Information Retrieval and Query Reformulation

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Indexing and evaluating the indexed ClueWeb12-B dataset and wrote an algorithm for automated query reformulation using concepts of graph theory

During June-July 2015, I got an opportunity to work as undergraduate summer research at Institut de Recherche en Informatique de Toulouse under the guidance of Prof. Josiane Mothe with her team SIG.

During this period, I performed a comparative study intending to find a better method of indexing Clueweb12-B(shards and complete dataset) using terrier. After that, I devised a method for automated query reformulation using the concepts of graph theory such as indegree of nodes linked to the query terms and used them to query the ClueWeb12-B dataset. The algorithm showed positive results with a subset of the actual data, and the testing for the complete dataset is scheduled for December 2015.