Real Time Information Extraction from Microblog

This paper present the participation of Information Retrieval Lab(IR LAB DA-IICT Gandhinagar) in FIRE 2016 Microblog Track. The main objective of the track is to identify Information Retrieval methodologies to retrieve important information from Twitter posted during the disasters. We have submitted two runs for this track. In the first run, daiict irlab 1, we have expanded topic term using Word2vec model trained by the tweet corpus provided by the organizer. Relevance score between tweet and corpus are calculated by Okapi BM25 model. Precision@20 ,primary metric, for this run, is 0.3143. In the second run,daiict irlab 2, we have set different weight for original term and expanded topic term, we achieve precision@20 around 0.30.