ORCID Profile
0000-0003-1734-0477
Current Organisations
CSIRO
,
University of Queensland
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Publisher: IEEE
Date: 04-2020
Publisher: Springer International Publishing
Date: 2018
Publisher: Springer Science and Business Media LLC
Date: 24-06-2021
Publisher: Springer Berlin Heidelberg
Date: 2004
DOI: 10.1007/B96838
Publisher: IEEE
Date: 2006
Publisher: Springer Science and Business Media LLC
Date: 02-09-2017
Publisher: Springer Science and Business Media LLC
Date: 10-2011
Publisher: World Scientific Pub Co Pte Ltd
Date: 2023
DOI: 10.1142/S2811032323300025
Abstract: Evidence-based Medicine (EBM) is facing a new challenge in applying Artificial Intelligence (AI) for better services. Here the fundamental question is: can AI be used as a human intelligence lifier to make better evidence-based medical decisions? This argument can only be answered if AI-supported decisions are compared and contrasted with those of human experts, and if the implementation of AI-enabled Evidence-Based Medicine (AiEBM) can be explained or justified using the available evidence and experience. In this paper, we propose AiEBM as a human-centered approach to be integrated into processes of healthcare systems, thereby increasing the credibility of the clinical decision support systems. We provide insights into the applicability of AI and its challenges and opportunities in EBM. The AaaS (AI as a Service) and high-order reasoning facilitated by machine learning and AI for medical decisions will be discussed.
Publisher: Elsevier BV
Date: 10-2023
Publisher: Springer Berlin Heidelberg
Date: 2007
Publisher: Inderscience Publishers
Date: 2011
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2022
Publisher: Springer Science and Business Media LLC
Date: 27-11-2016
Publisher: Association for Computing Machinery (ACM)
Date: 07-2011
Abstract: Both similarity-based and popularity-based document ranking functions have been successfully applied to information retrieval (IR) in general. However, the dimension of semantic granularity also should be considered for effective retrieval. In this article, we propose a semantic granularity-based IR model that takes into account the three dimensions, namely similarity, popularity, and semantic granularity, to improve domain-specific search. In particular, a concept-based computational model is developed to estimate the semantic granularity of documents with reference to a domain ontology. Semantic granularity refers to the levels of semantic detail carried by an information item. The results of our benchmark experiments confirm that the proposed semantic granularity based IR model performs significantly better than the similarity-based baseline in both a bio-medical and an agricultural domain. In addition, a series of user-oriented studies reveal that the proposed document ranking functions resemble the implicit ranking functions exercised by humans. The perceived relevance of the documents delivered by the granularity-based IR system is significantly higher than that produced by a popular search engine for a number of domain-specific search tasks. To the best of our knowledge, this is the first study regarding the application of semantic granularity to enhance domain-specific IR.
Publisher: IEEE
Date: 12-2017
Publisher: Inderscience Publishers
Date: 2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2006
Publisher: Springer Science and Business Media LLC
Date: 05-01-2013
Publisher: Springer Science and Business Media LLC
Date: 12-09-2020
Publisher: Inderscience Publishers
Date: 2013
Publisher: IEEE
Date: 23-09-2022
Publisher: Elsevier BV
Date: 10-2018
DOI: 10.1016/J.DIABRES.2018.07.002
Abstract: Insulin has traditionally been the gold standard pharmacological treatment for gestational diabetes mellitus (GDM). Insulin requires multiple injections a day, can cause frequent hypoglycaemia, requires careful handling, and is generally more expensive compared to oral agents. Metformin has been increasingly popular in recent years. Based on the short-term data available, metformin appears to be safe and effective for the treatment of GDM but existing studies have all stressed the lack of longer-term offspring data. This article will analyse the evidence available on the longer-term outcomes in the offspring of women with GDM treated with metformin versus insulin. Pubmed, EMBASE, CENTRAL, and CNKI were searched for follow-up studies of randomised controlled trials that compared metformin with insulin for the treatment of GDM. Existing follow-up studies did not find any significant increase in the risk of adverse effects in terms of growth and development in the offspring of GDM mothers managed with metformin versus insulin.
