Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Singapore Management University (2966)
- Wright State University (632)
- Walden University (447)
- Selected Works (287)
- New Jersey Institute of Technology (137)
-
- University of Nebraska at Omaha (119)
- California State University, San Bernardino (96)
- Old Dominion University (95)
- San Jose State University (85)
- University of Dayton (82)
- The University of Maine (67)
- City University of New York (CUNY) (65)
- University of Nebraska - Lincoln (54)
- Air Force Institute of Technology (53)
- SelectedWorks (53)
- Technological University Dublin (51)
- University of South Florida (50)
- Kennesaw State University (46)
- Nova Southeastern University (43)
- Claremont Colleges (42)
- University of Arkansas, Fayetteville (42)
- University of Wisconsin Milwaukee (42)
- Western Kentucky University (41)
- Dakota State University (39)
- Institute of Business Administration (38)
- California Polytechnic State University, San Luis Obispo (36)
- Western University (35)
- Ateneo de Manila University (34)
- Governors State University (34)
- Purdue University (34)
- Keyword
-
- Machine learning (101)
- Information technology (93)
- Data mining (89)
- Social media (78)
- Twitter (64)
-
- Machine Learning (57)
- Cybersecurity (54)
- Semantic Web (54)
- Deep learning (52)
- Artificial intelligence (49)
- Online learning (49)
- Information Technology (47)
- Classification (46)
- Cloud computing (45)
- Information retrieval (45)
- Privacy (45)
- Big data (44)
- Database (43)
- Ontology (43)
- Computer science (42)
- Information security (41)
- Algorithms (40)
- Security (40)
- Databases (39)
- Information systems (39)
- Management (37)
- Clustering (36)
- Data Mining (36)
- Northern Ohio Data and Information Service (NODIS) (36)
- Technology (35)
- Publication Year
- Publication
-
- Research Collection School Of Computing and Information Systems (2872)
- Kno.e.sis Publications (541)
- Walden Dissertations and Doctoral Studies (447)
- Theses and Dissertations (116)
- Dissertations (107)
-
- Computer Science Faculty Publications (91)
- Computer Science and Engineering Faculty Publications (91)
- Theses Digitization Project (84)
- Master's Projects (68)
- Information Systems and Quantitative Analysis Faculty Proceedings & Presentations (64)
- Electronic Theses and Dissertations (55)
- Dissertations and Theses Collection (Open Access) (50)
- Theses (46)
- USF Tampa Graduate Theses and Dissertations (46)
- CCE Theses and Dissertations (42)
- Information Systems and Quantitative Analysis Faculty Publications (41)
- Kyriakos MOURATIDIS (40)
- CGU Faculty Publications and Research (37)
- International Conference on Information and Communication Technologies (36)
- Open Educational Resources (34)
- Department of Information Systems & Computer Science Faculty Publications (33)
- Graduate Theses and Dissertations (33)
- All Capstone Projects (32)
- Masters Theses & Doctoral Dissertations (32)
- Articles (29)
- Conference papers (28)
- David LO (28)
- Journal of Spatial Information Science (28)
- All Maxine Goodman Levin School of Urban Affairs Publications (27)
- Saverio Perugini (25)
- Publication Type
Articles 4321 - 4350 of 6727
Full-Text Articles in Physical Sciences and Mathematics
Understanding User Triads On Facebook, Derek Doran, Alberta De La Rosa Algarin, Swapna S. Gokhale
Understanding User Triads On Facebook, Derek Doran, Alberta De La Rosa Algarin, Swapna S. Gokhale
Kno.e.sis Publications
Contemporary approaches that analyze user behavior on online social networks only consider interactions among dyads, which are pairs of directly connected users. A large body of sociological work, however, suggests that mutual connections among users can influence their activities, leading to differences between two- and three-way interactions. This paper explores the dynamics of triads among Facebook users based on the wall posts from the New Orleans regional network. Initially, each connection is categorized as a close friendship or an acquiantance, contingent on the number of wall posts exchanged. Subsequently, the impact of different types of connections comprising triads is examined …
Linked Data Demystified: Practical Efforts To Transform Contentdm Metadata For The Linked Data Cloud, Silvia B. Southwick, Cory K. Lampert
Linked Data Demystified: Practical Efforts To Transform Contentdm Metadata For The Linked Data Cloud, Silvia B. Southwick, Cory K. Lampert
Library Faculty Presentations
The library literature and events like the ALA Annual Conference have been inundated with presentations and articles on linked data. At UNLV Libraries, we understand the importance of linked data in helping to better service our users. We have designed and initiated a pilot project to apply linked data concepts to the practical task of transforming a sample set of our CONTENTdm digital collections data into future-oriented linked data. This presentation will outline rationale for beginning work in linked data and detail the phases we will undertake in the proof of concept project. We hope through this research experiment to …
Audit Mechanisms For Provable Risk Management And Accountable Data Governance, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha
Audit Mechanisms For Provable Risk Management And Accountable Data Governance, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha
