantifyingtheir two-sided inter-source agreements. In particular, two graphs areconstructed to model inter-source relations. Then two aspects of sourcereliability are derived from these graphs and …
A Fast Trajectory Outlier Detection Approach Via Driving Behavior Modeling, Hao Wu, Weiwei Sun, Baihua Zheng
A Fast Trajectory Outlier Detection Approach Via Driving Behavior Modeling, Hao Wu, Weiwei Sun, Baihua Zheng
Research Collection School Of Computing and Information Systems
Trajectory outlier detection is a fundamental building block for many location-based service (LBS) applications, with a large application base. We dedicate this paper on detecting the outliers from vehicle trajectories efficiently and effectively. In addition, we want our solution to be able to issue an alarm early when an outlier trajectory is only partially observed (i.e., the trajectory has not yet reached the destination). Most existing works study the problem on general Euclidean trajectories and require accesses to the historical trajectory database or computations on the distance metric that are very expensive. Furthermore, few of existing works consider some specific …
Self Service Business Intelligence: An Analysis Of Tourists Preferences In Kosovo, Ardian Hyseni
Self Service Business Intelligence: An Analysis Of Tourists Preferences In Kosovo, Ardian Hyseni
UBT International Conference
The purpose of this paper is to analyze the preferences of tourists in Kosovo through the data from TripAdvisor.com. Top things to do in Kosovo, will be analyzed through the comments of tourists in TripAdvisor.com. By analyzing the data with PowerBI, will be analyzed what are the most preferred things to do and what the tourists like the most in Kosovo. This paper will contribute on defining the preferences of tourists in Kosovo, it also can help tourism to invest and attract more tourists in specific areas or improve and invest in places less preferred by tourists.
Security Assessment Of Web Applications, Renelada Kushe
Security Assessment Of Web Applications, Renelada Kushe
UBT International Conference
A web application is an application that is accessed by users over a network such as the internet or intranet. The term also refers an application that is coded in a browser-supported programming language and reliant on a common web browser to render the application executable. Web applications are vulnerable to varies exploits from those which manipulate the application via its graphical web interface (HTTP exploits), to tampering the Uniform Resource Identifier (URI) or tampering HTTPS elements not contained in the URI. Getting started from the accessibility and the variety of exploits, the security assessment is a necessity for providing …
Web Scrapping And Self Service Business Intelligence: Analysis Of Preferences Of Tourists In Albania, Ardian Hyseni
Web Scrapping And Self Service Business Intelligence: Analysis Of Preferences Of Tourists In Albania, Ardian Hyseni
UBT International Conference
The purpose of this paper is to analyze the preferences of tourists in Albania through the data web scrapped from TripAdvisor.com. Top things to do in Albania, will be analyzed through the comments of tourists in TripAdvisor.com. By using tools for web scrapping and analyzing of data with nVivo and PowerBI, will be analyzed what are the most preferred things to do and what the tourists like doing the most in Albania. This paper will contribute on defining the preferences of tourists in Albania, also can help tourism to invest and attract more tourists in specific areas or improve and …
Implications Of Eu-Gdpr In Low-Grade Social, Activist And Ngo Settings, Lars Magnusson, Sarfraz Iqbal
Implications Of Eu-Gdpr In Low-Grade Social, Activist And Ngo Settings, Lars Magnusson, Sarfraz Iqbal
UBT International Conference
Social support services are becoming popular among the citizens of every country and every age. Though, social support services easily accessible on mobile phones are used in different contexts, ranging from extending your presence and connectivity to friends, family and colleagues to using social media services for being a social activist seeking to help individuals confined in miserable situations such as homeless community, drug addicts or even revolutionists fighting against dictatorships etc. However, a very recent development in the European Parliament’s law (2016/679) on the processing and free movement of personal data in terms of EU-GDPR (General data protection rules) …
E-Commerce Implementation In Kosovo, Besnik Skenderi, Diamanta Skenderi
E-Commerce Implementation In Kosovo, Besnik Skenderi, Diamanta Skenderi
UBT International Conference
In this paper, author had analyzed journal articles that were published by Alemayehu & Heeks, (2007) and Hwang, Jung, & Selvendy (2006). Both articles are about e-commerce and in first article (Alemayehu & Heeks, 2007) authors had analyzed impact of cultural differences, telecomunication infrastructure and local market. In addition, authors of this research paper were focused on consumers that are purchasing through e-commerce companies.
