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629 results on '"Pardede, Eric"'

5. Scalable Teacher Forcing Network for Semi-Supervised Large Scale Data Streams

Author

Pratama, Mahardhika, Za'in, Choiru, Lughofer, Edwin, Pardede, Eric, and Rahayu, Dwi A. P.

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

The large-scale data stream problem refers to high-speed information flow which cannot be processed in scalable manner under a traditional computing platform. This problem also imposes expensive labelling cost making the deployment of fully supervised algorithms unfeasible. On the other hand, the problem of semi-supervised large-scale data streams is little explored in the literature because most works are designed in the traditional single-node computing environments while also being fully supervised approaches. This paper offers Weakly Supervised Scalable Teacher Forcing Network (WeScatterNet) to cope with the scarcity of labelled samples and the large-scale data streams simultaneously. WeScatterNet is crafted under distributed computing platform of Apache Spark with a data-free model fusion strategy for model compression after parallel computing stage. It features an open network structure to address the global and local drift problems while integrating a data augmentation, annotation and auto-correction ($DA^3$) method for handling partially labelled data streams. The performance of WeScatterNet is numerically evaluated in the six large-scale data stream problems with only $25\%$ label proportions. It shows highly competitive performance even if compared with fully supervised learners with $100\%$ label proportions., Comment: This paper has been accepted for publication in Information Sciences

Published
2021

8. Evolving Large-Scale Data Stream Analytics based on Scalable PANFIS

Author

Pratama, Mahardhika, Za'in, Choiru, and Pardede, Eric

Subjects
Computer Science - Artificial Intelligence, Computer Science - Databases
Abstract

Many distributed machine learning frameworks have recently been built to speed up the large-scale data learning process. However, most distributed machine learning used in these frameworks still uses an offline algorithm model which cannot cope with the data stream problems. In fact, large-scale data are mostly generated by the non-stationary data stream where its pattern evolves over time. To address this problem, we propose a novel Evolving Large-scale Data Stream Analytics framework based on a Scalable Parsimonious Network based on Fuzzy Inference System (Scalable PANFIS), where the PANFIS evolving algorithm is distributed over the worker nodes in the cloud to learn large-scale data stream. Scalable PANFIS framework incorporates the active learning (AL) strategy and two model fusion methods. The AL accelerates the distributed learning process to generate an initial evolving large-scale data stream model (initial model), whereas the two model fusion methods aggregate an initial model to generate the final model. The final model represents the update of current large-scale data knowledge which can be used to infer future data. Extensive experiments on this framework are validated by measuring the accuracy and running time of four combinations of Scalable PANFIS and other Spark-based built in algorithms. The results indicate that Scalable PANFIS with AL improves the training time to be almost two times faster than Scalable PANFIS without AL. The results also show both rule merging and the voting mechanisms yield similar accuracy in general among Scalable PANFIS algorithms and they are generally better than Spark-based algorithms. In terms of running time, the Scalable PANFIS training time outperforms all Spark-based algorithms when classifying numerous benchmark datasets., Comment: 20 pages, 5 figures

Published
2018

9. Big Data Analytic based on Scalable PANFIS for RFID Localization

Author

Za'in, Choiru, Pratama, Mahardhika, Ashfahani, Andri, Pardede, Eric, and Sheng, Huang

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

RFID technology has gained popularity to address localization problem in the manufacturing shopfloor due to its affordability and easiness in deployment. This technology is used to track the manufacturing object location to increase the production efficiency. However, the data used for localization task is not easy to analyze because it is generated from the non-stationary environment. It also continuously arrive over time and yields the large-volume of data. Therefore, an advanced big data analytic is required to overcome this problem. We propose a distributed big data analytic framework based on PANFIS (Scalable PANFIS), where PANFIS is an evolving algorithm which has capability to learn data stream in the single pass mode. Scalable PANFIS can learn big data stream by processing many chunks/partitions of data stream. Scalable PANFIS is also equipped with rule structure merging to eliminate the redundancy among rules. Scalable PANFIS is validated by measuring its performance against single PANFIS and other Spark scalable machine learning algorithms. The result shows that Scalable PANFIS performs running time more than 20 times faster than single PANFIS. The rule merging process in Scalable PANFIS shows that there is no significant reduction of accuracy in classification task with 96.67 percent of accuracy in comparison with single PANFIS of 98.71 percent. Scalable PANFIS also generally outperforms some Spark MLib machine learnings to classify RFID data with the comparable speed in running time., Comment: 7 pages and 3 figures, IEEE SMC

Published
2018

12. Graph-Based Semantic Query Optimization for Intensional XML Data

Author

Alrefae, Abdullah, Cao, Jinli, Pardede, Eric, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, Hussain, Farookh Khadeer, editor, and Ikeda, Makoto, editor

Published
2020
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16. A Framework for Cleaning Streaming Data in Healthcare: A Context and User-Supported Approach.

