Computer Sciences Commons^™

Online Multi-Task Collaborative Filtering For On-The-Fly Recommender Systems, Jialei Wang, Steven C. H. Hoi, Peilin Zhao, Zhi-Yong Liu

Research Collection School Of Computing and Information Systems

Traditional batch model-based Collaborative Filtering (CF) approaches typically assume a collection of users' rating data is given a priori for training the model. They suffer from a common yet critical drawback, i.e., the model has to be re-trained completely from scratch whenever new training data arrives, which is clearly non-scalable for large real recommender systems where users' rating data often arrives sequentially and frequently. In this paper, we investigate a novel efficient and scalable online collaborative filtering technique for on-the-fly recommender systems, which is able to effectively online update the recommendation model from a sequence of rating observations. Specifically, we …

The Myths Of G-Tech For Business Decision Making, Tin Seong Kam

Research Collection School Of Computing and Information Systems

More than 80% of organisation data are location related - the locations where transactions are done, where retailers are found, and of customers who buy their products. Since the early 2005, there has been an increasing interest among the business community to use geospatial technology to enhance decision making process at both strategic and operational levels. Millions of dollars and man-hours have been invested into driving their geo-technology development and implementation. The use of geospatial technology in business, however, tends to confine to simple mapping. Many of these failures are the victims of misperception. Some of the perpetrators are practitioners. …

Riga: A Rich Internet Geospatial Analytics Application For Area-Based Data, Tin Seong Kam

Research Collection School Of Computing and Information Systems

In this information age, more and more public statistical data such as population census, household living, local economy and business establishment are distributed over the internet within the framework of spatial data infrastructure. By and large, these data are organized geographically such as region, province as well as district. Usually, they are published in the form of digital maps over the internet as simple points, lines and polygons markers limited or no analytical function available to transform these data into useful information. To meet the analytical needs of casual public data users, we contribute RIGA, a rich internet geospatial analytics …

Making Sense Of Trends And Data, Singapore Management University

Perspectives@SMU

How do you make sense of data when it is all unpredictable?

A Statistical And Schema Independent Approach To Identify Equivalent Properties On Linked Data, Kalpa Gunaratna, Krishnaprasad Thirunarayan, Prateek Jain, Amit P. Sheth, Sanjaya Wijeratne

Kno.e.sis Publications

Linked Open Data (LOD) cloud has gained significant attention in the Semantic Web community recently. Currently it consists of approximately 295 interlinked datasets with over 50 billion triples including 500 million links, and continues to expand in size. This vast source of structured information has the potential to have a significant impact on knowledge-based applications. However, a key impediment to the use of LOD cloud is limited support for data integration tasks over concepts, instances, and properties. Efforts to address this limitation over properties have focused on matching data-type properties across datasets; however, matching of object-type properties has not received …

A Robust Rgbd Slam System For 3d Environment With Planar Surfaces, Po-Chang Su, Ju Shen, Sen-Ching S. Cheung

Computer Science Faculty Publications

With the increasing popularity of RGB-depth (RGB-D) sensors such as the Microsoft Kinect, there have been much research on capturing and reconstructing 3D environments using a movable RGB-D sensor. The key process behind these kinds of simultaneous location and mapping (SLAM) systems is the iterative closest point or ICP algorithm, which is an iterative algorithm that can estimate the rigid movement of the camera based on the captured 3D point clouds. While ICP is a well-studied algorithm, it is problematic when it is used in scanning large planar regions such as wall surfaces in a room. The lack of depth …

Mining Effective Multi-Segment Sliding Window For Pathogen Incidence Rate Prediction, Lei Duan, Changjie Tang, Xiasong Li, Guozhu Dong, Xianming Wang, Jie Zuo, Min Jiang, Zhongqi Li, Yongqing Zhang

Kno.e.sis Publications

Pathogen incidence rate prediction, which can be considered as time series modeling, is an important task for infectious disease incidence rate prediction and for public health. This paper investigates the application of a genetic computation technique, namely GEP, for pathogen incidence rate prediction. To overcome the shortcomings of traditional sliding windows in GEP-based time series modeling, the paper introduces the problem of mining effective sliding window, for discovering optimal sliding windows for building accurate prediction models. To utilize the periodical characteristic of pathogen incidence rates, a multi-segment sliding window consisting of several segments from different periodical intervals is proposed and …

