Rawat, Sandeep Singh; Rajamani, Lakshmi
August 2010
International Journal of Computer Science & Information Technolo;Aug2010, Vol. 2 Issue 4, p28
Academic Journal
Most of the organizations put information on the web because they want it to be seen by the world. Their goal is to have visitors come to the site, feel comfortable and stay a while and try to know completely about the running organization. As educational system increasingly requires data mining, the opportunity arises to mine the resulting large amounts of student information for hidden useful information (patterns like rule, clustering, and classification, etc). The education domain offers ground for many interesting and challenging data mining applications like astronomy, chemistry, engineering, climate studies, geology, oceanography, ecology, physics, biology, health sciences and computer science. Collecting the interesting patterns using the required interestingness measures, which help us in discovering the sophisticated patterns that are ultimately used for developing the site. We study the application of data mining to educational log data collected from Guru Nanak Institute of Technology, Ibrahimpatnam, India. We have proposed a custom-built apriori algorithm to find the effective pattern analysis. Finally, analyzing web logs for usage and access trends can not only provide important information to web site developers and administrators, but also help in creating adaptive web sites.


Related Articles

  • Constraining and summarizing association rules in medical data. Ordonez, Carlos; Ezquerra, Norberto; Santana, Cesar A. // Knowledge & Information Systems;Mar2006, Vol. 9 Issue 3, p1 

    Association rules are a data mining technique used to discover frequent patterns in a data set. In this work, association rules are used in the medical domain, where data sets are generally high dimensional and small. The chief disadvantage about mining association rules in a high dimensional...

  • AN EFFICIENT PROCEDURE FOR MINING STATISTICALLY SIGNIFICANT FREQUENT ITEMSETS. StaniĊĦic, Predrag; Tomovic, Savo // Publications de l'Institut Mathematique;2010, Vol. 87 Issue 101, p109 

    We suggest the original procedure for frequent itemsets generation, which is more efficient than the appropriate procedure of the well known Apriori algorithm. The correctness of the procedure is based on a special structure called Rymon tree. For its implementation, we suggest a modified...

  • A New Method for Preserving Privacy in Quantitative Association Rules using Genetic Algorithm. SathiyaPriya, K.; Sudha Sadasivam, G.; Karthikeyan, V. B. // International Journal of Computer Applications;2012, Vol. 60, p12 

    Data mining is the process of extracting hidden patterns from data. With the explosion of data, data mining is essential to extract useful information. Association rule mining is a method for finding correlation among large set of data items. A rule is characterized as sensitive if its...

  • Learn the knowledge. Garfoot, Annie // IT Training;Jun2004, p26 

    The article presents many definitions of knowledge management. But for most organisations, knowledge management can be defined as the process through which they generate value from their intellectual property and from their knowledge-based assets, such as customer lists, business plans,...

  • Implementing Association Rules Technique to Predict Student Result based on Historical Data. Aziz, Azwa Abdul; Jusoh, Julaily Aida // Annual International Conference on Infocomm Technologies in Comp;2012, p50 

    University or Higher Learning Institution is a platform to train students in specific domain area that will become an asset for a country. One of the critical issues in University is to avoid dropout students. Educational Data Mining (EDM) is an emergent discipline in developing methods to...

  • A CONCEPT BASED APPROACH OF RARE ASSOCIATION RULE MINING FROM EDUCATION DATA. PAREEK, ASTHA; GUPTA, MANISH // International Journal of Research in Computer Application & Mana;Sep2012, Vol. 2 Issue 9, p46 

    Data mining is the process of discovering useful knowledge in the form of patterns from the data. Association rule mining is an important knowledge discovery technique in the field of data mining. It involves finding interesting associations between the sets of objects in a transactional...

  • Performance Analysis of Genetic Algorithm for Mining Association Rules. Indira, K.; Kanmani, S. // International Journal of Computer Science Issues (IJCSI);Mar2012, Vol. 9 Issue 2, p368 

    Association rule (AR) mining is a data mining task that attempts to discover interesting patterns or relationships between data in large databases. Genetic algorithm (GA) based on evolution principles has found its strong base in mining ARs. This paper analyzes the performance of GA in Mining...

  • A hybrid multi-group approach for privacy-preserving data mining. Teng, Zhouxuan; Du, Wenliang // Knowledge & Information Systems;May2009, Vol. 19 Issue 2, p133 

    In this paper, we propose a hybrid multi-group approach for privacy preserving data mining. We make two contributions in this paper. First, we propose a hybrid approach. Previous work has used either the randomization approach or the secure multi-party computation (SMC) approach. However, these...

  • An Agenda- and Justification-Based Framework for Discovery Systems. Livingston, Gary R.; Rosenberg, John M.; Buchanan, Bruce G. // Knowledge & Information Systems;Apr2003, Vol. 5 Issue 2, p133 

    We propose and evaluate an agenda- and justification-based architecture for discovery systems that selects the next tasks to perform, as well as heuristics for use in discovery systems. This framework has many desirable properties: (1) it selects its own tasks to perform based upon how plausible...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics