Understanding The Information-Based Transformation Of Strategy And Society,
2017
University of Pennsylvania
Understanding The Information-Based Transformation Of Strategy And Society, Eric K. Clemons, Rajiv M. Dewan, Robert J. Kauffman, Thomas A. Weber
Research Collection School Of Computing and Information Systems
The world economy is undergoing dramatic changes, largely driven by the new availability of fine-grained information. Innovative ways of using data—large and small—have also prompted a rethinking of the boundaries for the combination and use of knowledge. The strategic design of information flows in the economy has the upside of higher economic rents and competitive advantage, as well as the downsides of wealth inequality and abuse of power. This has brought a wide range of regulatory challenges. To understand the nature of these sweeping changes, it is important to examine the new ways information is used, and how information flows …
Assessing The Language Of Chat For Teamwork Dialogue,
2017
Nanyang Technological University
Assessing The Language Of Chat For Teamwork Dialogue, Antonette Shibani, Elizabeth Koh, Vivian Lai, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
In technology enhanced language learning, many pedagogical activities involve students in online discussion such as synchronous chat, in order to help them practice their language skills. Besides developing the language competency of students, it is also crucial to nurture their teamwork competencies for today's global and complex environment. Language communication is an important glue of teamwork. In order to assess the language of chat for teamwork dimensions, several text mining methods are pos sible. However, difficulties arise such as pre-processing being a black box and classification approaches and algorithms being dependent on the context. To address these issues, the study …
Aspect Extraction From Product Reviews Using Category Hierarchy Information,
2017
Singapore Management University
Aspect Extraction From Product Reviews Using Category Hierarchy Information, Yifeng Yang, Chen Cen, Minghui Qiu, Forrest Sheng Bao
Research Collection School Of Computing and Information Systems
Aspect extraction is a task to abstract the common properties of objects from corpora discussing them, such as reviews of products. Recent work on aspect extraction is leveraging the hierarchical relationship between products and their categories. However, such effort focuses on the aspects of child categories but ignores those from parent categories. Hence, we propose an LDA-based generative topic model inducing the two-layer categorical information (CAT-LDA), to balance the aspects of both a parent category and its child categories. Our hypothesis is that child categories inherit aspects from parent categories, controlled by the hierarchy between them. Experimental results on 5 …
Viewability Prediction For Display Advertising,
2017
New Jersey Institute of Technology
Viewability Prediction For Display Advertising, Chong Wang
Dissertations
As a massive industry, display advertising delivers advertisers’ marketing messages to attract customers through graphic banners on webpages. Display advertising is also the most essential revenue source of online publishers. Currently, advertisers are charged by user response or ad serving. However, recent studies show that users barely click or convert display ads. Moreover, about half of the ads are actually never seen by users. In this case, advertisers cannot enhance their brand awareness and increase return on investment. Publishers also lose much revenue. Therefore, the ad pricing standards are shifting to a new model: ad impressions are paid if they …
Now You See It, Now You Don't! A Study Of Content Modification Behavior In Facebook,
2017
Singapore Management University
Now You See It, Now You Don't! A Study Of Content Modification Behavior In Facebook, Fuxiang Chen, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Social media, as a major platform to disseminate information, has changed the way users and communities contribute content. In this paper, we aim to study content modifications on public Facebook pages operated by news media, community groups, and bloggers. We also study the possible reasons behind them, and their effects on user interaction. We conducted a detailed study of Content Censorship (CC) and Content Edit (CE) in Facebook using a detailed longitudinal dataset consisting of 57 public Facebook pages over 3 weeks covering 145,955 posts and 9,379,200 comments. We detected many CC and CE activities between 28% and 56% of …
Machine Comprehension Using Match-Lstm And Answer Pointer,
2017
Singapore Management University
Machine Comprehension Using Match-Lstm And Answer Pointer, Shuohang Wang, Jing Jiang
Research Collection School Of Computing and Information Systems
Machine comprehension of text is an important problem in natural language processing. A recently released dataset, the Stanford Question Answering Dataset (SQuAD), offers a large number of real questions and their answers created by humans through crowdsourcing. SQuAD provides a challenging testbed for evaluating machine comprehension algorithms, partly because compared with previous datasets, in SQuAD the answers do not come from a small set of candidate answers and they have variable lengths. We propose an end-to-end neural architecture for the task. The architecture is based on match-LSTM, a model we proposed previously for textual entailment, and Pointer Net, a sequence-to-sequence …