Publisher: Springer Science and Business Media LLC
Date: 02-08-2022
DOI: 10.1186/S40536-022-00128-6
Abstract: This study analyzed the latest four PISA surveys, 2009, 2012, 2015, and 2018, to explore the association between students’ ICT-related use and math and science performance. Using ICT Engagement Theory as a theoretical framework and a three-level hierarchical linear modeling approach, while controlling for confounding effects, ICT-related independent variables of interest were added to the models at the student, school, and country levels. The series of models revealed that, in general, an increase in ICT availability and ICT use both inside and outside school had a negative association with learning outcomes, while students’ positive attitude toward ICT demonstrated a strong positive relationship. However, students’ perceived autonomy related to ICT use had the strongest association with academic performance, which is consistent with the changing nature of the modern learning environments. Findings revealed that virtually all forms of student ICT use, both inside and outside of school and whether subject related or not, had no substantive positive relationship with student performance in math or science. Conversely, higher student attitude toward, confidence in, belief in utility of, and autonomous use of ICT was associated with higher math and science performance for each of the four years of the study. Incidentally, we also found that while country GDP per capita had no consistent association with student performance, a school’s provision of extra-curricula activities did. Recommendations for educational leaders, teachers, and parents are offered.
Publisher: Springer Science and Business Media LLC
Date: 05-10-2019
Publisher: Hindawi Limited
Date: 08-05-2021
DOI: 10.1002/INT.22434
Publisher: Springer Science and Business Media LLC
Date: 03-09-2019
Publisher: Springer International Publishing
Date: 2020
Publisher: IEEE
Date: 12-2014
DOI: 10.1109/ICDM.2014.32
Publisher: Springer Science and Business Media LLC
Date: 09-2018
Publisher: IEEE
Date: 11-2018
Publisher: Springer Berlin Heidelberg
Date: 2005
DOI: 10.1007/11564126_42
Publisher: Springer Berlin Heidelberg
Date: 2004
Publisher: IEEE
Date: 2006
Publisher: Springer International Publishing
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2014
Publisher: Springer International Publishing
Date: 2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2019
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: Springer Science and Business Media LLC
Date: 25-06-2020
Publisher: Emerald
Date: 04-2006
DOI: 10.1108/02635570610661606
Abstract: To propose an assessment framework that can be used to categorise and assess commercial web sites from the perspective of web‐technological features and functions and to demonstrate its usefulness. Drawing on prior relevant research and successful web site design experiences of industrial experts in the field, an assessment framework that can be used to categorise and assess web features and functions is proposed, and 252 commercial web sites of listed Australian companies were randomly s led and assessed to demonstrate the usefulness of the proposed assessment framework. The proposed assessment framework provides valuable insights. While different companies normally use different web‐technological features and functions on their web sites, certain features and functions have been more commonly used in designing commercial web sites than others, and certain differences in the use of web features and functions on commercial web sites exist across different industries. This research studied commercial web sites of Australian companies. Possible differences in the use of web features and functions on commercial web sites across different countries remain to be explored. Although various approaches have been proposed in previous studies to evaluate commercial web sites, no prior research could be found to assess commercial web sites from the perspective of web‐technological features and functions. This research proposed an assessment framework that can be used to categorise and assess commercial web sites from the perspective of web‐technological features and functions and demonstrated its usefulness. It also provided valuable insights to commercial web site owners and designers.
Publisher: ACM
Date: 26-10-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2022
Publisher: Springer International Publishing
Date: 2014
Publisher: Springer Berlin Heidelberg
Date: 2013
Publisher: Elsevier BV
Date: 06-2020
Publisher: Elsevier BV
Date: 2016
Publisher: World Scientific Pub Co Pte Lt
Date: 03-2003
DOI: 10.1142/S1469026803000859
Abstract: This paper proposes a novel application of fuzzy logic to web data mining for two basic problems of a website: popularity and satisfaction. Popularity means that people will visit the website while satisfaction refers to the usefulness of the site. We will illustrate that the popularity of a website is a fuzzy logic problem. It is an important characteristic of a website in order to survive in Internet commerce. The satisfaction of a website is also a fuzzy logic problem that represents the degree of success in the application of information technology to the business. We propose a framework of fuzzy logic for the representation of these two problems based on web data mining techniques to fuzzify the attributes of a website.
