Discoveries of Contextualized Research Areas for Scientific Community

In scientific community searching the relevant paper is a time critical task and often leads to misdirection. This is mainly due to the unstructured or semi-structured information indexed by search engines. However, with the evolution of social web (Web 2.0), the social community is being engaged in a system where they provide useful annotations (termed as tags) to the electronic resources. The current research makes use of social web to discover the most relevant papers from the Web. In our previous work, we compared author's keywords in a publication with the tags provided by the social community for serendipitous discoveries of related concepts and papers. However, in the current work, we focused to find a hierarchy of concepts related to focused publication. This hierarchy is discovered from Wordnet ontology, producing the convergent and divergent concepts for the author's keywords in a publication. These extended sets of keywords are matched with tags in social Web to find related concepts. In this way, the system is able to not only find the concepts in social Web that are directly related to the topics of the paper, instead, the system also discover the divergent and convergent concepts related to the topic of the paper. In this way, the users will be able to explore a topic hierarchy related to the paper's topics. The user can follow a concept to see the associated resources that have been annotated by the social community.