Types Of Property Pairs And Alignment On Linked Datasets - A Preliminary Analysis, Kalpa Gunaratna, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

Dataset publication on the Web has been greatly influenced by the Linked Open Data (LOD) project. Many interlinked datasets have become freely available on the Web creating a structured and distributed knowledge representation. Analysis and aligning of concepts and instances in these interconnected datasets have received a lot of attention in the recent past compared to properties. We identify three different categories of property pairs found in the alignment process and study their relative distribution among well known LOD datasets. We also provide comparative analysis of state-of-the-art techniques with regard to different categories, highlighting their capabilities. This could lead to …

Web-Scale Near-Duplicate Search: Techniques And Applications, Chong-Wah Ngo, Changsheng Xu, Wessel Kraaij, Abdulmotaleb El Saddik

Research Collection School Of Computing and Information Systems

This paper presents some of the most recent advances in the research on Web-scale near-duplicate search and explores the potential for bringing this research a substantial step further. It contains high-quality contributions addressing various aspects of the Web-scale near-duplicate search problem in a number of relevant domains. The topics range from feature representation, matching, and indexing from different novel aspects to the adaptation of current technologies for mobile media search and photo archaeology mining.

Generative Models For Item Adoptions Using Social Correlation, Freddy Chong Tat Chua, Hady Wirawan Lauw, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Users face many choices on the Web when it comes to choosing which product to buy, which video to watch, etc. In making adoption decisions, users rely not only on their own preferences, but also on friends. We call the latter social correlation which may be caused by the homophily and social influence effects. In this paper, we focus on modeling social correlation on users’ item adoptions. Given a user-user social graph and an item-user adoption graph, our research seeks to answer the following questions: whether the items adopted by a user correlate to items adopted by her friends, and …

The Impact Of Ineffective Internal Control On The Value Relevance Of Accounting Information, Nan Hu, Baolei Qi, Gaoliang Tian, Lee Yao, Zhen Zeng

Research Collection School Of Computing and Information Systems

This paper investigates the value relevance of accounting information in the presence of ineffective internal control (IIC). Based on Ohlson's valuation model, this paper first documents that IIC can directly affect a firm's market value after control cost of capital, corporate governance, and other, value-relevant variables. Second, this paper finds that the value relevance of earnings and book value in determining a firm's market value are significantly reduced. Collectively, the results of this paper indicate that the effectiveness of internal controls can directly affect a firm's market value and the value relevance of accounting information.

A Study On The Application Of Information System In Patrol Vessel Management, Lei Li

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Research On The Establishment Of Promulgation System Of Maritime Safety Information In Chengshan Jiao Vts Center, Yunjiang Liu

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Building An Access Database For Cookstove Research, Margaret L. Weddle

Student Works

This paper takes the reader through the thought process and actual instructions to create your own Microsoft Access database, or how to use the one provided with this paper. Also, instructions to use the HBLL resources of Compendex and RefWorks are covered. While this work was built specifically for Cookstoves research, it could be adapted to any research where you would need to maintain a record of the journal articles that you are using. It has been discovered that building a database is a time consuming and difficult work, but once done, Access provides an easy way to work with …

Development Of A Jobs Database For Tracking Knowledge And Skills Expectations In The Workplace, Esa M. Rantanen, Christopher Claeys, Daniel Roder

Articles

The primary objective of college education in applied disciplines is that it is relevant to the expectations for new professionals entering the labor market. Academic institutions should therefore pay close attention to the ever-changing skills and knowledge expectations in the labor market. These trends are not easy to track, however. Surveys of new professionals about their experiences in their first jobs or surveys of employers about their experiences with new hires suffer from low response rates, nonresponse bias, and the one-time nature of survey research. A better way to track labor market trends is to continually analyze human factors job …

Multi-View Discriminant Transfer Learning, Pei Yang Yang, Wei Gao

Research Collection School Of Computing and Information Systems

We study to incorporate multiple views of data in a perceptive transfer learning framework and propose a Multi-view Discriminant Transfer (MDT) learning approach for domain adaptation. The main idea is to find the optimal discriminant weight vectors for each view such that the correlation between the two-view projected data is maximized, while both the domain discrepancy and the view disagreement are minimized simultaneously. Furthermore, we analyze MDT theoretically from discriminant analysis perspective to explain the condition and reason, under which the proposed method is not applicable. The analytical results allow us to investigate whether there exist within-view and/or betweenview conflicts, …

An Empirical Study On Uncertainty Identification In Social Media Context, Zhongyu Wei, Junwen Chen, Wei Gao, Binyang Li, Lanjun Zhou, Yulan He, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Uncertainty text detection is important to many social-media-based applications since more and more users utilize social media platforms (e.g., Twitter, Facebook, etc.) as information source to produce or derive interpretations based on them. However, existing uncertainty cues are ineffective in social media context because of its specific characteristics. In this paper, we propose a variant of annotation scheme for uncertainty identification and construct the first uncertainty corpus based on tweets. We then conduct experiments on the generated tweets corpus to study the effectiveness of different types of features for uncertainty text identification.