Discovering Anomalous Events From Urban Informatics Data,
2017
Singapore Management University
Discovering Anomalous Events From Urban Informatics Data, Kasthuri Jayarajah, Vigneshwaran Subbaraju, Dulanga Kaveesha Weerakoon Mudiyanselage, Archan Misra, La Thanh Tam, Noel Athaide
Research Collection School Of Computing and Information Systems
Singapore's "smart city" agenda is driving the government to provide public access to a broader variety of urban informatics sources, such as images from traffic cameras and information about buses servicing different bus stops. Such informatics data serves as probes of evolving conditions at different spatiotemporal scales. This paper explores how such multi-modal informatics data can be used to establish the normal operating conditions at different city locations, and then apply appropriate outlier-based analysis techniques to identify anomalous events at these selected locations. We will introduce the overall architecture of sociophysical analytics, where such infrastructural data sources can be combined …
Neural Collaborative Filtering,
2017
Singapore Management University
Neural Collaborative Filtering, Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
In recent years, deep neural networks have yielded immense success on speech recognition, computer vision and natural language processing. However, the exploration of deep neural networks on recommender systems has received relatively less scrutiny. In this work, we strive to develop techniques based on neural networks to tackle the key problem in recommendation --- collaborative filtering --- on the basis of implicit feedback.Although some recent work has employed deep learning for recommendation, they primarily used it to model auxiliary information, such as textual descriptions of items and acoustic features of musics. When it comes to model the key factor in …
Achievement And Friends: Key Factors Of Player Retention Vary Across Player Levels In Online Multiplayer Games,
2017
Singapore Management University
Achievement And Friends: Key Factors Of Player Retention Vary Across Player Levels In Online Multiplayer Games, Korea Advanced Institute Of Science & Technology, Qatar Computing Research Institute, Haewoon Kwak
Research Collection School Of Computing and Information Systems
Retaining players over an extended period of time is a long-standing challenge in game industry. Significant effort has been paid to understanding what motivates players enjoy games. While individuals may have varying reasons to play or abandon a game at different stages within the game, previous studies have looked at the retention problem from a snapshot view. This study, by analyzing in-game logs of 51,104 distinct individuals in an online multiplayer game, uniquely offers a multifaceted view of the retention problem over the players' virtual life phases. We find that key indicators of longevity change with the game level. Achievement …
I Would Not Plant Apple Trees If The World Will Be Wiped: Analyzing Hundreds Of Millions Of Behavioral Records Of Players During An Mmorpg Beta Test,
2017
Singapore Management University
I Would Not Plant Apple Trees If The World Will Be Wiped: Analyzing Hundreds Of Millions Of Behavioral Records Of Players During An Mmorpg Beta Test, Qatar Computing Research Institute, The State University Of New York University At Buffalo, Haewoon Kwak, Korea University
Research Collection School Of Computing and Information Systems
In this work, we use player behavior during the closed beta test of the MMORPG ArcheAge as a proxy for an extreme situation: at the end of the closed beta test, all user data is deleted, and thus, the outcome (or penalty) of players' in-game behaviors in the last few days loses its meaning. We analyzed 270 million records of player behavior in the 4th closed beta test of ArcheAge. Our findings show that there are no apparent pandemic behavior changes, but some outlierswere more likely to exhibit anti-social behavior (e.g., player killing). We also found that contrary to the …
Harnessing Legal Complexity,
2017
Vanderbilt University Law School
Harnessing Legal Complexity, Daniel Katz, J. Ruhl, M Bommarito
All Faculty Scholarship
No abstract provided.
An Evidence-Based Review Of Academic Web Search Engines, 2014-2016: Implications For Librarians’ Practice And Research Agenda,
2017
James Madison University
An Evidence-Based Review Of Academic Web Search Engines, 2014-2016: Implications For Librarians’ Practice And Research Agenda, Jody C. Fagan
Libraries
Academic web search engines have become central to scholarly research. While the fitness of Google Scholar for research purposes has been examined repeatedly, Microsoft Academic and Google Books have not received much attention. Recent studies have much to tell us about the coverage and utility of Google Scholar, its coverage of the sciences, and its utility for evaluating researcher impact. But other aspects have been understudied, such as coverage of the arts and humanities, books, and non-Western, non-English publications. User research has also tapered off. A small number of articles hint at the opportunity for librarians to become expert advisors …
Ten Simple Rules For Responsible Big Data Research,
2017
University of Kentucky
Ten Simple Rules For Responsible Big Data Research, Matthew Zook, Solon Barocas, Danah Boyd, Kate Crawford, Emily Keller, Seeta Peña Gangadharan, Alyssa Goodman, Rachelle Hollander, Barbara A. Koenig, Jacob Metcalf, Arvind Narayanan, Alondra Nelson, Frank Pasquale
Geography Faculty Publications
No abstract provided.
