Partial Least Squares Regression On Grassmannian Manifold For Emotion Recognition,
2013
Singapore Management University
Partial Least Squares Regression On Grassmannian Manifold For Emotion Recognition, M. Liu, R. Wang, Zhiwu Huang, S. Shan, X. Chen
Research Collection School Of Computing and Information Systems
In this paper, we propose a method for video-based human emotion recognition. For each video clip, all frames are represented as an image set, which can be modeled as a linear subspace to be embedded in Grassmannian manifold. After feature extraction, Class-specific One-to-Rest Partial Least Squares (PLS) is learned on video and audio data respectively to distinguish each class from the other confusing ones. Finally, an optimal fusion of classifiers learned from both modalities (video and audio) is conducted at decision level. Our method is evaluated on the Emotion Recognition In The Wild Challenge (EmotiW 2013). The experimental results on …
A Simple Integration Of Social Relationship And Text Data For Identifying Potential Customers In Microblogging,
2013
Singapore Management University
A Simple Integration Of Social Relationship And Text Data For Identifying Potential Customers In Microblogging, Guansong Pang, Shengyi Jiang, Dongyi Chen
Research Collection School Of Computing and Information Systems
Identifying potential customers among a huge number of users in microblogging is a fundamental problem for microblog marketing. One challenge in potential customer detection in microblogging is how to generate an accurate characteristic description for users, i.e., user profile generation. Intuitively, the preference of a user’s friends (i.e., the person followed by the user in microblogging) is of great importance to capture the characteristic of the user. Also, a user’s self-defined tags are often concise and accurate carriers for the user’s interests. In this paper, for identifying potential customers in microblogging, we propose a method to generate user profiles via …
Modeling Preferences With Availability Constraints,
2013
Singapore Management University
Modeling Preferences With Availability Constraints, Bingtian Dai, Hady W. Lauw
Research Collection School Of Computing and Information Systems
User preferences are commonly learned from historical data whereby users express preferences for items, e.g., through consumption of products or services. Most work assumes that a user is not constrained in their selection of items. This assumption does not take into account the availability constraint, whereby users could only access some items, but not others. For example, in subscription-based systems, we can observe only those historical preferences on subscribed (available) items. However, the objective is to predict preferences on unsubscribed (unavailable) items, which do not appear in the historical observations due to their (lack of) availability. To model preferences in …
Topicsketch: Real-Time Bursty Topic Detection From Twitter,
2013
Singapore Management University
Topicsketch: Real-Time Bursty Topic Detection From Twitter, Wei Xie, Feida Zhu, Jing Jiang, Ee Peng Lim, Ke Wang
Research Collection School Of Computing and Information Systems
Twitter has become one of the largest platforms for users around the world to share anything happening around them with friends and beyond. A bursty topic in Twitter is one that triggers a surge of relevant tweets within a short time, which often reflects important events of mass interest. How to leverage Twitter for early detection of bursty topics has therefore become an important research problem with immense practical value. Despite the wealth of research work on topic modeling and analysis in Twitter, it remains a huge challenge to detect bursty topics in real-time. As existing methods can hardly scale …
Query-Document-Dependent Fusion: A Case Study Of Multimodal Music Retrieval,
2013
National University of Singapore
Query-Document-Dependent Fusion: A Case Study Of Multimodal Music Retrieval, Zhonghua Li, Bingjun Zhang, Yi Yu, Jialie Shen, Ye Wang
Research Collection School Of Computing and Information Systems
In recent years, multimodal fusion has emerged as a promising technology for effective multimedia retrieval. Developing the optimal fusion strategy for different modality (e.g. content, metadata) has been the subject of intensive research. Given a query, existing methods derive a unified fusion strategy for all documents with the underlying assumption that the relative significance of a modality remains the same across all documents. However, this assumption is often invalid. We thus propose a general multimodal fusion framework, query-document-dependent fusion (QDDF), which derives the optimal fusion strategy for each query-document pair via intelligent content analysis of both queries and documents. By …
Two Formulas For Success In Social Media: Social Learning And Network Effects,
2013
University of Texas at Austin
Two Formulas For Success In Social Media: Social Learning And Network Effects, Liangfei Qiu, Qian Tang, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
This paper examines social learning and network effects that are particularly important for online videos, considering the limited marketing campaigns of user-generated content. Rather than combining both social learning and network effects under the umbrella of social contagion or peer influence, we develop a theoretical model and empirically identify social learning and network effects separately. Using a unique data set from YouTube, we find that both mechanisms have statistically and economically significant effects on video views, and which mechanism dominates depends on the specific video type.
