Information Retrieval from Microblogs during Natural Disasters
نویسندگان
چکیده
In this paper, we devise an information retrieval system which can filter and rank tweets according to relevance to the query. We devise methods to understand relationships among entities and action verbs from a small set of manually annotated tweets. We further use these relationships to filter tweets and rank them accordingly. Our results (as published by FIRE Microblog Track) show that we have high precision score in detection of topmost 20 tweets.
منابع مشابه
Word Embeddings for Information Extraction from Tweets
This paper describes our approach on “Information Extraction from Microblogs Posted during Disasters”as an attempt in the shared task of the Microblog Track at Forum for Information Retrieval Evaluation (FIRE) 2016 [2]. Our method uses vector space word embeddings to extract information from microblogs (tweets) related to disaster scenarios, and can be replicated across various domains. The sys...
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