Publisher: Elsevier BV
Date: 08-2014
Publisher: Springer Berlin Heidelberg
Date: 2007
Publisher: Elsevier
Date: 2017
Publisher: Elsevier BV
Date: 09-2018
Publisher: Springer International Publishing
Date: 2019
Publisher: Springer Berlin Heidelberg
Date: 2005
DOI: 10.1007/11508069_39
Publisher: Springer Science and Business Media LLC
Date: 28-04-2018
Publisher: Springer Science and Business Media LLC
Date: 09-10-2019
Publisher: Elsevier BV
Date: 08-2023
Publisher: ACM
Date: 12-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Elsevier BV
Date: 03-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2008
Publisher: ACM
Date: 30-01-2019
Publisher: Springer Science and Business Media LLC
Date: 09-2019
Publisher: Frontiers Media SA
Date: 10-02-2023
DOI: 10.3389/FNINS.2023.1112355
Abstract: Automated diagnosis of intracranial hemorrhage on head computed tomography (CT) plays a decisive role in clinical management. This paper presents a prior knowledge-based precise diagnosis of blend sign network from head CT scans. We employ the object detection task as an auxiliary task in addition to the classification task, which could incorporate the hemorrhage location as prior knowledge into the detection framework. The auxiliary task could help the model pay more attention to the regions with hemorrhage, which is beneficial for distinguishing the blend sign. Furthermore, we propose a self-knowledge distillation strategy to deal with inaccuracy annotations. In the experiment, we retrospectively collected 1749 anonymous non-contrast head CT scans from the First Affiliated Hospital of China Medical University. The dataset contains three categories: no intracranial hemorrhage (non-ICH), normal intracranial hemorrhage (normal ICH), and blend sign. The experimental results demonstrate that our method performs better than other methods. Our method has the potential to assist less-experienced head CT interpreters, reduce radiologists' workload, and improve efficiency in natural clinical settings.
Publisher: IEEE
Date: 18-07-2022
Publisher: Springer Science and Business Media LLC
Date: 23-12-2012
Publisher: Springer Science and Business Media LLC
Date: 23-05-2018
Publisher: IEEE
Date: 2006
Publisher: Universidad Politecnica de Madrid - University Library
Date: 2018
Publisher: ACM
Date: 26-10-2021
Publisher: Elsevier BV
Date: 04-2013
Publisher: Springer Berlin Heidelberg
Date: 2005
DOI: 10.1007/11546849_46
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: IEEE
Date: 04-2013
Publisher: Springer Berlin Heidelberg
Date: 2007
Publisher: Society for Industrial and Applied Mathematics
Date: 29-04-2010
Publisher: Springer International Publishing
Date: 2016
Publisher: Informa UK Limited
Date: 07-02-2019
Publisher: Springer International Publishing
Date: 2016
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: Elsevier BV
Date: 04-2020
Publisher: Elsevier BV
Date: 04-2018
Publisher: Springer Berlin Heidelberg
Date: 2013
Publisher: IEEE
Date: 2005
DOI: 10.1109/MMMC.2005.35
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2016
Publisher: Springer Berlin Heidelberg
Date: 2005
DOI: 10.1007/11581062_28
Publisher: Society for Industrial and Applied Mathematics
Date: 07-05-2018
Publisher: Springer Berlin Heidelberg
Date: 2008
Publisher: Elsevier BV
Date: 02-2018
Publisher: ACM
Date: 17-10-2015
Publisher: Springer International Publishing
Date: 2022
Publisher: IEEE
Date: 04-2019
Publisher: Springer International Publishing
Date: 2019
Publisher: ACM
Date: 17-10-2015
Publisher: Association for Computing Machinery (ACM)
Date: 30-03-2016
DOI: 10.1145/2837024
Abstract: The emerging Internet of Things (IoT) bridges the gap between the physical and the digital worlds, which enables a deeper understanding of user preferences and behaviors. The rich interactions and relations between users and things call for effective and efficient recommendation approaches to better meet users’ interests and needs. In this article, we focus on the problem of things recommendation in IoT, which is important for many applications such as e-Commerce and health care. We discuss the new properties of recommending things of interest in IoT, and propose a unified probabilistic factor based framework by fusing relations across heterogeneous entities of IoT, for ex le, user-thing relations, user-user relations, and thing-thing relations, to make more accurate recommendations. Specifically, we develop a hypergraph to model things’ spatiotemporal correlations, on top of which implicit things correlations can be generated. We have built an IoT testbed to validate our approach and the experimental results demonstrate its feasibility and effectiveness.
Publisher: Springer Science and Business Media LLC
Date: 12-05-2016
Publisher: Springer International Publishing
Date: 2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2016
Publisher: Elsevier BV
Date: 03-2024
Publisher: IEEE
Date: 12-2012
Publisher: Elsevier BV
Date: 10-2019
Publisher: IEEE
Date: 05-12-2021
Publisher: Springer Science and Business Media LLC
Date: 09-04-2011
Publisher: IEEE
Date: 12-2016
Publisher: World Scientific Pub Co Pte Ltd
Date: 20-02-2023
DOI: 10.1142/S0218001423500040
Abstract: Knowledge distillation has been widely applied in semantic segmentation to reduce the model size and computational complexity. The prior knowledge distillation methods for semantic segmentation mainly focus on transferring the spatial relation knowledge, neglecting to transfer the channel correlation knowledge in the feature space, which is vital for semantic segmentation. We propose a novel Channel Correlation Distillation (CCD) method for semantic segmentation to solve this issue. The correlation between channels tells how likely these channels belong to the same categories. We force the student to mimic the teacher by minimizing the distance between the channel correlation maps of the student and the teacher. Furthermore, we propose the multi-scale discriminators to sufficiently distinguish the multi-scale differences between the teacher and student segmentation outputs. Extensive experiments on three popular datasets: Cityscapes, CamVid, and Pascal VOC 2012 validate the superiority of our CCD. Experimental results show that our CCD could consistently improve the state-of-the-art methods with various network structures for semantic segmentation.
Publisher: Informa UK Limited
Date: 20-10-2006
Publisher: Springer International Publishing
Date: 2018
Publisher: IEE
Date: 2006
DOI: 10.1049/CP:20062127
Publisher: IGI Global
Date: 2018
DOI: 10.4018/978-1-5225-3862-2.CH003
Abstract: With new developments and upcoming technologies, new sensing techniques are becoming available. Unfortunately, none of these techniques provides output interpreted the way human perception works. An inability to improve the effectiveness of these technologies limits their use in dedicated applications and increases their complexity. The growing adoption of this technology makes it critical to create a system capable of handling e-nose challenging issues such as noise, drift, imbalanced data, dynamic environment, and high uncertainties. Without appropriate pattern recognition methods that allow inferences to be derived based on patterns observed within these data sets, it will not be possible to improve the performance of current e-nose systems. In this chapter, e-nose drift issue is introduced and the available drift counteraction methods is discussed.
Publisher: World Scientific Pub Co Pte Lt
Date: 03-2007
DOI: 10.1142/S021962200700240X
Abstract: From an information systems perspective, the assessment of commercial websites can be assessed objectively or subjectively. From a business point of view, they can be assessed quantitatively or qualitatively. This paper describes taxonomy of website assessment approaches and proposes a knowledge-based system approach to evaluate commercial websites effectively. Given a large number of constantly evolving commercial websites on the Internet, our approach shows an efficient way of automatic assessment of commercial websites.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Elsevier BV
Date: 11-2021
Publisher: No publisher found
Date: 2018
Publisher: Springer Berlin Heidelberg
Date: 2007
Publisher: Springer Science and Business Media LLC
Date: 10-06-2015
Publisher: Unpublished
Date: 2017
Publisher: Elsevier BV
Date: 11-2009
Publisher: Springer Science and Business Media LLC
Date: 06-10-2016
Publisher: International Scientific Information, Inc.