Workforce Preparedness Of Information Systems Students: Perceptions Of Students, Alumni, And Employers,
2013
University of Arkansas, Fayetteville
Workforce Preparedness Of Information Systems Students: Perceptions Of Students, Alumni, And Employers, Susan Bristow
Graduate Theses and Dissertations
Employers of newly hired higher education graduates report their new workforce is not prepared. Further research was required to discover insights to the workforce readiness gap. This concurrent mixed methods study explored what competencies influenced employer's perceptions of the work-readiness of Information Systems (ISYS) undergraduate students and discovered ISYS graduates' and current ISYS students' perceptions of their work-readiness. Participants consisted of a convenience sample including 69 ISYS program upperclassmen, 20 ISYS program alumni, and 8 employers of the ISYS program graduates. ISYS program alumni completed an online Qualtrics survey to measure the participants' perception of their workforce preparedness. ISYS program …
Dynamic Joint Sentiment-Topic Mode,
2013
Singapore Management University
Dynamic Joint Sentiment-Topic Mode, Yulan He, Chenghua Lin, Wei Gao, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Social media data are produced continuously by a large and uncontrolled number of users. The dynamic nature of such data requires the sentiment and topic analysis model to be also dynamically updated, capturing the most recent language use of sentiments and topics in text. We propose a dynamic Joint Sentiment-Topic model (dJST) which allows the detection and tracking of views of current and recurrent interests and shifts in topic and sentiment. Both topic and sentiment dynamics are captured by assuming that the current sentiment-topic-specific word distributions are generated according to the word distributions at previous epochs. We study three different …
Modeling Temporal Adoptions Using Dynamic Matrix Factorization,
2013
Singapore Management University
Modeling Temporal Adoptions Using Dynamic Matrix Factorization, Freddy Chong-Tat Chua, Richard Jayadi Oentaryo, Ee Peng Lim
Research Collection School Of Computing and Information Systems
The problem of recommending items to users is relevant to many applications and the problem has often been solved using methods developed from Collaborative Filtering (CF). Collaborative Filtering model-based methods such as Matrix Factorization have been shown to produce good results for static rating-type data, but have not been applied to time-stamped item adoption data. In this paper, we adopted a Dynamic Matrix Factorization (DMF) technique to derive different temporal factorization models that can predict missing adoptions at different time steps in the users' adoption history. This DMF technique is an extension of the Non-negative Matrix Factorization (NMF) based on …
Adaptive Computer‐Generated Forces For Simulator‐Based Training, Expert Systems With Applications,
2013
Singapore Management University
Adaptive Computer‐Generated Forces For Simulator‐Based Training, Expert Systems With Applications, Teck-Hou Teng, Ah-Hwee Tan, Loo-Nin Teow
Research Collection School Of Computing and Information Systems
Simulator-based training is in constant pursuit of increasing level of realism. The transition from doctrine-driven computer-generated forces (CGF) to adaptive CGF represents one such effort. The use of doctrine-driven CGF is fraught with challenges such as modeling of complex expert knowledge and adapting to the trainees’ progress in real time. Therefore, this paper reports on how the use of adaptive CGF can overcome these challenges. Using a self-organizing neural network to implement the adaptive CGF, air combat maneuvering strategies are learned incrementally and generalized in real time. The state space and action space are extracted from the same hierarchical doctrine …
Consumer Adoption Of Health Information Systems,
2013
University of Arkansas, Fayetteville
Consumer Adoption Of Health Information Systems, Sankara Subramanian Srinivasan
Graduate Theses and Dissertations
At nearly 18 percent of the country's GDP, the U.S. healthcare industry continues to wrestle with growing cost and a quality of care that does not match the increased spending. The dominant focus to date has been on promoting Health IT (HIT) system implementation and digitizing health records at the provider's end, with scant attention to the role of the patient in the healthcare process. The source of inefficiency in the healthcare system is not only on account of shortcomings at the provider's end but also due to non-compliance (such as failing to adhere to medication advice and follow-up visits) …
Client-Based Qos Monitoring And Evaluation Architecture For Network Infrastructure And Services,
2013
Western Michigan University
Client-Based Qos Monitoring And Evaluation Architecture For Network Infrastructure And Services, Ammar Mohammed Kamel
Dissertations
Providing an efficient Quality-of-Service (QoS) measurement model is a challenging problem in today’s mobile computing and telecommunications networks. Currently, most of QoS techniques utilize service measurements that are collected by the network elements (i.e., network-side monitoring) to evaluate the network performance. However, this process does not take into account the service performance from the clients' perspective and might contradict with the Service Level Agreement (SLA). In order to overcome the limitations of service-side QoS monitoring, a number of research studies have been conducted to present alternative architectures and algorithms for client-side QoS service assessment in computer networks. The client-side QoS …
Automatic Domain Identification For Linked Open Data,
2013
Wright State University - Main Campus
Automatic Domain Identification For Linked Open Data, Sarasi Lalithsena, Pascal Hitzler, Amit P. Sheth, Prateek Jain
Kno.e.sis Publications
Linked Open Data (LOD) has emerged as one of the largest collections of interlinked structured datasets on the Web. Although the adoption of such datasets for applications is increasing, identifying relevant datasets for a specific task or topic is still challenging. As an initial step to make such identification easier, we provide an approach to automatically identify the topic domains of given datasets. Our method utilizes existing knowledge sources, more specifically Freebase, and we present an evaluation which validates the topic domains we can identify with our system. Furthermore, we evaluate the effectiveness of identified topic domains for the purpose …