Second analyzed article (Hwang, Jung, & Selvendy, 2006) is about exploring e-commerce benefits in developing countries and developing countries are home to more than 80% of the world’s population, and are the site for growing use …
Learning Management Systems In Higher Education, Romina Agaçi
Learning Management Systems In Higher Education, Romina Agaçi
UBT International Conference
Learning Management Systems (LMSs) are improving learning processes and are widely used in higher education institutions. There are available various types of LMSs used by pedagogues to manage eLearning and to deliver course materials to students. Nowadays, LMSs have become essential tools that affect the quality of learning and teaching in higher education. In this article, we introduce LMSs and we choose Moodle as a tool to presentaninformation system that is used in our university. Moodle is an online learning environment that supports classroom teaching. We will focus on the advantages of LMSs and why we choose Moodle as the …
An Approach To Information Security For Smes Based On The Resource-Based View Theory, Blerton Abazi
An Approach To Information Security For Smes Based On The Resource-Based View Theory, Blerton Abazi
UBT International Conference
The main focus of this proposal is to analyze implementation challenges, benefits and requirements in implementation of Information Systems and managing information security in small and medium size companies in Western Balkans countries. In relation to the study, the proposal will focus in the following questions to investigate: What are the benefits that companies mostly find after the implementation of Information Systems has been implemented, efficiency, how to they manage security of the information’s, competitive advantage, return of investments etc. The study should give a clear approach to Information Systems implementation, information security, maintenance, measurable benefits, challenges companies have gone …
Towards Secure Data Flow Oriented Multi-Vendor Ict Governance Model, Lars Magnusson, Patrik Elm, Anita Mirijamdotter
Towards Secure Data Flow Oriented Multi-Vendor Ict Governance Model, Lars Magnusson, Patrik Elm, Anita Mirijamdotter
UBT International Conference
Today, still, ICT Governance is being regarded as a departmental concern, not an overall organizational concern. History has shown us that implementation strategies, which are based on departments, results in fractional implementations leading to ad hoc solutions with no central control and stagnation for the in-house ICT strategy. Further, this recently has created an opinion trend; many are talking about the ICT department as being redundant, a dying out breed, which should be replaced by on-demand specialized external services. Clearly, the evermore changing surroundings do force organizations to accelerate the pace of new adaptations within their ICT plans, more vivacious …
Healthcare It In Skilled Nursing And Post-Acute Care Facilities: Reducing Hospital Admissions And Re-Admissions, Improving Reimbursement And Improving Clinical Operations, Scott L. Hopes
USF Tampa Graduate Theses and Dissertations
Health information technology (HIT), which includes electronic health record (EHR) systems and clinical data analytics, has become a major component of all health care delivery and care management. The adoption of HIT by physicians, hospitals, post-acute care organizations, pharmacies and other health care providers has been accepted as a necessary (and recently, a government required) step toward improved quality, care coordination and reduced costs: “Better coordination of care provides a path to improving communication, improving quality of care, and reducing unnecessary emergency room use and hospital readmissions. LTPAC providers play a critical role in achieving these goals” (HealthIT.gov, 2013).
