Mining Competitors from Large Unstructured Datasets using C-Miner Algorithm

Data mining is the process of sorting through large datasets to identify patterns and establish relationship to solve a problem through data analysis. One of the major unsolved problems is the management of unstructured data. The unstructured data such as multimedia files, documents, comments, customer support request, news, emails, reports and web pages are difficult to capture and store in the common database system. Data mining is the popular area of the research which facilitates the business improvement process such as mining user preference, mining web information to get opinion about the product or services. In the current competitive business scenario, there is a need to analyse the competitive features and factors of an item that most affect its competitiveness. The evaluation of competitiveness always uses the customer opinions in terms of reviews, ratings and abundant source of information from the web and other sources. The challenges arise on the features of main competitors of a given item. Here our algorithm presents the reliable methods for evaluating competitiveness in large datasets and addresses the natural problem finding top-level competitors. This project provides the optimal improvements in the competitor mining tasks.