Retrieving relevant tweets corresponding to cultural events can be used in various applications like event reporting, event recommendation, etc. This type of retrieval is challenging due to short length of the tweet, noise, out of vocabulary words, abbreviations in the tweet. In this paper, we focus on the problem of retrieving relevant tweets related to given cultural event of a festival. We consider several factors like BM25, DFR, presence of artist name, relevant hashtag, festival name for finding the relevance of tweets to the event. We apply BM25 + DFR model to retrieve candidate set of tweets related to each event of a festival. We find the top hashtags for each event by exploring meta-attributes of an event. We re-rank the initial rank list from BM25 + DFR based on two strategies, namely, presence of the event meta-attributes (artist name, festival name, title, etc.) and the identified top hashtags in the tweet, and based on the timestamp of the event. We experimented on a subset of CLEF 2017 cultural microblog contextualization dataset. The experimental results show that the proposed method is able to put relevant tweets at the top of the retrieval list.