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Text Summarization is very effective in relevant assessment tasks. The Multiple Document Summarizer presents a novel approach to select sentences from documents according to several heuristic features. Summaries are generated modeling the set of documents as Semantic Vector Space Model (SVSM) and applying Principal Component Analysis (PCA) to extract topic features. Pure Statistical VSM assumes terms to be independent of each other and may result in inconsistent results. Vector space isdblp:journals/ijclclp/VikasMMG08 fatcat:mrg2zb5eobhufobt7ajtis6zvq