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Category: NLP

A General Supervised Approach for Segmentation of Clinical Texts

A General Supervised Approach for Segmentation of Clinical Texts

Segmentation of clinical texts into logical groups is critical for all sorts of tasks such as medical coding for billing, auto drafting of discharge summaries, patient problem list generation, population study on allergies, etc. While there have been previous studies on using supervised approaches to segmentation of clinical texts, these existing approaches were trained and tested on a fairly limited data set showing low adaptability to new unseen documents. We propose a highly generalized model for segmenting clinical texts, based on a set of line-wise predictions by a classifier with constraints imposing their coherence. Evaluation results on 5 independent test sets show that the proposed approach can work on all sorts of note types and performs consistently across different organizations (i.e. hospitals).

Micropinion Generation: An Unsupervised Approach to Generating Ultra-Concise Summaries of Opinions

Micropinion Generation: An Unsupervised Approach to Generating Ultra-Concise Summaries of Opinions

This paper presents a new unsupervised approach to generating ultra-concise summaries of opinions. We formulate the problem of generating such a micropinion summary as an optimization problem, where we seek a set of concise and non-redundant phrases that are readable and represent key opinions in text. We measure representativeness based on a modified mutual information function and model readability with an n-gram language model.

Automated story capture from conversational speech

Automated story capture from conversational speech

Abstract While storytelling has long been recognized as an important part of effective knowledge management in organizations, knowledge management technologies have generally not distinguished between stories and other types of discourse. In this paper we describe a new type of technological support for storytelling that involves automatically capturing the stories that people tell to each other in conversations. We describe our first attempt at constructing an automated story extraction system using statistical text classification and a simple voting scheme. We…

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Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions

Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions

The Opinosis Summarization framework focuses on generating very short abstractive summaries from large amounts of text. These summaries can resemble micropinions or “micro-reviews” that you see on sites like twitter and four squares. The idea of the algorithm is to use a word graph data structure referred to as the Opinosis-Graph to represent the text to be summarized. Then, the resulting graph is repeatedly explored to find meaningful paths which in turn becomes candidate summary phrases.

What is ROUGE and how it works for evaluation of summaries?

What is ROUGE and how it works for evaluation of summaries?

ROUGE stands for Recall-Oriented Understudy for Gisting Evaluation. It is essentially of a set of metrics for evaluating automatic summarization of texts as well as machine translation. It works by comparing an automatically produced summary or translation against a set of reference summaries (typically human-produced). This article provides an intuitive explanation of how ROUGE works. 

Abstractive Summarization Papers

Abstractive Summarization Papers

While much work has been done in the area of extractive summarization, there has been limited study in abstractive summarization as this is much harder to achieve (going by the definition of true abstraction). This page contains a very small collection of ¬†summarization methods that are non-extractive…

rouge2csv – Script to Interpret ROUGE Scores

rouge2csv – Script to Interpret ROUGE Scores

This is a perl script that helps in interpreting ROUGE scores generated by the perl (original) implementation of ROUGE. If you need Instructions on how to set-up ROUGE for evaluation of your summarization tasks go here. Assuming you have piped all your ROUGE results to a file, this tool will collect all rouge scores into separate CSV files depending on the n-grams used. For example, all ROUGE-1 scores will be collected into a ROUGE-1.csv file, similarly all ROUGE-2 scores will…

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