Abstract: The rise of Social Media such as E- Commerce and social networks has interest in sentiment analysis. With the rapid increase of reviews, ratings, recommendations and other forms of online expression, online opinion is nothing but virtual currency for businesses looking to market their products, identify new opportunities and manage their reputations. Opinions of product express the ideas, interests and emotions about particular product for the world. With the increasing use of internet sources for all needs of life and peoples choices on how to send their life around computers new organizations on the web such as online networks, forums important source of and blogs are the new meeting point for the people. The difficulty comes out by the personalized design and the size of the blogosphere; every blog has a different structure which prevents us to find the information or related data with several tracking from one to another the Aim of this paper is to create an analysis framework using web mining principles on opinion mining application to grab people’s opinions and emotions about recent mobile  from contents of website addition to this, we also introduce an architecture, implementation, and evaluation of a web mining application called the Opinion mining, which will extracts classifies people's opinions & emotions about mobile reviews.

Abstract: Image files can be compressed the different techniques. An compressing image is significantly different than compressing raw binary data. Image compression addresses the problem by reducing the amount of data required to represent a digital image. The uncompressed image data requires a large storage capacity and transmission bandwidth. The purpose of the image compression algorithm is to reduce the amount of data required to represents the image with less degradation in the visual quality and without any information loss. The discrete cosine transform (DCT) used to reduce the redundancy between the pixels and for energy compaction. It is used specially for the compression of images where tolerable degradation is required. With the wide use of computers and consequently need for large scale storage and transmission of data, efficient ways of storing of data have become necessary. In this paper the performance of discrete cosine transform based compression technique with different matrix order was analyzed.  DCT with 8 x 8 block gives good compromise between information packing ability and computational complexity.

Abstract: The aim of Association Rule Mining is to find the correlation between data Items based on frequency of occurrence. Infrequent Item set mining is a variation of frequent item set mining where it finds the uninteresting patterns i.e., it finds the data items which occurs very rarely. Considering weight for each distinct item in a transaction independent manner adds effectiveness for finding frequent item set mining. Several articles related to frequent and weighted infrequent item set mining were proposed. This paper focus on reviewing various Existing Algorithms related to frequent and infrequent item set mining which creates a path for future researches in the field of Association Rule Mining.

Abstract: Manet (Mobile Ad-Hoc Network) refers to a network that is designed for a specific purpose only and employ where it is difficult to set-up a centralized network. It is a collection of mobile devices forming a communication network without using any pre-established infrastructure. Because of the dynamic nature like node mobility, resource constrained environment and routing using wireless media of Manet networks routing protocols play a significant role to measure the efficiency and performance of the network. Some typical application areas of Manet consider some efficiency parameters. Generally it includes packet delivery ratio, throughput and shortest available path. This paper evaluates and analyzes the performance of three Manet routing protocols namely, AODV, DSDV and OLSR using simulation.  On the basis of detailed simulation results and analysis, a suitable routing protocol can be indentified to meet the specified network conditions and the targeted goals.

Abstract: Information present on the internet is in the form of text. Even other sources of information like images, audios, videos also must be described in the form of text to convey their value to the users. So Information retrieval (IR) and Text mining applications have become very important. These applications require an proper way to represent text document in the form of mathematical objects so that it can be processed as required. Also an intelligent system which calculates closeness between two text documents is integral part of such applications. There are many ways to represent text document in mathematical form like Vector Space Model (VSM), Distance Graph, Concept Link Graph etc. VSM is most efficient and is widely used in many applications requiring text processing rather than other techniques. But VSM has major limitation that it can't maintain semantics of document. E-VSM: Enhanced-Vector Space Model is proposed to overcome original VSM's limitation of not able to maintain ordering of terms in text document and novel approach to find context-based closeness between two text documents which uses E-VSM to represent text document.

Abstract: The rapid growth of available data and the widespread use of database have created an immense need for data mining. It allows user to analyse data from many different dimensions, categorize it, and summarize the relationships identified for finding correlations or patterns among dozens of fields in large relational database to make processes more efficient, effective, predictable, and profitable. It is used to make critical business decisions include retail, telecommunication, sales and marketing, healthcare, insurance, finance, manufacturing and various other. This article discuss about data mining meaning, need for data mining, its major elements, advantages, various types of data used, and some data mining applications. The relation between data, information and knowledge in knowledge discovery is illustrated. Data mining finds applications in different areas like banking, financial, astrology, retail, telecommunication, education, bio-medical, agricultural, social media, spacial, tax governing fields, security and various others. Modern technologies allow storage of large amounts of raw data which invariably contains usable information, by using data mining techniques which can be used to analyse that data and uncover previously unknown rules and associations, hidden knowledge which once acquired and properly interpreted can be used in multitude of ways, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics.