Date: 07-01-2018
DOI: 10.12659/MSM.907015
Abstract: BACKGROUND The explosive increase in medical literature has changed therapeutic strategies, but it is challenging for physicians to keep up-to-date on the medical literature. Scientific literature data mining on a large-scale of can be used to refresh physician knowledge and better improve the quality of disease treatment. MATERIAL AND METHODS This paper reports on a reformulated version of a data mining method called MedRank, which is a network-based algorithm that ranks therapy for a target disease based on the MEDLINE literature database. MedRank algorithm input for this study was a clear definition of the disease model the algorithm output was the accurate recommendation of antihypertensive drugs. Hypertension with diabetes mellitus was chosen as the input disease model. The ranking output of antihypertensive drugs are based on the Joint National Committee (JNC) guidelines, one through eight, and the publication dates, ≤1977, ≤1980, ≤1984, ≤1988, ≤1993, ≤1997, ≤2003, and ≤2013. The McNemar's test was used to evaluate the efficacy of MedRank based on specific JNC guidelines. RESULTS The ranking order of antihypertensive drugs changed with the date of the published literature, and the MedRank algorithm drug recommendations had excellent consistency with the JNC guidelines in 2013 (P=1.00 from McNemar's test, Kappa=0.78, P=1.00). Moreover, the Kappa index increased over time. Sensitivity was better than specificity for MedRank in addition, sensitivity was maintained at a high level, and specificity increased from 1997 to 2013. CONCLUSIONS The use of MedRank in ranking medical literature on hypertension with diabetes mellitus in our study suggests possible application in clinical practice it is a potential method for supporting antihypertensive drug-prescription decisions.
Publisher: ACM Press
Date: 2006
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: Springer Science and Business Media LLC
Date: 15-07-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2023
Publisher: Springer Nature Switzerland
Date: 2022
Publisher: SPIE-Intl Soc Optical Eng
Date: 16-09-2013
Publisher: ACM
Date: 03-11-2019
Publisher: Elsevier BV
Date: 2018
Publisher: ACM
Date: 21-10-2013
Publisher: Elsevier BV
Date: 11-2021
Publisher: Wiley
Date: 16-01-2014
DOI: 10.1111/COIN.12028
Publisher: IEEE Comput. Soc
Date: 2003
Publisher: IEEE
Date: 04-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2018
Publisher: ACM
Date: 31-10-2005
Publisher: Springer International Publishing
Date: 2015
Publisher: IEEE
Date: 23-05-2022
Publisher: Elsevier BV
Date: 04-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Springer Science and Business Media LLC
Date: 15-05-2011
Publisher: Elsevier BV
Date: 2024
Publisher: Springer US
Date: 2009
Publisher: Springer Berlin Heidelberg
Date: 2005
DOI: 10.1007/11546849
Publisher: IEEE Comput. Soc
Date: 2003
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: IEEE
Date: 07-2010
Publisher: IEEE
Date: 2006
Publisher: Springer International Publishing
Date: 2018
Publisher: Elsevier BV
Date: 02-2018
Publisher: ACM
Date: 10-10-2004
Publisher: Inderscience Publishers
Date: 2013
Publisher: Springer International Publishing
Date: 2018
Publisher: Springer International Publishing
Date: 24-08-2014
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Springer Berlin Heidelberg
Date: 2003
Publisher: ACM
Date: 24-10-2016
Publisher: Springer Science and Business Media LLC
Date: 03-03-2023
Publisher: Springer US
Date: 2009
Publisher: Institution of Engineering and Technology (IET)
Date: 2007
Publisher: IEEE
Date: 11-2015
Publisher: Association for Computing Machinery (ACM)
Date: 10-2014
DOI: 10.1145/2648583
Abstract: Online human gesture recognition has a wide range of applications in computer vision, especially in human-computer interaction applications. The recent introduction of cost-effective depth cameras brings a new trend of research on body-movement gesture recognition. However, there are two major challenges: (i) how to continuously detect gestures from unsegmented streams, and (ii) how to differentiate different styles of the same gesture from other types of gestures. In this article, we solve these two problems with a new effective and efficient feature extraction method—Structured Streaming Skeleton (SSS)—which uses a dynamic matching approach to construct a feature vector for each frame. Our comprehensive experiments on MSRC-12 Kinect Gesture, Huawei/3DLife-2013, and MSR-Action3D datasets have demonstrated superior performances than the state-of-the-art approaches. We also demonstrate model selection based on the proposed SSS feature, where the classifier of squared loss regression with l 2,1 norm regularization is a recommended classifier for best performance.
