Keyword Extraction for Medium-Sized Documents Using Corpus-Based Contextual Semantic Smoothing

Keyword extraction refers to the process of selecting most significant, relevant, and descriptive terms as keywords, which are present inside a single document. has major applications in information retrieval domain, such analysis, summarization, indexing, search, documents. In this paper, we novel supervised technique for keywords from medium-sized documents, namely Corpus-based Contextual Semantic Smoothing (CCSS). CCSS extends concept (CSS), considers term usage patterns similar texts improve relevance information. We introduce four more features beyond CSS our contributions work. systematically compare performance with other techniques, when implemented over INSPEC dataset, where outperforms all state-of-the-art keyphrase techniques presented literature.