Web + Data Mining: Web Mining

Zusammenfassung: Dieser Beitrag gibt eine kurze Beschreibung, was unter dem Begriff Web Mining zu verstehen ist und wie Webdaten mit gängigen Data-Mining-Techniken kombiniert werden können, um das Web besser als Informationsquelle nutzbar zu machen. Des Weiteren wird ein Überblick über die gängigen Hauptachsen gegeben, entlang derer die meisten aktuellen Entwicklungen stattfinden. Diese Ausführungen werden mit einem Ausblick auf mögliche zukünftige Entwicklungen abgeschlossen, die vor allem durch die neusten Trends in der Benutzung des World Wide Web vorgezeichnet sin

DAMEWARE - Data Mining & Exploration Web Application Resource

Astronomy is undergoing through a methodological revolution triggered by an unprecedented wealth of complex and accurate data. DAMEWARE (DAta Mining & Exploration Web Application and REsource) is a general purpose, Web-based, Virtual Observatory compliant, distributed data mining framework specialized in massive data sets exploration with machine learning methods. We present the DAMEWARE (DAta Mining & Exploration Web Application REsource) which allows the scientific community to perform data mining and exploratory experiments on massive data sets, by using a simple web browser. DAMEWARE offers several tools which can be seen as working environments where to choose data analysis functionalities such as clustering, classification, regression, feature extraction etc., together with models and algorithms.Comment: User Manual of the DAMEWARE Web Application, 51 page

A Literature Survey on Web Content Mining

Web is an accumulation of inter related documents on one or more web servers while web mining implies extricating important data from web databases. Web mining is one of the data mining spaces where data mining methods are utilized for extricating data from the web servers. The web information incorporates site pages, web links, questions on the web and web logs. Web mining is utilized to comprehend the client behavior, assess a specific site in view of the data which is stored in web log documents. Web mining is assessed by utilizing data mining strategies, specifically Association Rules, Classification and Clustering. It has some helpful regions or applications, for example, Electronic trade, E-learning, E-government, E-arrangements, E-majority rules system, Electronic business, security, crime examination and computerized library. Recovering the required web page from the web productively and adequately becomes a challenging task since web is comprised of unstructured information, which conveys the substantial measure of data and increment the unpredictability of managing data from various web service providers. The accumulation of data turns out to be elusive, extract, channel or assess the significant data for the clients. In this paper, we have considered the essential ideas of web mining, classification, procedures and issues. Notwithstanding this, this paper likewise broke down the web mining research challenges

Using web mining in e-commerce applications

Nowadays, the web is an important part of our daily life. The web is now the best medium of doing business. Large companies rethink their business strategy using the web to improve business. Business carried on the Web offers the opportunity to potential customers or partners where their products and specific business can be found. Business presence through a company web site has several advantages as it breaks the barrier of time and space compared with the existence of a physical office. To differentiate through the Internet economy, winning companies have realized that e-commerce transactions is more than just buying / selling, appropriate strategies are key to improve competitive power. One effective technique used for this purpose is data mining. Data mining is the process of extracting interesting knowledge from data. Web mining is the use of data mining techniques to extract information from web data. This article presents the three components of web mining: web usage mining, web structure mining and web content mining.e-commerce, web mining, web content mining, web structure mining, web usage mining

A Survey on Web Usage Mining, Applications and Tools

World Wide Web is a vast collection of unstructured web documents like text, images, audio, video or Multimedia content.  As web is growing rapidly with millions of documents, mining the data from the web is a difficult task. To mine various patterns from the web is known as Web mining. Web mining is further classified as content mining, structure mining and web usage mining. Web usage mining is the data mining technique to mine the knowledge of usage of web data from World Wide Web. Web usage mining extracts useful information from various web logs i.e. users usage history. This is useful for better understanding and serve the people for better web applications. Web usage mining not only useful for the people who access the documents from the World Wide Web, but also it useful for many applications like e-commerce to do personalized marketing, e-services, the government agencies to classify threats and fight against terrorism, fraud detection, to identify criminal activities, the companies can establish better customer relationship and can improve their businesses by analyzing the people buying strategies etc. This paper is going to explain in detail about web usage mining and how it is helpful. Web Usage Mining has seen rapid increase towards research and people communities

Web Usage Mining for UUM Learning Care Using Association Rules

The enormous of information on the World Wide Web makes it obvious candidate for data mining research. Application of data mining techniques to the World Wide Web referred as Web mining where this term has been used in three distint ways; Web Content Mining, Web Structure Mining and Web Usage Mining. E-Learning is one of the Web based application where it will facing with large amount of data. In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. Web usage mining consists of three main phases, namely Data Preprocessing. Pattern Discovering and Patern Analysis. Main resources, server log files become a set of raw data where it's must go through with all the Web usage mining technique, Web usage mining approach has been combined with the basic Association Rules, Apriori Algorithm to optimize the content of the university E-Learning portal. Finally this paper will present an overview of results with the analysis and Web administrator can use the findings for the suitable valuable actions