Though …
Modeling Habitat Suitability Of Invasive Carps In The Upper Missisisippi River System, Charlotte Alexander, Robert F. Allen, Kevin J. Aagard
Modeling Habitat Suitability Of Invasive Carps In The Upper Missisisippi River System, Charlotte Alexander, Robert F. Allen, Kevin J. Aagard
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
A Conversation Centric Approach To Understanding And Supporting The Coordination Of Social Group-Activities, Richard P. Schuler
A Conversation Centric Approach To Understanding And Supporting The Coordination Of Social Group-Activities, Richard P. Schuler
Dissertations
Despite the widespread and large variety of communication tools available to us such as, text messaging, Skype, email, twitter, Facebook, instant messaging, GroupMe, WhatsApp, Snapchat, etc., many people still routinely find coordinating activities with our friends to be a very frustrating experience. Everyone, has at least once, encountered the difficulties involved with deciding what to do as a group. Some friends may be busy, others may have already seen the movie that the others want to see, and some do not like Mexican food. It is a challenge everyone has faced and continue to face. This is a result of …
Cross-Modal Recipe Retrieval With Rich Food Attributes, Jingjing Chen, Chong-Wah Ngo, Tat-Seng Chua
Cross-Modal Recipe Retrieval With Rich Food Attributes, Jingjing Chen, Chong-Wah Ngo, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Food is rich of visible (e.g., colour, shape) and procedural (e.g., cutting, cooking) attributes. Proper leveraging of these attributes, particularly the interplay among ingredients, cutting and cooking methods, for health-related applications has not been previously explored. This paper investigates cross-modal retrieval of recipes, specifically to retrieve a text-based recipe given a food picture as query. As similar ingredient composition can end up with wildly different dishes depending on the cooking and cutting procedures, the difficulty of retrieval originates from fine-grained recognition of rich attributes from pictures. With a multi-task deep learning model, this paper provides insights on the feasibility of …
Visual Sentiment Analysis For Review Images With Item-Oriented And User-Oriented Cnn, Quoc Tuan Truong, Hady W. Lauw
Visual Sentiment Analysis For Review Images With Item-Oriented And User-Oriented Cnn, Quoc Tuan Truong, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Online reviews are prevalent. When recounting their experience with a product, service, or venue, in addition to textual narration, a reviewer frequently includes images as photographic record. While textual sentiment analysis has been widely studied, in this paper we are interested in visual sentiment analysis to infer whether a given image included as part of a review expresses the overall positive or negative sentiment of that review. Visual sentiment analysis can be formulated as image classification using deep learning methods such as Convolutional Neural Networks or CNN. However, we observe that the sentiment captured within an image may be affected …
Delving Into Salient Object Subitizing And Detection, Shengfeng He, Jianbo Jiao, Xiaodan Zhang, Guoqiang Han, Rynson W.H Lau
Delving Into Salient Object Subitizing And Detection, Shengfeng He, Jianbo Jiao, Xiaodan Zhang, Guoqiang Han, Rynson W.H Lau
Research Collection School Of Computing and Information Systems
Subitizing (i.e., instant judgement on the number) and detection of salient objects are human inborn abilities. These two tasks influence each other in the human visual system. In this paper, we delve into the complementarity of these two tasks. We propose a multi-task deep neural network with weight prediction for salient object detection, where the parameters of an adaptive weight layer are dynamically determined by an auxiliary subitizing network. The numerical representation of salient objects is therefore embedded into the spatial representation. The proposed joint network can be trained end-to-end using backpropagation. Experiments show the proposed multi-task network outperforms existing …
Tensor Factorization For Low-Rank Tensor Completion, Pan Zhou, Canyi Lu, Zhouchen Lin, Chao Zhang
Tensor Factorization For Low-Rank Tensor Completion, Pan Zhou, Canyi Lu, Zhouchen Lin, Chao Zhang
Research Collection School Of Computing and Information Systems
