Impact Of Multimedia In Sina Weibo: Popularity And Life Span,
2012
Singapore Management University
Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou
Research Collection School Of Computing and Information Systems
Multimedia contents such as images and videos are widely used in social network sites nowadays. Sina Weibo, a Chinese microblogging service, is one of the first microblog platforms to incorporate multimedia content sharing features. This work provides statistical analysis on how multimedia contents are produced, consumed, and propagated in Sina Weibo. Based on 230 million tweets and 1.8 million user profiles in Sina Weibo, we study the impact of multimedia contents on the popularity of both users and tweets as well as tweet life span. Our preliminary study shows that multimedia tweets dominant pure text ones in SinaWeibo. Multimedia contents …
Virtual Phd Courses – A New Mode Of Phd Education?,
2012
Agder University College
Virtual Phd Courses – A New Mode Of Phd Education?, Bjørn Erik Munkvold, Ilze Zigurs, Deepak Khazanchi
Information Systems and Quantitative Analysis Faculty Proceedings & Presentations
This paper presents experiences from a joint virtual PhD course for doctoral students at a Norwegian and a US university. Based on an experiential learning approach, the course focused on practices for virtual research collaboration. Through six synchronous online sessions, interspersed with interaction in sub-teams, the participants worked on developing a joint conference publication. This gave the PhD students first-hand experience with working in a virtual research team. Based on our analysis of the experiences from the course, we discuss challenges of the virtual course setting and present guidelines for the design and conduct of similar virtual courses. Our results …
A Generalized Cluster Centroid Based Classifier For Text Categorization,
2012
Singapore Management University
A Generalized Cluster Centroid Based Classifier For Text Categorization, Guansong Pang, Shengyi Jiang
Research Collection School Of Computing and Information Systems
In this paper, a Generalized Cluster Centroid based Classifier (GCCC) and its variants for text categorization are proposed by utilizing a clustering algorithm to integrate two wellknown classifiers, i.e., the K-nearest-neighbor (KNN) classifier and the Rocchio classifier. KNN, a lazy learning method, suffers from inefficiency in online categorization while achieving remarkable effectiveness. Rocchio, which has efficient categorization performance, fails to obtain an expressive categorization model due to its inherent linear separability assumption. Our proposed method mainly focuses on two points: one point is that we use a clustering algorithm to strengthen the expressiveness of the Rocchio model; another one is …
Cross-View Graph Embedding,
2012
Singapore Management University
Cross-View Graph Embedding, Zhiwu Huang, S. Shan, H. Zhang, S. Lao, X. Chen
Research Collection School Of Computing and Information Systems
Recently, more and more approaches are emerging to solve the cross-view matching problem where reference samples and query samples are from different views. In this paper, inspired by Graph Embedding, we propose a unified framework for these cross-view methods called Cross-view Graph Embedding. The proposed framework can not only reformulate most traditional cross-view methods (e.g., CCA, PLS and CDFE), but also extend the typical single-view algorithms (e.g., PCA, LDA and LPP) to cross-view editions. Furthermore, our general framework also facilitates the development of new cross-view methods. In this paper, we present a new algorithm named Cross-view Local Discriminant Analysis (CLODA) …
Fast And Accurate Psd Matrix Estimation By Row Reduction,
2012
Denso Corporation
Fast And Accurate Psd Matrix Estimation By Row Reduction, Hiroshi Kuwajima, Takashi Washio, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Fast and accurate estimation of missing relations, e.g., similarity, distance and kernel, among objects is now one of the most important techniques required by major data mining tasks, because the missing information of the relations is needed in many applications such as economics, psychology, and social network communities. Though some approaches have been proposed in the last several years, the practical balance between their required computation amount and obtained accuracy are insufficient for some class of the relation estimation. The objective of this paper is to formalize a problem to quickly and efficiently estimate missing relations among objects from the …
Video Hyperlinking: Libraries And Tools For Threading And Visualizing Large Video Collection,
2012
Singapore Management University
Video Hyperlinking: Libraries And Tools For Threading And Visualizing Large Video Collection, Lei Pang, Wei Zhang, Hung-Khoon Tan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
While HTML documents could be effortlessly hyperlinked by markup tags, creation of the hyperlinks for multimedia objects is by no means easy due to the involvement of various visual processing units and intensive computational overhead. This paper introduces an open source, named VIREO-VH, which provides end-to-end support for creating hyperlinks to thread and visualize collections of videos. The software components include video pre-processing, bag-ofwords based inverted file indexing for scalable near-duplicate keyframe search, localization of partial near-duplicate segments, and galaxy visualization of video collection. The open source has been internally used by VIREO research team since 2007, and was evolved …
Vireo@Trecvid 2012: Searching With Topology, Recounting Will Small Concepts, Learning With Free Examples,
2012
Singapore Management University
Vireo@Trecvid 2012: Searching With Topology, Recounting Will Small Concepts, Learning With Free Examples, Wei Zhang, Chun-Chet Tan, Shi-Ai Zhu, Ting Yao, Lei Pang, Chong-Wah Ngo
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.
