Asian Transactions on Computers

Volume: 02, Issue: 01, March 2012
ISSN 2221-4275

Title: An Opportunity Cost Approach for Measuring Performance of An Intelligent Knowledge Based Search Assistant
Authors: Md. Mahbubul Alam Joarder, Khaled Mahmud, and Bulbul Ahamed
Paper ID: ATC-30228014
Pages: 1 - 4
Abstract: The Web has myriad of useful information, but its dynamic, unstructured nature makes them difficult to locate the desired information. A general-purpose search engine, such as Google or AltaVista usually generates thousands of hits, many of them irrelevant to the user query. A knowledge based search assistant is developed which reduces the time and cost of information accumulating of common interest groups. When the users from a common network search on similar topics then an intelligent agent minimize the searching effort of a user by utilizing the previous experience of the users they have gathered from their surfing behaviours. Additionally the agent incrementally updates its database by analyzing its perception, which gradually increases its recall rate. A search assistant that accumulates knowledge from user activity and gathers information would provide a convenient searching environment with minimum effort within shortest possible time.

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Title: Pattern Discovery Analysis On Agricultural Corps Of Eastern Anatolian Region By Priori Algorithm
Authors: Ahmet CINAR & Fatih TOPALOGLU
Paper ID: ATC-80231019
Pages: 5 - 10
Abstract: There are very critical data in the decision phases, and the effects of the results are proportional to the accuracy of such data. Data mining can be defined as a series of techniques and concepts that allow us to extract previously unknown and useful knowledge from data in a dynamic process for the decision phases and make forecasts and future plans [3]. In this study, the pattern discovery analysis was performed for the agricultural corps of the Eastern Anatolian Region using the Data Mining techniques. The Apriori algorithm which is one of the association rule extraction algorithms in Data Mining was used for this analysis. The application data was interpreted using the software prepared and applied on the provinces, Malatya, Erzurum, and Igdir selected as the model. Then, the Apriori algorithm was applied on the results obtained from such transactions and thus, the agricultural crop pattern discovery analysis was realized for the Eastern Anatolian Region.

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Title: Evaluation of Technical Factors in Distance Learning with respect to Open Source LMS
Authors: Saleh Alshomrani
Paper ID: ATC-40232015
Pages: 11 - 17
Abstract: Market monopolies are one of the biggest threats for educational sector [1]. To utilize internet resources and abide from market monopolies open source distance learning management systems are addressing the technical factors in providing perfect solution for educational sector. Higher Education institution face challenges to make suitable selection which best fit to their requirements, as well examining the effectiveness and evaluation of open source LMS’s are a complex issue. In our study the main objective is to overcome the difficulties by comparing best available Open Source (OSC) LMS’s and recommend a modern open source distance learning system considering enhancement in technology, recent trends, quality assurance of instructional process and it’s outputs according to targeted goals, as well educational sector can customize, enhance functionalities and redistribute it. In this study literature is reviewed and as per our finding not much research has been already conducted about comparison of open source software in distance learning. This paper compared and analysed different open source distance learning systems and extract the some important recommendations and conclusions.

Full Text: PDF (422 KB)