Multi-objective Genetic Algorithm for Association Rule Mining Using a Homogeneous Dedicated Cluster of Workstations

Dehuri, Satchidananda; Jagadev, Alok Kumar; Ghosh, Ashish; Mall, Rajib

doi:10.3844/ajassp.2006.2086.2095

Cited by 43 publications

(34 citation statements)

References 21 publications

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“…The authors in [11] proposed a fast and scalable MOGA for mining QAR from large datasets using parallel processing and a homogeneous network of workstations. The confidence, comprehensibility and interest of QAR were the target objectives.…”

Section: Related Workmentioning

confidence: 99%

Improving a multi-objective evolutionary algorithm to discover quantitative association rules

et al. 2015

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This work aims at correcting flaws existing in multi-objective evolutionary schemes to discover quantitative association rules, specifically those based on the wellknown non-dominated sorting genetic algorithm-II (NSGA-II). In particular, a methodology is proposed to find the most suitable configurations based on the set of objectives to optimize and distance measures to rank the non-dominated solutions. First, several quality measures are analyzed to select the best set of them to be optimized. Furthermore, different strate-gies are applied to replace the crowding distance used by NSGA-II to sort the solutions for each Pareto-front since such distance is not suitable for handling many-objective problems. The proposed enhancements have been integrated into the multi-objective algorithm called MOQAR. Several experiments have been carried out to assess the algorithm's performance by using different configuration settings, and the best ones have been compared to other existing algorithms. The results obtained show a remarkable performance of MOQAR in terms of quality measures.

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Section: Related Workmentioning

confidence: 99%

Improving a multi-objective evolutionary algorithm to discover quantitative association rules

et al. 2015

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“…Therefore, it makes modeling the HTML structure into a DOM tree becoming an essential aspect. For that purpose, the need of an artificial intelligence is required in the formulation of its algorithm (Dehuri et al, 2006;Mamat et al, 2006;Sleit et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Proposing the new Algorithm and Technique Development for Integrating Web Table Extraction and Building a Mashup

Gultom

Sari²,

Budiardjo³

2011

Journal of Computer Science

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Problem statement: Nowadays, various types of data in web table can be easily extracted from the Internet, although not all of web tables are relevant to the users. As we may know, most web pages are in unstructured HTML format, making web table extraction process very time consuming and costly. HTML format only focuses on the presentation, not based on the database system. Therefore, users need a tool in dealing with that process. Approach: This research proposed an approach for implementing web table extraction and making a Mashup from HTML web pages using Xtractorz application. It is also discussed on how to collaborate and integrate a web table extraction process in the stage of building a Mashup, i.e., Data Retrieval, Data Source Modeling, Data Cleaning/ Filtering, Data Integration and Data Visualization. The main issue lies in stage of data modeling creation, in which Xtractorz must be able to automatically render Document Object Model (DOM) tree in accordance to HTML tag or code of the web page from which the table is extracted. To overcome that, the Xtractorz is equipped with algorithm and rules so it can enable to specifically analyze the HTML tags and to extract the data into a new table format. The algorithm is created by using recursive technique within a user-friendly GUI of Xtractorz. Results: The approach was evaluated by conducting experiment using Xtractorz and other similar applications, such as RoboMaker and Karma. The result of experiment showed that Xtractorz is more efficient in completing the experiment tasks, since Xtractorz has fewer steps to complete the whole tasks. Conclusion: Xtractorz can give a positive contribution in terms of algorithm technique and a new approach method to web table extraction process and making a Mashup, where the core algorithm can extracts web data tables using recursive technique while rendering the DOM tree model automatically.

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“…The past researches of the new encoding method are referred in various authors. Patvichaichod (2011), Nazif and, Sarabian and Lee (2010), Al Rahedi and Atoum (2009), Yang et al (2008), Kangrang and Chaleeraktrakoon (2007) and Dehuri et al (2006).…”

Section: Introductionmentioning

confidence: 99%

Application of Hybrid Encoding Genetic Algorithm on Pickup and Delivery Traveling Salesman Problem with Traffic Conditions

Patvichaichod¹

2011

Journal of Computer Science

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Problem statement:This study deals with the pickup and delivery traveling salesman problem with traffic conditions (PDTSPTW), an extension of the pickup and delivery traveling salesman problem (PDTSP) where each customer to be served is associated with two quantities of product to be collected and delivered. Almost PDTSP problems uses distance between each point of customers as Euclidean Distance and are not concerned with other parameters to find minimal cost. Approach: The PDTSPTC concerns more parameters, such as street network and vehicle speed, which results it closer to the real world condition. The study also proposes the developed genetic algorithm called "Hybrid Encoding Genetic Algorithm (HEGA)". The concept is to combine binary encoding and integer encoding together, causing the in complexity of the algorithm structure and the ease of implementation. Results: the HEGA can save the travel cost about 26-57%. It is obviously seen that HEGA in the PDTSPTC test problems result the fast convergence that is about 12-43% and in all, the computational time is under 6 seconds. Conclusion: The HEGA performs quite well when testing a test problem. Computation times are small in all case. The PDTSPTC is closer to real-world conditions than PDTSP. This problem can be applied in logistics immediately if the distance of streets, traffic conditions (average vehicle speed in each street) and vehicle conditions (fuel consumption rate and vehicle capacity) are known.

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Multi-objective Genetic Algorithm for Association Rule Mining Using a Homogeneous Dedicated Cluster of Workstations

Cited by 43 publications

References 21 publications

Improving a multi-objective evolutionary algorithm to discover quantitative association rules

Improving a multi-objective evolutionary algorithm to discover quantitative association rules

Proposing the new Algorithm and Technique Development for Integrating Web Table Extraction and Building a Mashup

Application of Hybrid Encoding Genetic Algorithm on Pickup and Delivery Traveling Salesman Problem with Traffic Conditions

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