Recently, a tensor nuclear norm (TNN) based method [1] was proposed to solve the tensor completion problem, which has achieved state-of-the-art performance on image and video inpainting tasks. However, it requires computing tensor singular value decomposition (t-SVD), which costs much computation and thus cannot efficiently handle tensor data, due to its natural large scale. Motivated by TNN, we propose a novel low-rank tensor factorization method for efficiently solving the 3-way tensor completion problem. Our method preserves the lowrank structure of a tensor by factorizing it into the product of two tensors of smaller sizes. In the optimization process, our method …
Interactive Visual Analytics Application For Spatiotemporal Movement Data Vast Challenge 2017 Mini-Challenge 1: Award For Actionable And Detailed Analysis, Yifei Guan, Tin Seong Kam
Interactive Visual Analytics Application For Spatiotemporal Movement Data Vast Challenge 2017 Mini-Challenge 1: Award For Actionable And Detailed Analysis, Yifei Guan, Tin Seong Kam
Research Collection School Of Computing and Information Systems
The Visual Analytics Science and Technology (VAST) Challenge 2017 Mini-Challenge 1 dataset mirrored the challenging scenarios in analysing large spatiotemporal movement tracking datasets. The datasets provided contains a 13-month movement data generated by five types of sensors, for six types of vehicles passing through the Boonsong Lekagul Nature Preserve. We present an application developed with the market leading visualisation software Tableau to provide an interactive visual analysis of the multi-dimensional spatiotemporal datasets. Our interactive application allows the user to perform an interactive analysis to observe movement patterns, study vehicle trajectories and identify movement anomalies while allowing them to customise the …
Tagscan: Simultaneous Target Imaging And Material Identification With Commodity Rfid Devices, Ju Wang, Jie Xiong, Xiaojiang Chen, Hongbo Jiang, Rajesh Krishna Balan, Dingyi Fang
Tagscan: Simultaneous Target Imaging And Material Identification With Commodity Rfid Devices, Ju Wang, Jie Xiong, Xiaojiang Chen, Hongbo Jiang, Rajesh Krishna Balan, Dingyi Fang
Research Collection School Of Computing and Information Systems
Target imaging and material identification play an important role in many real-life applications. This paper introduces TagScan, a system that can identify the material type and image the horizontal cut of a target simultaneously with cheap commercial of-the-shelf (COTS) RFID devices. The key intuition is that different materials and target sizes cause different amounts of phase and RSS (Received Signal Strength) changes when radio frequency (RF) signal penetrates through the target. Multiple challenges need to be addressed before we can turn the idea into a functional system including (i) indoor environments exhibit rich multipath which breaks the linear relationship between …
Vungle Inc. Improves Monetization Using Big-Data Analytics, Bert De Reyck, Ioannis Fragkos, Yael Gruksha-Cockayne, Casey Lichtendahl, Hammond Guerin, Andre Kritzer
Vungle Inc. Improves Monetization Using Big-Data Analytics, Bert De Reyck, Ioannis Fragkos, Yael Gruksha-Cockayne, Casey Lichtendahl, Hammond Guerin, Andre Kritzer
Research Collection Lee Kong Chian School Of Business
The advent of big data has created opportunities for firms to customize their products and services to unprecedented levels of granularity. Using big data to personalize an offering in real time, however, remains a major challenge. In the mobile advertising industry, once a customer enters the network, an ad-serving decision must be made in a matter of milliseconds. In this work, we describe the design and implementation of an ad-serving algorithm that incorporates machine-learning methods to make personalized ad-serving decisions within milliseconds. We developed this algorithm for Vungle Inc., one of the largest global mobile ad networks. Our approach also …
Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li
Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li
Research Collection School Of Computing and Information Systems
Path authentication thwarts counterfeits in RFID-based supply chains. Its motivation is that tagged products taking invalid paths are likely faked and injected by adversaries at certain supply chain partners/steps. Existing solutions are path-grained in that they simply regard a product as genuine if it takes any valid path. Furthermore, they enforce distributed authentication by offloading the sets of valid paths to some or all steps from a centralized issuer. This not only imposes network and storage overhead but also leaks transaction privacy. We present StepAuth, the first step-grained path authentication protocol that is practically efficient for authenticating products with strict …