Semantic Assistance For Data Utilization And Curation, Brian J. Becker

LSU New Orleans Theses and Dissertations

We propose that most data stores for large organizations are ill-designed for the future, due to limited searchability of the databases. The study of the Semantic Web has been an emerging technology since first proposed by Berners-Lee. New vocabularies have emerged, such as FOAF, Dublin Core, and PROV-O ontologies. These vocabularies, combined, can relate people, places, things, and events. Technologies developed for the Semantic Web, namely the standardized vocabularies for expressing metadata, will make data easier to utilize. We gathered use cases for various data sources, from human resources to big enterprise. Most of our use cases reflect real-world data. …

Reaper – Toward Automating Mobile Cloud Communication, Daniel R. Ward

LSU New Orleans Theses and Dissertations

Mobile devices connected to cloud based services are becoming a mainstream method of delivery up-to-date and context aware information to users. Connecting mobile applications to cloud service require significant developer effort. Yet this communication code usually follows certain patterns, varying accordingly to the specific type of data sent and received from the server. By analyzing the causes of theses variations, we can create a system that can automate the code creation for communication from a mobile device to a cloud server. To automate code creation, a general pattern must extracted. This general solution can then be applied to any database …

Oyster Sustainability Modeling As A Public Resource, Nathan A. Cooper

LSU New Orleans Theses and Dissertations

A simulation algorithm based on biological references points proposed by Powell and Klink (2007) is implemented for predicting the total allowable catch of eastern oysters (Crassostrea virginica) from Louisiana’s coast. The model accepts initial per-square-meter shell mass and oyster size distributions as input. Fishing effort is provided as fractions removed of each resource for each month of the season. The model outputs the expected remaining shell mass and harvests of sack and seed oysters after discrete fishing months. Oyster mortality credits the shell budget, while fishing fractions debit oyster and shell resources. Surviving oysters grow larger along a …

Forensic Analysis Of Whatsapp On Android Smartphones, Neha S. Thakur

LSU New Orleans Theses and Dissertations

Android forensics has evolved over time offering significant opportunities and exciting challenges. On one hand, being an open source platform Android is giving developers the freedom to contribute to the rapid growth of the Android market whereas on the other hand Android users may not be aware of the security and privacy implications of installing these applications on their phones. Users may assume that a password-locked device protects their personal information, but applications may retain private information on devices, in ways that users might not anticipate. In this thesis we will be concentrating on one such application called 'WhatsApp', a …

Flitecam Data Process Validation, Jesse K. Tsai, Sachindev S. Shenoy, Brent Cedric Nicklas, Zaheer Ali, William T. Reach

STAR Program Research Presentations

FLITECAM Data Processing Validation

Many of the challenges that come from working with astronomical imaging arise from the reduction of raw data into scientifically meaningful data. First Light Infrared Test CAMera (FLITECAM) is an infrared camera operating in the 1.0–5.5 μm waveband on board SOFIA (Stratospheric Observatory For Infrared Astronomy). Due to the significant noise from the atmosphere and the camera itself, astronomers have developed many methods to reduce the effects of atmospheric and instrumental emission. The FLITECAM Data Reduction Program (FDRP) is a program, developed at SOFIA Science Center, subtracts darks, removes flats, and dithers images.