Publisher: Springer Science and Business Media LLC
Date: 04-09-2008
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: BMJ
Date: 10-1993
Abstract: The conotruncal anomaly face syndrome was described in a Japanese publication in 1976 and comprises dysmorphic facial appearance and outflow tract defects of the heart. The authors subsequently noted similarities to Shprintzen syndrome and DiGeorge syndrome. Chromosome analysis in five cases did not show a deletion at high resolution, but fluorescent in situ hybridisation using probe DO832 showed a deletion within chromosome 22q11 in all cases.
Publisher: Association for Computing Machinery (ACM)
Date: 06-03-2017
DOI: 10.1145/3003729
Abstract: In the era of big data, a mechanism that can automatically annotate disease codes to patients’ records in the medical information system is in demand. The purpose of this work is to propose a framework that automatically annotates the disease labels of multi-source patient data in Intensive Care Units (ICUs). We extract features from two main sources, medical charts and notes. The Bag-of-Words model is used to encode the features. Unlike most of the existing multi-label learning algorithms that globally consider correlations between diseases, our model learns disease correlation locally in the patient data. To achieve this, we derive a local disease correlation representation to enrich the discriminant power of each patient data. This representation is embedded into a unified multi-label learning framework. We develop an alternating algorithm to iteratively optimize the objective function. Extensive experiments have been conducted on a real-world ICU database. We have compared our algorithm with representative multi-label learning algorithms. Evaluation results have shown that our proposed method has state-of-the-art performance in the annotation of multiple diagnostic codes for ICU patients. This study suggests that problems in the automated diagnosis code annotation can be reliably addressed by using a multi-label learning model that exploits disease correlation. The findings of this study will greatly benefit health care and management in ICU considering that the automated diagnosis code annotation can significantly improve the quality and management of health care for both patients and caregivers.
Publisher: Elsevier BV
Date: 09-2013
Publisher: Springer Berlin Heidelberg
Date: 2004
Publisher: Springer Berlin Heidelberg
Date: 2004
Publisher: ACM
Date: 12-09-2016
Publisher: Springer International Publishing
Date: 2014
Publisher: IEEE
Date: 10-2016
Publisher: ACM
Date: 03-11-2014
Publisher: Elsevier BV
Date: 12-2018
Publisher: Informa UK Limited
Date: 30-01-2020
Publisher: Elsevier BV
Date: 08-2020
Publisher: Springer Berlin Heidelberg
Date: 2004
DOI: 10.1007/B97861
Publisher: IEEE
Date: 2007
Publisher: IEEE
Date: 10-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2023
Publisher: IEEE
Date: 2007
Publisher: Informa UK Limited
Date: 02-2014
DOI: 10.1057/HS.2013.8
Publisher: ACM
Date: 24-10-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2008
DOI: 10.1109/MIC.2009.18
Publisher: IEEE
Date: 12-2011
Publisher: IEEE
Date: 05-2011
Publisher: Unpublished
Date: 2014
Publisher: Springer Science and Business Media LLC
Date: 04-07-2018
Publisher: Elsevier BV
Date: 08-2010
Publisher: Springer International Publishing
Date: 2017
Publisher: Elsevier BV
Date: 04-2009
Publisher: IGI Global
Date: 2009
DOI: 10.4018/978-1-60566-618-1.CH008
Abstract: In this paper, we propose a framework namely, Prediction-Learning-Distillation (PLD) for interactive document classification and distilling the misclassified documents. Whenever a user points out misclassified documents, the PLD learns from the mistakes and identifies the same mistakes from all other classified documents. The PLD then enforces this learning for future classifications. If the classifier fails to accept relevant documents or reject irrelevant documents on certain categories, then PLD will assign those documents as new positive/negative training instances. The classifier can then strengthen its weakness by learning from these new training instances. Our experiments results have demonstrated that the proposed algorithm can learn from user identified misclassified documents, and then distil the rest successfully.
