This paper presents a new approach for automatically extracting key phrases from a Bengali document. Our proposed approach presented in this paper has two important steps: (1) a shallow parsing based candidate key phrase identification that uses lexical information and case markers for candidate key phrase identification and (2) choosing the best items from the set of the candidates using a ranking method that combines the statistical features and the linguistic features for ranking the candidates. The feature set includes term frequency, position of the phrase's first occurrence, named entity information and lexical information. The proposed system has been tested on a collection of Bengali news documents. The experimental results show that it performs better than the existing approaches to which it is compared.
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