Informatics Publishing Limited

G. Maragatham ¹, M. Lakshmi ¹

Affiliations
1 Computer Science & Engineering Department, Sathyabama University, Chennai-600119, IN

Abstract

The main task of Association rule mining is to find correlations among the set of data items present in the database. Rule interestingness is mainly measured by means of support and confidence. There exists various other measures for depicting the rule interestingness such as Lift, Conviction, Drift etc. Apart from these, there also exists diversity measures which are applied on Summaries. Much little work was done on association rule mining using diversity measures. This article suggests the use of predictive apriori approach for selecting the best dataset based on the application of diversity measures on the association rules generated. The experimental results are encouraging.

Keywords

Association Rule, Diveristy Measures, Predictive Apriori Algorithm, Rule Interestingness.

Full Text

     

Venkatesan Ganesan ¹, G. Maragatham ², U. S. Lavanya ¹

Affiliations
1 TCS, Rajiv Gandhi Salai, Taramani, Chennai - 600113, Tamil Nadu, IN
2 SRM University, Department of Information Technology, Kattangulathur, Chennai - 603203, Tamil Nadu, IN

Abstract

Objectives: In this modern era, technologies play a crucial role in determining a success of an industry, since the market is more volatile, understanding the customer base and forecasting of demand itself is complex, on top of that fulfilling the forecasted demand by meeting all the supply chain bottle necks is much more complex without better IT and coordination between the various business partners. This has pushed the companies to address the gap through various software application and utilizing the eminent data pockets are very important. In order to support this challenge, as a part of the review the impact of IoT in area of Supply chain Management such as with respect to Transportation is discussed. Methods: An analysis has been done in various industries and identified factors influencing the supply chain efficiency in a complex business environment. This is theoretical study is done for effective Business functionality in relating the technological innovations that is the IoT. Findings: Based on the survey conducted, the parameters that could play crucial role in the business operations are identified. In this IT driven world, utilizing the crucial information from the date and gaining the competitive advantage help the business to meet growing market to serve the customer better. Gartner says a thirty-fold increase in Internet-connected physical devices by the year 2020 will "significantly alter how the supply chain operates. Before reaching the customer, products should cross the multiple business partners from manufacturers, suppliers, the Distribution Centers, retailer, and then customer. So it is vital for the business to provide the visibility of product in each stage of Supply chain to have right information about the identity, location, and other tracking information. This study attempts to bring the node of IoT in Transportation. Also, the study highlights the IoT trigger points for tracking the accurate information of the goods that are connected to a common platform. The factors influencing the supply chain management is discussed in section 4. Applications/Improvements: As IoT is in the infant stage, with respect to the global business environment, an attempt have been made to study its impact on the Mutli-modal decision making scenario. This framework would be much useful in the Business environment of how to improve the business to a better scale.

Keywords

Distribution Centers, IT, IoT, Multi-modal Transportation, Supply Chain Management.

Full Text