Abstract:
Academic search engines typically capture the statistical properties of text rather than the linguistic structure. Depending on the interested research area, a researcher needs to read a lot of related literature articles to find a good research topic, to learn more about how a particular research area has evolved throughout time, to get an idea about the existing researches and products, to know about the cutting edge technologies used in current researches, to improve factual knowledge and to provide evidence and complete the research project in a unique approach successfully. Research Timeliner is an academic search engine which aims at solving the issues in current academic search engines by presenting the concept of improving the scholarly literature search by incorporating similarity measures with the linguistic features of research papers. It enhances the usual keyword-based, citation analysis and ratings search by hierarchically classifying the researcher’s interested research area according to the research techniques used in each research paper and chronologically order them. It combines the already known similarity approaches with semantic analysis concepts in order to create a holistic research paper search engine. It will show the researcher the related research papers to his/her interested area by classifying the searched area from the main domain to sub- domains with the semantically identified research papers.