Cognitive Architectures And Autonomy: Commentary And Response,
2012
Singapore Management University
Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin
Research Collection School Of Computing and Information Systems
This paper provides a very useful and promising analysis and comparison of current architectures of autonomous intelligent systems acting in real time and specific contexts, with all their constraints. The chosen issue of Cognitive Architectures and Autonomy is really a challenge for AI current projects and future research. I appreciate and endorse not only that challenge but many specific choices and claims; in particular: (i) that “autonomy” is a key concept for general intelligent systems; (ii) that “a core issue in cognitive architecture is the integration of cognitive processes ....”; (iii) the analysis of features and capabilities missing in current …
Divad: A Dynamic And Interactive Visual Analytical Dashboard For Exploring And Analyzing Transport Data,
2012
Singapore Management University
Divad: A Dynamic And Interactive Visual Analytical Dashboard For Exploring And Analyzing Transport Data, Tin Seong Kam, Ketan Barshikar, Shaun Jun Hua Tan
Research Collection School Of Computing and Information Systems
The advances in location-based data collection technologies such as GPS, RFID etc. and the rapid reduction of their costs provide us with a huge and continuously increasing amount of data about movement of vehicles, people and goods in an urban area. This explosive growth of geospatially-referenced data has far outpaced the planner’s ability to utilize and transform the data into insightful information thus creating an adverse impact on the return on the investment made to collect and manage this data. Addressing this pressing need, we designed and developed DIVAD, a dynamic and interactive visual analytics dashboard to allow city planners …
Multiview Semi-Supervised Learning With Consensus,
2012
Nanyang Technological University
Multiview Semi-Supervised Learning With Consensus, Guangxia Li, Kuiyu Chang, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications. Semi-supervised learning aims to improve the performance of a classifier trained with limited number of labeled data by utilizing the unlabeled ones. This paper demonstrates a way to improve the transductive SVM, which is an existing semi-supervised learning algorithm, by employing a multiview learning paradigm. Multiview learning is based on the fact that for some problems, there may exist multiple perspectives, so called views, of each data sample. For example, in text classification, the typical view contains a large number of raw content features such …
A Unified Learning Framework For Auto Face Annotation By Mining Web Facial Images,
2012
Nanyang Technological University
A Unified Learning Framework For Auto Face Annotation By Mining Web Facial Images, Dayong Wang, Steven C. H. Hoi, Ying He
Research Collection School Of Computing and Information Systems
Auto face annotation plays an important role in many real-world multimedia information and knowledge management systems. Recently there is a surge of research interests in mining weakly-labeled facial images on the internet to tackle this long-standing research challenge in computer vision and image understanding. In this paper, we present a novel unified learning framework for face annotation by mining weakly labeled web facial images through interdisciplinary efforts of combining sparse feature representation, content-based image retrieval, transductive learning and inductive learning techniques. In particular, we first introduce a new search-based face annotation paradigm using transductive learning, and then propose an effective …
Google Apps For Education: Valparaiso University's Migration Experience,
2012
Valparaiso University
Google Apps For Education: Valparaiso University's Migration Experience, Rebecca Klein, Richard Orelup, Matthew Smith
Information Technology Faculty and Staff Publications
Many campuses are investigating cloud-based or hosted email solutions. This paper will cover Valparaiso University’s decision to move to the Google Apps for Education platform and our campus migration strategy. Google Apps offers significant savings in both cost of service and cost of support / maintenance while simultaneously offering functionality improvements to the campus experience over our previous system. Valparaiso University was using the GroupWise email and calendaring system and began the process of migrating all of campus to the Google Apps for Education platform in early 2011. Our process began with a student led evaluation team to select the …
Adaptive Grid Based Localized Learning For Multidimensional Data,
2012
Louisiana Tech University
Adaptive Grid Based Localized Learning For Multidimensional Data, Sheetal Saini
Doctoral Dissertations
Rapid advances in data-rich domains of science, technology, and business has amplified the computational challenges of "Big Data" synthesis necessary to slow the widening gap between the rate at which the data is being collected and analyzed for knowledge. This has led to the renewed need for efficient and accurate algorithms, framework, and algorithmic mechanisms essential for knowledge discovery, especially in the domains of clustering, classification, dimensionality reduction, feature ranking, and feature selection. However, data mining algorithms are frequently challenged by the sparseness due to the high dimensionality of the datasets in such domains which is particularly detrimental to the …
Building A Computer Program To Support Children, Parents, And Distraction During Healthcare Procedures,
2012
University of Iowa
Building A Computer Program To Support Children, Parents, And Distraction During Healthcare Procedures, Kirsten Hanrahan, Ann Marie Mccarthy, Charmaine Kleiber, Kaan Ataman, W. Nick Street, M. Bridget Zimmerman, Annel L. Ersig
Business Faculty Articles and Research
This secondary data analysis used data mining methods to develop predictive models of child risk for distress during a healthcare procedure. Data used came from a study that predicted factors associated with children's responses to an intravenous catheter insertion while parents provided distraction coaching. From the 255 items used in the primary study, 44 predictive items were identified through automatic feature selection and used to build support vector machine regression models. Models were validated using multiple cross-validation tests and by comparing variables identified as explanatory in the traditional versus support vector machine regression. Rule-based approaches were applied to the model …
Neural Modeling Of Episodic Memory: Encoding, Retrieval, And Forgetting,
2012
Singapore Management University
Neural Modeling Of Episodic Memory: Encoding, Retrieval, And Forgetting, Wenwen Wang, Budhitama Subagdja, Ah-Hwee Tan, Janusz A. Starzyk
Research Collection School Of Computing and Information Systems
This paper presents a neural model that learns episodic traces in response to a continuous stream of sensory input and feedback received from the environment. The proposed model, based on fusion Adaptive Resonance Theory (fusion ART) network, extracts key events and encodes spatio-temporal relations between events by creating cognitive nodes dynamically. The model further incorporates a novel memory search procedure, which performs parallel search of stored episodic traces continuously. Combined with a mechanism of gradual forgetting, the model is able to achieve a high level of memory performance and robustness, while controlling memory consumption over time. We present experimental studies, …
A Probabilistic Graphical Model For Topic And Preference Discovery On Social Media,
2012
Capital Medical University
A Probabilistic Graphical Model For Topic And Preference Discovery On Social Media, Lu Liu, Feida Zhu, Lei Zhang, Shiqiang Yang
Research Collection School Of Computing and Information Systems
Many web applications today thrive on offering services for large-scale multimedia data, e.g., Flickr for photos and YouTube for videos. However, these data, while rich in content, are usually sparse in textual descriptive information. For example, a video clip is often associated with only a few tags. Moreover, the textual descriptions are often overly specific to the video content. Such characteristics make it very challenging to discover topics at a satisfactory granularity on this kind of data. In this paper, we propose a generative probabilistic model named Preference-Topic Model (PTM) to introduce the dimension of user preferences to enhance the …
Influentials, Novelty, And Social Contagion: The Viral Power Of Average Friends, Close Communities, And Old News,
2012
Singapore Management University
Influentials, Novelty, And Social Contagion: The Viral Power Of Average Friends, Close Communities, And Old News, Nicholas Harrigan, Palakorn Achananuparp, Ee Peng Lim
Research Collection School Of Computing and Information Systems
What is the effect of (1) popular individuals, and (2) community structures on the retransmission of socially contagious behavior? We examine a community of Twitter users over a five month period, operationalizing social contagion as ‘retweeting’, and social structure as the count of subgraphs (small patterns of ties and nodes) between users in the follower/following network. We find that popular individuals act as ‘inefficient hubs’ for social contagion: they have limited attention, are overloaded with inputs, and therefore display limited responsiveness to viral messages. We argue this contradicts the ‘law of the few’ and ‘influentials hypothesis’. We find that community …
Entity Synonyms For Structured Web Search,
2012
Microsoft Research
Entity Synonyms For Structured Web Search, Tao Cheng, Hady W. Lauw, Stelios Paparizos
Research Collection School Of Computing and Information Systems
Nowadays, there are many queries issued to search engines targeting at finding values from structured data (e.g., movie showtime of a specific location). In such scenarios, there is often a mismatch between the values of structured data (how content creators describe entities) and the web queries (how different users try to retrieve them). Therefore, recognizing the alternative ways people use to reference an entity, is crucial for structured web search. In this paper, we study the problem of automatic generation of entity synonyms over structured data toward closing the gap between users and structured data. We propose an offline, data-driven …
Computing Perception From Sensor Data,
2012
Wright State University - Main Campus
Computing Perception From Sensor Data, Payam Barnaghi, Frieder Ganz, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
This paper describes a framework for perception creation from sensor data. We propose using data abstraction techniques, in particular Symbolic Aggregate Approximation (SAX), to analyse and create patterns from sensor data. The created patterns are then linked to semantic descriptions that define thematic, spatial and temporal features, providing highly granular abstract representation of the raw sensor data. This helps to reduce the size of the data that needs to be communicated from the sensor nodes to the gateways or highlevel processing components. We then discuss a method that uses abstract patterns created by SAX method and occurrences of different observations …
Privacy Preserving Boosting In The Cloud With Secure Half-Space Queries,
2012
Wright State University - Main Campus
Privacy Preserving Boosting In The Cloud With Secure Half-Space Queries, Shumin Guo, Keke Chen
Kno.e.sis Publications
This paper presents a preliminary study on the PerturBoost approach that aims to provide efficient and secure classifier learning in the cloud with both data and model privacy preserved.
