Web Mining and Social Multimedia Research Paper

Web Mining and Social Multimedia - Research Paper Example However, how does data mining filters the information gathered from the web from undesirable and inaccurate data that is so often giving us difficulties in gathering valuable and high-quality results? It is common knowledge that the data found on the web is unstructured, dynamic, complex and huge in amount. This results in difficulties for analyzing such data. What techniques and applications are used in Web Mining to overcome these difficulties? The answers to these questions could benefit both research and industry communities. Web Mining and Social Multimedia Introduction Web mining refers to the application of data mining techniques to extract patterns from the web. Generally data mining allows for analysis of data in order to make rational decision based on the data report collected. It is common knowledge that the data found on the web is unstructured, dynamic, complex and huge in amount which results in difficulties for analyzing such data. Consequently the information gathere d by web mining can be further evaluated using various software or through the traditional data mining parameters such as classification, clustering and association. There are three main axes of web mining which include content mining, usage mining and structure mining. Content mining is usually applied in the examination of data collected by web spiders and search engines. On the other hand, structure mining is used when examining the structure of given websites while usage mining is generally used to study data related to user’s browser as well as the data collected by the forms users usually submit during their web transactions. When such data is being analyzed based on the web documents, especially with a wide spread of social multimedia, the information gathered can benefit research institutions, businesses and economy overall. Additionally web mining can potentially be used in customer relationship management by helping to evaluate the customer behavior, effectiveness o f the website as well as quantify the success of the marketing campaign used in the World Wide Web. Although web mining has numerous potential benefits particularly with regard to the interpretation of meaningful data, the technology has also been regarded as a disruptive technology due to some of the risks it poses both to personal and cooperate privacy (Domingos, 58). For example, the sophisticated technologies used in web mining have significantly increased the risk of information abuse as well as privacy violation. As many social media platforms continue to urge their users to become more transparent by revealing their personal information, the privacy of such users may be compromised. There are a number of data base technologies through which web mining can be used to discover the patterns in data. Some of the commonly used database mining techniques used in web mining include clustering, association and data classification. The difficulties in gathering quality data using web mining techniques usually arise from the fact that there are currently no agreed upon quality assessment models as well as the difficultly that arises from handling the quality of information particularly during the query processing and integration of data. In web mining, some of the scenarios in which the problem of data quality may arise include during the integration of scientific or business data and during the dissemination of the collected data. History of web mining The concept of web mining has rapidly grown in a short period of time both in terms of