This paper studies the problem of automatically extracting a short title from a manually written longer description of E-commerce products for display on mobile devices. It is a new extractive summarization problem on short text inputs, for which we propose a feature-enriched network model, combining three different categories of features in parallel. Experimental results show that our framewor...

Back ground: Ayurvedic medicines play an important role in gastro intestinal problems due to safety and efficacy in it. Hence churna meant for digestive property has been formulated by standard procedures and evaluated by physical and analytical methods. Method: The formulation consists of fine powder (sieve 60 size) of dried rhizomes of Zingiber officinale, fruits of Foeniculum vulgarae, barks...

The problem of extractive text summarization for a collection of documents is defined as selecting a small subset of sentences so the contents and meaning of the original document set are preserved in the best possible way. In this paper we present a new model for the problem of extractive summarization, where we strive to obtain a summary that preserves the information coverage as much as poss...

We consider the problem of producing a multi-document summary given a collection of documents. Since most successful methods of multi-document summarization are still largely extractive, in this paper, we explore just how well an extractive method can perform. We introduce an “oracle” score, based on the probability distribution of unigrams in human summaries. We then demonstrate that with the ...

While sentence extraction as an approach to summarization has been shown to work in documents of certain genres, because of the conversational nature of email communication, sentence extraction may not result in a coherent summary. In this paper, we present our work on augmenting extractive summaries of threads of email conversations with automatically detected question-answer pairs. We compare...

Extractive methods work by selecting a subset of existing words, phrases, or sentences in the original text to form the summary. In contrast, abstractivemethods build an internal semantic representation and then use natural language generation techniques to create a summary that is closer to what a human might generate. Such a summary might contain words not explicitly present in the original. ...

a simple extractive spectrophotometric method has been developed for the estimation of miconazole nitratein both pure and pharmaceutical preparation. the method is based on the formation of ion-pair complex of thedrug with acidic dye bromothymol blue (btb) in acidic condition, followed by its extraction in organic solvent(chloroform). the absorbance was measured against the corresponding blank....

We present an approach for extractive, query-focused, singledocument summarisation of medical text. Our approach utilises a combination of target-sentence-specific and target-sentence-independent statistics derived from a corpus specialised for summarisation in the medical domain. We incorporate domain knowledge via the application of multiple domain-specific features, and we customise the answ...

There are known biocatalytic pathways to produce many common fuels and petrochemicals. These biocatalysts can be either enzymes or living microorganisms. The challenge is to produce these fuels and chemicals efficiently and economically. Critical parameters include feedstock Costs, yield, rate and downstream processing. Here we will examine several immobilized biocatalyst reactor designs that w...

In this paper we address two key challenges for extractive multi-document summarization: the search problem of finding the best scoring summary and the training problem of learning the best model parameters. We propose an A* search algorithm to find the best extractive summary up to a given length, which is both optimal and efficient to run. Further, we propose a discriminative training algorit...