Optimized summarization of research papers as an aid for research scholars using data mining techniques

Whenever a research scholar starts working on some innovative ideas he/she searches for the domain specific technical research articles published as research papers in most of the international journals, conferences or workshops. The problems associated with these papers are similarity in contents and repeated relevant information. Reading these all relatedpapers completely one by one to get the latest research developments in the interested domain is time-consuming, unnecessary, irrelevant, cumbersome and impossible. These problems are solved by developing a innovative solution, which optimizes and summarizes these research papers as an aid for research scholars using various Data Mining strategies. This helps research scholar for getting short, condensed, accurate and most relevant summarized information i.e. overview of domain-specific topic-based contents from research papers. Data mining strategies such as extraction and clustering are used for identifying `Research Relevant Novel´ (RRN) terms. Extracting relevant sentences from multiple papers uses `Maximal Marginal Relevance´ (MMR) criteria containing RRN terms. In addition to optimized and summarized contents, this paperalso informs earlier and latest research developments, progress, and challenges and future scope in particular field of study through various research categories identified such as research methods/techniques/approaches used, comparisons with existing research and providing starting material for further innovation.