Research Collection School Of Computing and Information Systems
Organizations that collect and use large volumes of personal information are expected under the principle of accountable data governance to take measures to protect data subjects from risks that arise from inapproriate uses of this information. In this paper, we focus on a specific class of mechanisms—audits to identify policy violators coupled with punishments—that organizations such as hospitals, financial institutions, and Web services companies may adopt to protect data subjects from privacy and security risks stemming from inappropriate information use by insiders. We model the interaction between the organization (defender) and an insider (adversary) during the audit process as a …
Joint Topic Modeling For Event Summarization Across News And Social Media Streams, Wei Gao, Peng Li, Kareem Darwish
Joint Topic Modeling For Event Summarization Across News And Social Media Streams, Wei Gao, Peng Li, Kareem Darwish
Research Collection School Of Computing and Information Systems
Social media streams such as Twitter are regarded as faster first-hand sources of information generated by massive users. The content diffused through this channel, although noisy, provides important complement and sometimes even a substitute to the traditional news media reporting. In this paper, we propose a novel unsupervised approach based on topic modeling to summarize trending subjects by jointly discovering the representative and complementary information from news and tweets. Our method captures the content that enriches the subject matter by reinforcing the identification of complementary sentence-tweet pairs. To valuate the complementarity of a pair, we leverage topic modeling formalism by …
Virtual Phd Courses – A New Mode Of Phd Education?, Bjørn Erik Munkvold, Ilze Zigurs, Deepak Khazanchi
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 …
How I Would Like Semantic Web To Be, For My Children., Raghava Mutharaju
How I Would Like Semantic Web To Be, For My Children., Raghava Mutharaju
Kno.e.sis Publications
Semantic Web, since its inception, has gone through lot of developments in its relatively nascent existence; right from people's perception, to the standards and to its adoption by the industry and more importantly by the scientific community. This impressive growth only seems to increase. In this paper, we project this growth to the next 10 years and highlight some of the facets on which Semantic Web could have a major impact on. We also present the challenges that Semantic Web and its community has to deal with in order to get there.
Iexplore: Interactive Browsing And Exploring Biomedical Knowledge, Vinh Nguyen, Olivier Bodenreider, Jagannathan Srinivasan, Todd Minning, Thomas Rindflesch, Bastien Rance, Ramakanth Kavuluru, Himi Yalamanchili, Krishnaprasad Thirunarayan, Satya S. Sahoo, Amit P. Sheth
Iexplore: Interactive Browsing And Exploring Biomedical Knowledge, Vinh Nguyen, Olivier Bodenreider, Jagannathan Srinivasan, Todd Minning, Thomas Rindflesch, Bastien Rance, Ramakanth Kavuluru, Himi Yalamanchili, Krishnaprasad Thirunarayan, Satya S. Sahoo, Amit P. Sheth
Kno.e.sis Publications
We present iExplore, a Semantic Web based application that helps biomedical researchers study and explore biomedical knowledge interactively. iExplore uses the Biomedical Knowledge Repository (BKR), which integrates knowledge from various sources ranging from information extracted from biomedical literature (from PubMed) to many structured vocabularies in the Unified Medical Language System (UMLS). The current version of BKR provides a unified provenance representation for 12 million semantic predications (triples with a predicate connecting a subject and an object) derived from 87 vocabulary families in the UMLS and 14 million predications extracted from 21 million PubMed abstracts. To engage the domain experts in …
An Efficient Bit Vector Approach To Semantics-Based Machine Perception In Resource-Constrained Devices, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth
An Efficient Bit Vector Approach To Semantics-Based Machine Perception In Resource-Constrained Devices, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
The primary challenge of machine perception is to define efficient computational methods to derive high-level knowledge from low-level sensor observation data. Emerging solutions are using ontologies for expressive representation of concepts in the domain of sensing and perception, which enable advanced integration and interpretation of heterogeneous sensor data. The computational complexity of OWL, however, seriously limits its applicability and use within resource-constrained environments, such as mobile devices. To overcome this issue, we employ OWL to formally define the inference tasks needed for machine perception – explanation and discrimination – and then provide efficient algorithms for these tasks, using bit-vector encodings …
Multiview Semi-Supervised Learning With Consensus, Guangxia Li, Kuiyu Chang, Steven C. H. Hoi
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 Generalized Cluster Centroid Based Classifier For Text Categorization, Guansong Pang, Shengyi Jiang
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 …
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
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.