Forging Blockchains: Spatial Production And Political Economy Of Decentralized Cryptocurrency Code/Spaces,
2017
University of South Florida
Forging Blockchains: Spatial Production And Political Economy Of Decentralized Cryptocurrency Code/Spaces, Joe Blankenship
USF Tampa Graduate Theses and Dissertations
Cryptocurrencies and blockchains are increasingly used, implemented and adapted for numerous purposes; people and businesses are integrating these technologies into their practices and strategies, creating new political economies and spaces in and of everyday life. This thesis seeks to develop a foundation of geographic theory for the study of spatial production within and surrounding blockchain technologies focusing on acute studies of Bitcoin as cryptocurrency, Ethereum as digital marketplace, and their conditions of possibility as decentralized autonomous organizations. Utilizing concepts from Henri Lefebvre's Production of Space, this thesis situates blockchain technologies within the wider discussion about the political economy of …
Iota Pi Application For Ios,
2017
California Polytechnic State University, San Luis Obispo
Iota Pi Application For Ios, Deborah Newberry
Computer Science and Software Engineering
Kappa Kappa Psi is a national honorary fraternity for college band members. They meet every Sunday night, and during these meetings they plan events (both internal and external) that aim to meet our goal of making sure that the Cal Poly band programs have their social, financial, material, and educational needs satisfied. This paper details the steps I took to create an application for them to use internally to help ease organizational processes.
Version-Sensitive Mobile App Recommendation,
2017
Xiamen University
Version-Sensitive Mobile App Recommendation, Da Cao, Liqiang Nie, Xiangnan He, Xiaochi Wei, Jialie Shen, Shunxiang Wu, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Being part and parcel of the daily life for billions of people all over the globe, the domain of mobile Applications (Apps) is the fastest growing sector of mobile market today. Users, however, are frequently overwhelmed by the vast number of released Apps and frequently updated versions. Towards this end, we propose a novel version-sensitive mobile App recommendation framework. It is able to recommend appropriate Apps to right users by jointly exploring the version progression and dual-heterogeneous data. It is helpful for alleviating the data sparsity problem caused by version division. As a byproduct, it can be utilized to solve …
Metric Similarity Joins Using Mapreduce,
2017
Zhejiang University
Metric Similarity Joins Using Mapreduce, Yunjun Gao, Keyu Yang, Lu Chen, Baihua Zheng, Gang Chen, Chun Chen
Research Collection School Of Computing and Information Systems
Given two object sets Q and O , a metric similarity join finds similar object pairs according to a certain criterion. This operation has a wide variety of applications in data cleaning, data mining, to name but a few. However, the rapidly growing volume of data nowadays challenges traditional metric similarity join methods, and thus, a distributed method is required. In this paper, we adopt a popular distributed framework, namely, MapReduce, to support scalable metric similarity joins. To ensure the load balancing, we present two sampling based partition methods. One utilizes the pivot and the space-filling curve mappings to cluster …
Probabilistic Public Key Encryption For Controlled Equijoin In Relational Databases,
2017
Singapore Management University
Probabilistic Public Key Encryption For Controlled Equijoin In Relational Databases, Yujue Wang, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
We present a public key encryption scheme for relational databases (PKDE) that allows the owner to control the execution of cross-relation joins on an outsourced server. The scheme allows anyone to deposit encrypted records in a database on the server. Thereafter, the database owner may authorize the server to join any two relations to identify matching records across them, while preventing self-joins that would reveal information on records that are unmatched in the join. The security of our construction is formally proved in the random oracle model based on the computational bilinear Diffie-Hellman assumption. Specifically, before a relation is joined, …
Social Tag Relevance Learning Via Ranking-Oriented Neighbor Voting,
2017
Shandong University of Finance and Economics
Social Tag Relevance Learning Via Ranking-Oriented Neighbor Voting, Chaoran Cui, Jialie Shen, Jun Ma, Tao Lian
Research Collection School Of Computing and Information Systems
High quality tags play a critical role in applications involving online multimedia search, such as social image annotation, sharing and browsing. However, user-generated tags in real world are often imprecise and incomplete to describe the image contents, which severely degrades the performance of current search systems. To improve the descriptive powers of social tags, a fundamental issue is tag relevance learning, which concerns how to interpret the relevance of a tag with respect to the contents of an image effectively. In this paper, we investigate the problem from a new perspective of learning to rank, and develop a novel approach …
Effective K-Vertex Connected Component Detection In Large-Scale Networks,
2017
Northeastern University
Effective K-Vertex Connected Component Detection In Large-Scale Networks, Yuan Li, Yuha Zhao, Guoren Wang, Feida Zhu, Yubao Wu, Shenglei Shi
Research Collection School Of Computing and Information Systems
Finding components with high connectivity is an important problem in component detection with a wide range of applications, e.g., social network analysis, web-page research and bioinformatics. In particular, k-edge connected component (k-ECC) has recently been extensively studied to discover disjoint components. Yet many real applications present needs and challenges for overlapping components. In this paper, we propose a k-vertex connected component (k-VCC) model, which is much more cohesive and therefore allows overlapping between components. To find k-VCCs, a top-down framework is first developed to find the exact k-VCCs. To further reduce the high computational cost for input networks of large …