Abstract: Cloud computing is now evolving like never before, with companies of all shapes and sizes adapting to this new technology. Industry experts believe that this trend will only continue to grow and develop even further in the coming few years. Cloud computing is Internet-based computing, whereby shared resources, software and information are provided to computers and other devices on-demand, like the electricity grid. The cloud computing is a culmination of numerous attempts at large scale computing with seamless access to virtually limitless resources. It is providing excellent facilities to business entrepreneurs by flexible infrastructure. In this paper we have provided better understanding of the cloud computing and focused on important research issues and developments related to Cloud Computing Technology.

Abstract: Computer networking has become an important infrastructure for our daily communication as it is interconnecting people together to make a borderless world.  The usage of internet has increased in various fields like online banking, business tradition, online shopping and so on. Along with that hacking tools are appearing which exploits system vulnerabilities. So computer network security has become very important in order to develop a mechanism that provides a defense against the intrusions from attackers. Thus Intrusion Detection System (IDS) acts as a second line important component of the defense-in depth security mechanism. To detect the attack with the great accuracy is our major concerned. Many neural network (NNs) techniques have been used for detection of the attacks. This paper analyzes different Adaptive Resonance Theory (ART) techniques that are being used in IDS to detect attacks. Among those Fuzzy ART technique has been found beneficial. This thesis also shows that how different parameters of ART techniques affect the overall performance of the system.

Abstract: Templates are used by many websites for increasing the productivity of publishing the Web pages. Common templates are used with its contents. The templates provide users to easily access the contents due to its consistent structures. However, for machines, the templates are considered harmful because of its irrelevant terms in the template, so it will degrade the performance of web applications. Thus, template detection and extraction techniques have received a lot of attention to improve the performance of search engines, web application, clustering and classification of web documents. The objective of this paper is to cluster the web documents based on the similarity of underlying template structures in the documents so that the templates for each cluster are extracted simultaneously. While extracting the templates, here consider the web page structure along with its contents. To effectively manage an unknown number of clusters (templates) Minimum Description Length (MDL) Principle is use and MinHash technique to estimate the MDL cost quickly. So that it will form a qualified cluster.

Abstract:  In Kenya there has been a rapidly increasing adoption of electronic payment by large enterprises but not by small and medium enterprises. The purpose of this study was to investigate on the factors that influence adoption electronic payment among the hotel SMEs, Kisii town, Kenya. A Survey design was conducted to each manger of the 50 hotel SMEs in Kisii town using a closed ended questionnaire. Data on entrepreneurial characteristics, costs and ease of use was obtained and analysed for descriptive statistics.  The findings of the study confirmed that entrepreneur background characteristics in measured in terms of education levels, age and skills influenced electronic payments highly. Similarly, and ease of use of electronic gadgets in terms of speed, convenience and storage influenced adoption of electronic payments highly.  On the basis of the findings it was concluded that entrepreneur background characteristic sand ease of use of electronic gadgets  are the main factors that influence adoption of electron payments. On the basis of the findings the study recommends for improvement of the entrepreneur background characteristics through apprentinceship and training and exposure, and innovations to come up with cheap electronic payment gadgets affordable by the hotel SMEs. Likewise the Governments intervention in form of reduced taxation and tariffs would significantly reduce the cost of installation and operation of the electronic gadgets. More also the study recommends simple innovative gadgets that would enhance the ease of use by the hotel SMEs.

Abstract:  In this paper a robust image watermarking technique has been presented i.e. Discrete Cosine Transform. Watermarked data is encrypted for   the cryptography purpose. The main stratagem for the approach is to enhance capacity and security feature. Capacity is increased by the nesting technique as per which we will embed watermark into watermark. The frequency domain is used in this research as the spatial domain is less robust than this. Though the spatial domain is less time consuming but robustness is the most important factor to be considered for cryptography.