We present a novel Web Pages Summarizer ContextSummarizer that subgroups the given Web pages into ‘sense-clusters’ respecting a user’s topic interests, and constructs a dynamic extractive summary for each sense-cluster. A user’s topic interest is described by the user who selects and refines some of word senses disambiguated within the content contexts of the given Web pages. The semantic simil...

Background: In acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum ATCC 824 using corn-based substrate, the solvents are generally produced at a ratio of 3:6:1 (A:B:E, w/w). Results: A higher butanol/acetone ratio of 2.9:1 was found when cassava was used as the substrate of an in-situ extractive fermentation by C. acetobutylicum. This ratio had a 64% increment compared to t...

Although human-written summaries of documents tend to involve significant edits to the source text, most automated summarizers are extractive and select sentences verbatim. In this work we examine how elementary discourse units (EDUs) from Rhetorical Structure Theory can be used to extend extractive summarizers to produce a wider range of human-like summaries. Our analysis demonstrates that EDU...

In this paper, design and optimization procedures are developed for a conventional extractive distillation sequence and a thermally coupled extractive distillation scheme. The proposedmethodologies detect the optimal values of the design variables in order to guarantee theminimumenergy consumption. It was found that the optimumenergy consumption can be related to the minimum total annual operat...

We studied outlier document filtering (ODF) for extractive sentence summarization. Our results are superior compared to the average of the participant systems’ using DUC 2006. Furthermore, we add extractive paragraph summarization to the same system. It is surprising that the results are nearly the same for ROUGE metrics. Although extractive paragraph summarization has a better performance for ...

Automatic text summarization is the process of reducing the text content and retaining the important points of the document. Generally, there are two approaches for automatic text summarization: Extractive and Abstractive. The process of extractive based text summarization can be divided into two phases: pre-processing and processing. In this paper, we discuss some of the extractive based text ...