Using wordmap and score-based weight in opinion mining with mapreduce

摘要

Cloud computing is newly rising as a novel drift of data management and many researchers find that opinion mining can be faster using cloud computing. Using the current opinion mining is, however, unfit for the Internet because the Internet has huge information and is changing at short intervals. In addition, utilizing marks or scores such as the number of stars awarded and sentiment classification will be more commonly used for analyzing opinions. For these reasons, we propose a new approach to opinion mining. We use MapReduce function as an opinion analyzing and clustering tool with score-based weight and try to make opinion mining simpler because of fixing in MapReduce. Our new approach can analyze results of documents with the opinion mining faster than using current methods and make products that meet requirements of users who want to employ outcomes of opinion mining. Our study is a new idea for opinion mining and done in a distinctive way and we are looking forward to applying this noble method to all related fields including searching engines.