Author

Alotaibi, Obaid, Tomy, Sarath, and Pardede, Eric

Subjects
GENERATIVE artificial intelligence, DATA scrubbing, MISSING data (Statistics), DATA quality, DECISION making
Abstract

Nowadays, ubiquitous technology makes life easier, especially devices that use the internet (IoT). IoT devices have been used to generate data in various domains, including healthcare, industry, and education. However, there are often problems with this generated data such as missing values, duplication, and data errors, which can significantly affect data analysis results and lead to inaccurate decision making. Enhancing the quality of real-time data streams has become a challenging task as it is crucial for better decisions. In this paper, we propose a framework to improve the quality of a real-time data stream by considering different aspects, including context-awareness. The proposed framework tackles several issues in the data stream, including duplicated data, missing values, and outliers to improve data quality. The proposed framework also provides recommendations on appropriate data cleaning techniques to the user to help improve data quality in real time. Also, the data quality assessment is included in the proposed framework to provide insight to the user about the data stream quality for better decisions. We present a prototype to examine the concept of the proposed framework. We use a dataset that is collected in healthcare and process these data using a case study. The effectiveness of the proposed framework is verified by the ability to detect and repair stream data quality issues in selected context and to provide a recommended context and data cleaning techniques to the expert for better decision making in providing healthcare advice to the patient. We evaluate our proposed framework by comparing the proposed framework against previous works. [ABSTRACT FROM AUTHOR]

Published
2024
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20. Graph Database Indexing Layer for Logic-Based Tree Pattern Matching Over Intensional XML Document Databases

Author

Alrefae, Abdullah, Cao, Jinli, Pardede, Eric, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Misra, Sanjay, editor, Stankova, Elena, editor, Torre, Carmelo M., editor, Rocha, Ana Maria A.C., editor, Taniar, David, editor, Apduhan, Bernady O., editor, Tarantino, Eufemia, editor, and Ryu, Yeonseung, editor

Published
2018
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21. Course Map: A Career-Driven Course Planning Tool

Author

Tomy, Sarath, Pardede, Eric, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Misra, Sanjay, editor, Stankova, Elena, editor, Torre, Carmelo M., editor, Rocha, Ana Maria A.C., editor, Taniar, David, editor, Apduhan, Bernady O., editor, Tarantino, Eufemia, editor, and Ryu, Yeonseung, editor

Published
2018
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22. Dynamic Transitions of States for Context-Sensitive Access Control Decision

Author

Kayes, A. S. M., Rahayu, Wenny, Dillon, Tharam, Mahbub, Syed, Pardede, Eric, Chang, Elizabeth, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Hacid, Hakim, editor, Cellary, Wojciech, editor, Wang, Hua, editor, Paik, Hye-Young, editor, and Zhou, Rui, editor

Published
2018
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30. The Use of Modern Pedagogical Techniques When Introducing Information Technology Students to Entrepreneurship

Author

Pardede, Eric

Abstract

This paper describes the design of teaching and learning activities (TLAs) in an entrepreneurship subject offered to Information Technology (IT) students. We describe the challenges that we have encountered. Within one teaching semester, the students are expected to achieve a high level of applied knowledge in an area where they have little theoretical knowledge. We introduce TLAs that are not common in an IT curriculum. These TLAs use experience as the basis of knowledge, collaboration as the focus of learning and a reflective approach to structuring knowledge. We identify our rationale for using these new TLAs to achieve the intended learning outcomes for the subject based on the existing literature. To evaluate the effectiveness of our design, we conducted an annual survey. The results of the survey support our design. Student feedback surveys and end of course assessment results indicate that the new TLAs have enhanced the students' learning.

