E-learning process has been widely used in university campus and educational institutions are playing vital role to enhance the skill set of students. Modern E-learning done by many electronic devices, such as smartphones, Tabs, and so on, on existing E-learning tools is insufficient to achieve the purpose of online training of education. This paper presents a survey of online e-Learning authoring tools for creating and integrating reusable e-learning tool for generation and enhancing existing learning resources with them. The work concentrates on evaluation of the existing e-learning tools a, and authoring tools that have shown good performance in the past for online learners. This survey work takes more than 20 online tools that deal with the educational sector mechanism, for the purpose of observations, and the outcome were analyzed. The findings of this paper are the main reason for developing a new tool, and it shows that educators can enhance existing learning resources by adding assessment resources, if suitable authoring tools are provided. Finally, the different factors that assure the reusability of the created new e-learning tool has been analysed in this paper.E-learning environment is a guide for both students and tutorial management system. The useful on the e-learning system for apart from students and distance learning students. The purpose of using e-learning environment for online education system, developed in data mining for more number of clustering servers and resource chain has been good.

Abstract - Cloud computing [11] is a tremendous growth in every years and it can be utility the computing and large storage capability to the public users. The data owner can store the data in the cloud server is called data outsourcing and then the cloud data access for public users through the cloud server. The outsourced data are contains sensitive privacy information and it can be encrypted before uploaded to the cloud server and then the search user can access to the data through the cloud server is some difficulty of searching over the encrypted data in cloud. In this paper address this problem by developed the fine-grained multi-keyword search scheme over encrypted data in the cloud. There are three contribution of this paper. First one is, to provided relevance scores and preference factors upon keywords which enabled the precise keyword search. Second one is, to developed a complicated logic search the mixed AND, OR and NO operations of multi-keyword search scheme. And finally, auxiliary employ the classified subdictionaries technique to accomplish the index building, trapdoor generating and query. By using this experiments to the real-world dataset, so easily retrieve the result from dataset.

- Let R be a commutative ring with unity. In this paper we introduce and study Fuzzy Quasi regular ring as generalizations of (ordinary) Quasi regular ring. We give some basic properties about these concepts.

- Recommendation system plays a major role in web mining and it is applied to many applications such as ecommerce, e-government and e-library. The key challenges of recommendation system is to recommend the users based on their interest among more visitors and huge information. To make this challenge effective, there is a need for clustering algorithm to handle the data. Hence, this research focused on designing effective clustering algorithm to apply it in ecommerce applications. The grey wolf optimization based clustering is proposed to make an efficient clustering method for grouping the users based on their interest. To find the effective clustering, proposed a grey wolf optimization based fuzzy clustering algorithm, and made a comparison on Fuzzy C Means (FCM) based Genetic Algorithm (GA), Entropy based FCM and Improved Genetic FCM (FCM-GA). The experimental results proves that it performs better than traditional algorithms, at the same time the quality is improved.

- Automated log analysis has been a dominant subject area of interest to both industry and academics alike. The heterogeneous nature of system logs, the disparate sources of logs (Infrastructure, Networks, Databases and Applications) and their underlying structure & formats makes the challenge harder. In this paper I present the less frequently used document clustering techniques to dynamically organize real time log events (e.g. Errors, warnings) to specific categories that are pre-built from a corpus of log archives. This kind of syntactic log categorization can be exploited for automatic log monitoring, priority flagging and dynamic solution recommendation systems. I propose practical strategies to cluster and correlate high volume log archives and high velocity real time log events; both in terms of solution quality and computational efficiency. First I compare two traditional partitional document clustering approaches to categorize high dimensional log corpus. In order to select a suitable model for our problem, Entropy, Purity and Silhouette Index are used to evaluate these different learning approaches. Then I propose computationally efficient approaches to generate vector space model for the real time log events. Then to dynamically relate them to the categories from the corpus, I suggest the use of a combination of critical distance measure and least distance approach. In addition, I introduce and evaluate three different critical distance measures to ascertain if the real time event belongs to a totally new category that is unobserved in the corpus.

— The advancement in Information Technology (IT) has assisted in inculcating the three Nigeria major languages in text-based application such as text mining, information retrieval and natural language processing. The interest of this paper is the Igbo language, which uses compounding as a common type of word formation and as well has many vocabularies of compound words. The issues of collocation, word ordering and compounding play high role in Igbo language. The ambiguity in dealing with these compound words has made the representation of Igbo language text document very difficult because this cannot be addressed using the most common and standard approach of the Bag-Of-Words (BOW) model of text representation, which ignores the word order and relation. However, this cause for a concern and the need to develop an improved model to capture this situation. This paper presents the analysis of Igbo language text document, considering its compounding nature and describes its representation with the Word-based N-gram model to properly prepare it for any text-based application. The result shows that Bigram and Trigram n-gram text representation models provide more semantic information as well addresses the issues of compounding, word ordering and collocations which are the major language peculiarities in Igbo. They are likely to give better performance when used in any Igbo textbased system.

— In modern days, assessment methods are designed in online to enhance its effectiveness among students as well as staff members of the institution. The Learning Management System (LMS) plays a vital role of conducting the assessments through online. This paper discusses the need to have an efficient and systematic usage of LMS, in particular Moodle, for improving the existing assessment methods of mathematics curriculum. Also, various question types which are used to overcome the disadvantages of classical assessment methods, are highlighted and described in detail. The working methodology of such question types in Moodle is explained by using the properties of functions and cyclic groups.

: Privacy preservation of data mining has developed as a widespread study area in order to secure the private information over the network. Privacy preserving methods like L-diversity, Randomization, Data distribution, and Kanonymity have been recommended in directive to perform privacy preservation of data mining. The Privacy preservation of data mining (PPDM) methods protects data by masking or by erasing the original sensitive one to be masked. The private data can be preserved efficiently using cryptographic techniques .In our work we propose a modified two fish algorithm with 256 keys as a cryptographic approach to provide security for PPDM.

— In modern days, assessment methods are designed in online to enhance its effectiveness among students as well as staff members of the institution. The Learning Management System (LMS) plays a vital role of conducting the assessments through online. This paper discusses the need to have an efficient and systematic usage of LMS, in particular Moodle, for improving the existing assessment methods of mathematics curriculum. Also, various question types which are used to overcome the disadvantages of classical assessment methods, are highlighted and described in detail. The working methodology of such question types in Moodle is explained by using the properties of functions and cyclic groups.