Cross-View Graph Embedding, Zhiwu Huang, S. Shan, H. Zhang, S. Lao, X. Chen
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) …
Video Hyperlinking: Libraries And Tools For Threading And Visualizing Large Video Collection, Lei Pang, Wei Zhang, Hung-Khoon Tan, Chong-Wah Ngo
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 …
Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin
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 …
Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou
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 …
Divad: A Dynamic And Interactive Visual Analytical Dashboard For Exploring And Analyzing Transport Data, Tin Seong Kam, Ketan Barshikar, Shaun Jun Hua Tan
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 …
Fast And Accurate Psd Matrix Estimation By Row Reduction, Hiroshi Kuwajima, Takashi Washio, Ee Peng Lim
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 …
Mining Coherent Anomaly Collections On Web Data, Hanbo Dai, Feida Zhu, Ee-Peng Lim, Hwee Hwa Pang
Mining Coherent Anomaly Collections On Web Data, Hanbo Dai, Feida Zhu, Ee-Peng Lim, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
The recent boom of weblogs and social media has attached increasing importance to the identification of suspicious users with unusual behavior, such as spammers or fraudulent reviewers. A typical spamming strategy is to employ multiple dummy accounts to collectively promote a target, be it a URL or a product. Consequently, these suspicious accounts exhibit certain coherent anomalous behavior identifiable as a collection. In this paper, we propose the concept of Coherent Anomaly Collection (CAC) to capture this kind of collections, and put forward an efficient algorithm to simultaneously find the top-K disjoint CACs together with their anomalous behavior patterns. Compared …
A Unified Learning Framework For Auto Face Annotation By Mining Web Facial Images, Dayong Wang, Steven C. H. Hoi, Ying He
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 …
Analysis - Toward A New American Military., Adam Lowther, Jan Kallberg
Analysis - Toward A New American Military., Adam Lowther, Jan Kallberg
Jan Kallberg
In releasing the United States Department of Defense’s (DoD) Sustaining U.S. Global Leadership: Priorities for 21st Century Defense and Defense Budget Priorities and Choices in January 2012, President Barack Obama and Secretary of Defense Leon Panetta offered a rationale for the administration’s reductions in defense spending. By stating that the shift in strategic direction is an effort to “put our fiscal house in order” and a response to the 2011 Budget Control Act, which requires DoD to reduce spending by $487 billion between fiscal years 2012 and 2021, the United States’ NATO partners in Europe were given considerable reason for …
Competition In Information Technologies: Standards-Essential Patents, Non-Practicing Entities And Frand Bidding, Herbert J. Hovenkamp
Competition In Information Technologies: Standards-Essential Patents, Non-Practicing Entities And Frand Bidding, Herbert J. Hovenkamp
All Faculty Scholarship
Standard Setting is omnipresent in networked information technologies. Virtually every cellular phone, computer, digital camera or similar device contains technologies governed by a collaboratively developed standard. If these technologies are to perform competitively, the processes by which standards are developed and implemented must be competitive. In this case attaining competitive results requires a mixture of antitrust and non-antitrust legal tools.
FRAND refers to a firm’s ex ante commitment to make its technology available at a “fair, reasonable and nondiscriminatory royalty.” The FRAND commitment results from bidding to have one’s own technology selected as a standard. Typically the FRAND commitment is …
Privacy Preserving Boosting In The Cloud With Secure Half-Space Queries, Shumin Guo, Keke Chen
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.
Google Apps For Education: Valparaiso University's Migration Experience, Rebecca Klein, Richard Orelup, Matthew Smith
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, Sheetal Saini
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 …
Computing Perception From Sensor Data, Payam Barnaghi, Frieder Ganz, Cory Andrew Henson, Amit P. Sheth
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 …
The Shanghai-Hongkong Team At Mediaeval2012: Violent Scene Detection Using Trajectory-Based Features, Yu-Gang Jiang, Qi Dai, Chun Chet Tan, Xiangyang Xue, Chong-Wah Ngo
The Shanghai-Hongkong Team At Mediaeval2012: Violent Scene Detection Using Trajectory-Based Features, Yu-Gang Jiang, Qi Dai, Chun Chet Tan, Xiangyang Xue, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The Violent Scene Detection task offers a very practical challenge in detecting complex and diverse violent video clips in movies. In this working note paper, we will briefly describe our system and discuss the results, which achieved top performance in mAP@201 and runner-up in mAP@100, among all 35 submissions worldwide. The central component of our system is a set of features derived from the appearance and motion of local patch trajectories [2]. We use these features and SVM classifier as the baseline approach and add in a few other components to further improve the performance. Our findings indicate that the …
Trajectory-Based Modeling Of Human Actions With Motion Reference Points, Yu-Gang Jiang, Qi Dai, Xiangyang Xue, Wei Liu, Chong-Wah Ngo
Trajectory-Based Modeling Of Human Actions With Motion Reference Points, Yu-Gang Jiang, Qi Dai, Xiangyang Xue, Wei Liu, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Human action recognition in videos is a challenging problem with wide applications. State-of-the-art approaches often adopt the popular bag-of-features representation based on isolated local patches or temporal patch trajectories, where motion patterns like object relationships are mostly discarded. This paper proposes a simple representation specifically aimed at the modeling of such motion relationships. We adopt global and local reference points to characterize motion information, so that the final representation can be robust to camera movement. Our approach operates on top of visual codewords derived from local patch trajectories, and therefore does not require accurate foreground-background separation, which is typically a …
Neural Modeling Of Episodic Memory: Encoding, Retrieval, And Forgetting, Wenwen Wang, Budhitama Subagdja, Ah-Hwee Tan, Janusz A. Starzyk
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, …
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
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 …
Entity Synonyms For Structured Web Search, Tao Cheng, Hady W. Lauw, Stelios Paparizos
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 …