This project contains …

Has Safeer Improved Sacm's Work And Helped Saudi Students In The Usa Resolve Their Needs Quickly, Faisal M. Alzomily

Masters Theses & Specialist Projects

This study examined efficiency of the Safeer by gathering and analyzing the perception of 131 Saudi students from Bowling Green, KY. The purpose of the study was to ensure that the system is able to perform its function as the bridge between different institutions and Saudi students studying in the US who require assistance in processing their academic requirements. A self-administered survey using five scale points was employed. Results were summarized using descriptive statistics at 95% confidence level. The result confirmed the hypothesis that the use of the Safeer program provides quality service delivery within SACM, which in turn benefits …

Introduction To Gis Using Open Source Software, 4th Ed, Frank Donnelly

Open Educational Resources

This tutorial was created to accompany the GIS Practicum, a day-long workshop offered by the Newman Library at Baruch College CUNY that introduces participants to geographic information systems (GIS) using the open source software QGIS. The practicum introduces GIS as a concept for envisioning information and as a tool for conducting geographic analyses and creating maps. Participants learn how to navigate a GIS interface, how to prepare layers and conduct a basic geographic analysis, and how to create thematic maps. This tutorial was written using QGIS version 1.8 "Lisboa", a cross-platform (Windows, Mac, Linux) desktop GIS software package.

On Fuzzy Soft Matrix Based On Reference Function, Florentin Smarandache, Said Broumi, Mamoni Dhar

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we study fuzzy soft matrix based on reference function. Firstly, we define some new operations such as fuzzy soft complement matrix and trace of fuzzy soft matrix based on reference function. Then, we introduced some related properties, and some examples are given. Lastly, we define a new fuzzy soft matrix decision method based on reference function.

Segmenting Tables Via Indexing Of Value Cells By Table Headers, Sharad C. Seth, George Nagy

School of Computing: Conference and Workshop Papers

Correct segmentation of a web table into its component regions is the essential first step to understanding tabular data. Our algorithmic solution to the segmentation problem relies on the property that strings defining row and column header paths uniquely index each data cell in the table. We segment the table using only “logical layout analysis” without resorting to any appearance features or natural language understanding. We start with a CSV table that preserves the 2- dimensional structure and contents of the original source table (e.g., an HTML table) but not font size, font weight, and color. The indexing property of …

Vigilance Adaptation In Adaptive Resonance Theory, Lei Meng, Ah-Hwee Tan, Donald C. Winsch

Research Collection School Of Computing and Information Systems

Despite the advantages of fast and stable learning, Adaptive Resonance Theory (ART) still relies on an empirically fixed vigilance parameter value to determine the vigilance regions of all of the clusters in the category field (F 2 ), causing its performance to depend on the vigilance value. It would be desirable to use different values of vigilance for different category field nodes, in order to fit the data with a smaller number of categories. We therefore introduce two methods, the Activation Maximization Rule (AMR) and the Confliction Minimization Rule (CMR). Despite their differences, both ART with AMR (AM-ART) and with …

Self-Organizing Cognitive Models For Virtual Agents, Yilin Kang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Three key requirements of realistic characters or agents in virtual world can be identified as autonomy, interactivity, and personification. Working towards these challenges, this paper proposes a brain inspired agent architecture that integrates goal-directed autonomy, natural language interaction and human-like personification. Based on self-organizing neural models, the agent architecture maintains explicit mental representation of desires, intention, personalities, self-awareness, situation awareness and user awareness. Autonomous behaviors are generated via evaluating the current situation with active goals and learning the most appropriate social or goal-directed rule from the available knowledge, in accordance with the personality of each individual agent. We have built …

Delayflow Centrality For Identifying Critical Nodes In Transportation Networks, Yew-Yih Cheng, Roy Ka Wei Lee, Ee-Peng Lim, Feida Zhu

Research Collection School Of Computing and Information Systems

In an urban city, its transportation network supports efficient flow of people between different parts of the city. Failures in the network can cause major disruptions to commuter and business activities which can result in both significant economic and time losses. In this paper, we investigate the use of centrality measures to determine critical nodes in a transportation network so as to improve the design of the network as well as to devise plans for coping with network failures. Most centrality measures in social network analysis research unfortunately consider only topological structure of the network and are oblivious of transportation …

An Empirical Analysis Of A Network Of Expertise, Le Truc Viet, Minh Thap Nguyen

Research Collection School Of Computing and Information Systems

In this paper, we analyze the network of expertise constructed from the interactions of users on the online questionanswering (QA) community of Stack Overflow. This community was built with the intention of helping users with their programming tasks and, thus, questions are expected to be highly factual. This also indicates that the answers one provides may be highly indicative of one's level of expertise on the subject matter. Therefore, our main concern is how to model and characterize the user's expertise based on the constructed network and its centrality measures. We used the user's reputation established on Stack Overflow as …