Semantics-Empowered Big Data Processing With Applications,
2013
Wright State University - Main Campus
Semantics-Empowered Big Data Processing With Applications, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
We discuss the nature of Big Data and address the role of semantics in analyzing and processing Big Data that arises in the context of Physical-Cyber-Social Systems. We organize our research around the Five Vs of Big Data, where four of the Vs are harnessed to produce the fifth V - value. To handle the challenge of Volume, we advocate semantic perception that can convert low-level observational data to higher-level abstractions more suitable for decision-making. To handle the challenge of Variety, we resort to the use of semantic models and annotations of data so that much of the intelligent processing …
Vireo/Ecnu @ Trecvid 2013: A Video Dance Of Detection, Recounting And Search With Motion Relativity And Concept Learning From Wild,
2013
Singapore Management University
Vireo/Ecnu @ Trecvid 2013: A Video Dance Of Detection, Recounting And Search With Motion Relativity And Concept Learning From Wild, Chong-Wah Ngo, Feng Wang, Wei Zhang, Chun-Chet Tan, Zhanhu Sun, Shi-Ai Zhu, Ting Yao
Research Collection School Of Computing and Information Systems
The VIREO group participated in four tasks: instance search, multimedia event recounting, multimedia event detection, and semantic indexing. In this paper, we will present our approaches and discuss the evaluation results
A Social Network-Empowered Research Analytics Framework For Project Selection,
2013
City University of Hong Kong
A Social Network-Empowered Research Analytics Framework For Project Selection, Thushari Silva, Zhiling Guo, Jian Ma, Hongbing Jiang, Huaping Chen
Research Collection School Of Computing and Information Systems
Traditional approaches for research project selection by government funding agencies mainly focus on the matching of research relevance by keywords or disciplines. Other research relevant information such as social connections (e.g., collaboration and co-authorship) and productivity (e.g., quality, quantity, and citations of published journal articles) of researchers is largely ignored. To overcome these limitations, this paper proposes a social network-empowered research analytics framework (RAF) for research project selections. Scholarmate.com, a professional research social network with easy access to research relevant information, serves as a platform to build researcher profiles from three dimensions, i.e., relevance, productivity and connectivity. Building upon profiles …
Social Sensing For Urban Crisis Management: The Case Of Singapore Haze,
2013
Singapore Management University
Social Sensing For Urban Crisis Management: The Case Of Singapore Haze, Philips Kokoh Prasetyo, Ming Gao, Ee Peng Lim, Christie N. Scollon
Research Collection School Of Computing and Information Systems
Sensing social media for trends and events has become possible as increasing number of users rely on social media to share information. In the event of a major disaster or social event, one can therefore study the event quickly by gathering and analyzing social media data. One can also design appropriate responses such as allocating resources to the affected areas, sharing event related information, and managing public anxiety. Past research on social event studies using social media often focused on one type of data analysis (e.g., hashtag clusters, diffusion of events, influential users, etc.) on a single social media data …
Predicting Best Answerers For New Questions: An Approach Leveraging Topic Modeling And Collaborative Voting,
2013
Singapore Management University
Predicting Best Answerers For New Questions: An Approach Leveraging Topic Modeling And Collaborative Voting, Yuan Tian, Pavneet Singh Kochhar, Ee Peng Lim, Feida Zhu, David Lo
Research Collection School Of Computing and Information Systems
Community Question Answering (CQA) sites are becoming increasingly important source of information where users can share knowledge on various topics. Although these platforms bring new opportunities for users to seek help or provide solutions, they also pose many challenges with the ever growing size of the community. The sheer number of questions posted everyday motivates the problem of routing questions to the appropriate users who can answer them. In this paper, we propose an approach to predict the best answerer for a new question on CQA site. Our approach considers both user interest and user expertise relevant to the topics …
Covariance Selection By Thresholding The Sample Correlation Matrix,
2013
Singapore Management University LARC
Covariance Selection By Thresholding The Sample Correlation Matrix, Binyan Jiang
Research Collection School Of Computing and Information Systems
This article shows that when the nonzero coefficients of the population correlation matrix are all greater in absolute value than (C1logp/n)1/2 for some constant C1, we can obtain covariance selection consistency by thresholding the sample correlation matrix. Furthermore, the rate (logp/n)1/2 is shown to be optimal.
Predicting User's Political Party Using Ideological Stances,
2013
Singapore Management University
Predicting User's Political Party Using Ideological Stances, Swapna Gottopati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang
Research Collection School Of Computing and Information Systems
Predicting users political party in social media has important impacts on many real world applications such as targeted advertising, recommendation and personalization. Several political research studies on it indicate that political parties’ ideological beliefs on sociopolitical issues may influence the users political leaning. In our work, we exploit users’ ideological stances on controversial issues to predict political party of online users. We propose a collaborative filtering approach to solve the data sparsity problem of users stances on ideological topics and apply clustering method to group the users with the same party. We evaluated several state-of-the-art methods for party prediction task …
