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comprehensive and quality feeds for real-time event detection. In this paper, we present a novel adaptive keyword identification approach to retrieve a greater amount of event relevant content. This approach continuously monitors emerging hashtags and rates them by their similarity to specific pre-defined event hashtags using TF
In usual Information Retrieval (IR) systems, the user query is represented in the form of a keyword set. Information resources are retrieved according to their similarities to this query. Consequently if query is not declared with appropriate terms, retrieved results would not be satisfactory. Therefore query
In this paper, we examine the significance of expansion of the user query by two techniques namely Efficient Clustering-By-Direction and Theme Clustering. These two techniques produce the clusters of keywords extracted from the set of retrieved documents for the user query. The former clustering is based on
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