Publisher: Springer International Publishing
Date: 2017
Publisher: Informa UK Limited
Date: 20-10-2006
Publisher: Springer Science and Business Media LLC
Date: 31-07-2011
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2007
Publisher: ACM
Date: 03-11-2014
Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/11759966_168
Publisher: Springer Science and Business Media LLC
Date: 20-06-2007
Publisher: ACM
Date: 24-10-2016
Publisher: Springer Science and Business Media LLC
Date: 30-03-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Elsevier BV
Date: 2019
Publisher: Springer International Publishing
Date: 2019
Publisher: IEEE
Date: 12-2008
Publisher: IEEE
Date: 11-2018
Publisher: Springer International Publishing
Date: 2017
Publisher: Springer International Publishing
Date: 2014
Publisher: IEEE
Date: 06-2007
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2017
Publisher: Springer Berlin Heidelberg
Date: 2005
DOI: 10.1007/B104566
Publisher: No publisher found
Date: 2009
Publisher: Springer Science and Business Media LLC
Date: 08-07-2016
Publisher: Elsevier BV
Date: 10-2023
Publisher: Elsevier BV
Date: 2018
Publisher: Springer International Publishing
Date: 2018
Publisher: Springer International Publishing
Date: 2014
Publisher: IEEE
Date: 2008
Publisher: Springer International Publishing
Date: 2018
Publisher: IEEE
Date: 09-2013
Publisher: Springer Berlin Heidelberg
Date: 2008
Publisher: Springer International Publishing
Date: 2015
Publisher: Springer International Publishing
Date: 2017
Publisher: Elsevier BV
Date: 02-2013
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: Elsevier BV
Date: 09-2011
Publisher: IEEE
Date: 2004
Publisher: Springer Science and Business Media LLC
Date: 26-04-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Springer Berlin Heidelberg
Date: 2013
Publisher: IEEE
Date: 07-2019
Publisher: IEEE
Date: 2004
Publisher: IEEE Comput. Soc
Date: 2004
Publisher: Inderscience Publishers
Date: 2007
Publisher: IEEE
Date: 06-2007
Publisher: Springer Berlin Heidelberg
Date: 2005
DOI: 10.1007/11430919_91
Publisher: Association for Computing Machinery (ACM)
Date: 30-06-2017
DOI: 10.1145/3035967
Abstract: With recent advances in radio-frequency identification (RFID), wireless sensor networks, and Web services, physical things are becoming an integral part of the emerging ubiquitous Web. Finding correlations among ubiquitous things is a crucial prerequisite for many important applications such as things search, discovery, classification, recommendation, and composition. This article presents DisCor-T , a novel graph-based approach for discovering underlying connections of things via mining the rich content embodied in the human-thing interactions in terms of user, temporal, and spatial information. We model this various information using two graphs, namely a spatio-temporal graph and a social graph. Then, random walk with restart (RWR) is applied to find proximities among things, and a relational graph of things (RGT) indicating implicit correlations of things is learned. The correlation analysis lays a solid foundation contributing to improved effectiveness in things management and analytics. To demonstrate the utility of the proposed approach, we develop a flexible feature-based classification framework on top of RGT and perform a systematic case study. Our evaluation exhibits the strength and feasibility of the proposed approach.
Publisher: Springer International Publishing
Date: 2017
Publisher: ACM
Date: 03-07-2014
Publisher: Springer International Publishing
Date: 2013
Publisher: Informa UK Limited
Date: 10-2012
Publisher: IEEE
Date: 06-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2023
Publisher: ACM
Date: 2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2008
DOI: 10.1109/MC.2008.386
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: IGI Global
Date: 2006
DOI: 10.4018/IJITWE
Publisher: Inderscience Publishers
Date: 2011
Publisher: Springer International Publishing
Date: 2014
Publisher: IEEE
Date: 10-2009
Publisher: ACM
Date: 20-09-2004
Publisher: ACM
Date: 22-10-2013
Publisher: Elsevier BV
Date: 08-2022
Publisher: IEEE
Date: 12-2013
DOI: 10.1109/ICDM.2013.87
Publisher: Global Vision Press
Date: 30-04-2016
Publisher: Springer Science and Business Media LLC
Date: 09-03-2018
Publisher: Springer Science and Business Media LLC
Date: 04-09-2018
Location: Australia
No related grants have been discovered for Sandra Paula Villacorta Chambi.