Published
2015
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31. A feature-based model selection approach using web traffic for tourism data

Author

Karim, Ali Abdul, Pardede, Eric, and Mann, Scott

Abstract

The increased volume of accessible internet data creates an opportunity for researchers and practitioners to improve time series forecasting for many indicators. In our study, we assess the value of web traffic data in forecasting the number of short-term visitors travelling to Australia. We propose a feature-based model selection framework which combines random forest with feature ranking process to select the best performing model using limited and informative number of features extracted from web traffic data. The data was obtained for several tourist attraction and tourism information websites that could be visited by potential tourists to find out more about their destinations. The results of random forest models were evaluated over 3- and 12-month forecasting horizon. Features from web traffic data appears in the final model for short term forecasting. Further, the model with additional data performs better on unseen data post the COVID19 pandemic. Our study shows that web traffic data adds value to tourism forecasting and can assist tourist destination site managers and decision makers in forming timely decisions to prepare for changes in tourism demand.

Published
2024
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37. A Data-Driven Approach toward Building Dynamic Ontology

Author

Fudholi, Dhomas Hatta, Rahayu, Wenny, Pardede, Eric, Hendrik, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Mustofa, Khabib, editor, Neuhold, Erich J., editor, Tjoa, A Min, editor, Weippl, Edgar, editor, and You, Ilsun, editor

Published
2013
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38. XML Query Adaptation as Schema Evolves

Author

Polák, Marek, Mlýnková, Irena, Pardede, Eric, Linger, Henry, editor, Fisher, Julie, editor, Barnden, Andrew, editor, Barry, Chris, editor, Lang, Michael, editor, and Schneider, Christoph, editor

Published
2013
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39. The Development of XML Stored Procedures in XML Enabled Databases

Author

Alahmari, Fahad, Pardede, Eric, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Wang, Liwei, editor, Jiang, Jingjue, editor, Lu, Jiaheng, editor, Hong, Liang, editor, and Liu, Bin, editor

Published
2012
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42. Semantic Transformation Approach with Schema Constraints for XPath Query Axes

Author

Le, Dung Xuan Thi, Bressan, Stephane, Pardede, Eric, Rahayu, Wenny, Taniar, David, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Chen, Lei, editor, Triantafillou, Peter, editor, and Suel, Torsten, editor

Published
2010
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43. A Utilization of Schema Constraints to Transform Predicates in XPath Query

Author

Thi Le, Dung Xuan, Bressan, Stéphane, Pardede, Eric, Taniar, David, Rahayu, Wenny, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Bringas, Pablo García, editor, Hameurlain, Abdelkader, editor, and Quirchmayr, Gerald, editor

Published
2010
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46. On Using Semantic Transformation Algorithms for XML Safe Update

Author

Le, Dung Xuan Thi, Pardede, Eric, van der Aalst, Will, Series editor, Mylopoulos, John, Series editor, Sadeh, Norman M., Series editor, Shaw, Michael J., Series editor, Szyperski, Clemens, Series editor, Yang, Jianhua, editor, Ginige, Athula, editor, Mayr, Heinrich C., editor, and Kutsche, Ralf-D., editor

Published
2009
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47. On Developing Methods for XML Databases

Author

Do, William V., Pardede, Eric, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Laganà, Antonio, editor, Taniar, David, editor, Mun, Youngsong, editor, and Gavrilova, Marina L., editor

Published
2008
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48. SQL/XML Performance Analysis of Parent/Ancestor Queries

Author

Pardede, Eric, Rahayu, J. Wenny, Taniar, David, Kaur Aujla, Ramanpreet, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Laganà, Antonio, editor, Taniar, David, editor, Mun, Youngsong, editor, and Gavrilova, Marina L., editor

Published
2008
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49. Performance Analysis of Child/Descendant Queries in an XML-Enabled Database

Author

Pardede, Eric, Rahayu, J. Wenny, Taniar, David, Aujla, Ramanpreet Kaur, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Gervasi, Osvaldo, editor, and Gavrilova, Marina L., editor

Published
2007
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50. Towards Performance Efficiency in Safe XML Update

Author

Le, Dung Xuan Thi, Pardede, Eric, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Benatallah, Boualem, editor, Casati, Fabio, editor, Georgakopoulos, Dimitrios, editor, Bartolini, Claudio, editor, Sadiq, Wasim, editor, and Godart, Claude, editor

Published
2007
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