• Aucun résultat trouvé

Using a question-answering approach in machine reading task of biomedical texts about the Alzheimer disease

N/A
N/A
Protected

Academic year: 2021

Partager "Using a question-answering approach in machine reading task of biomedical texts about the Alzheimer disease"

Copied!
6
0
0

Texte intégral

Figure

Fig 1. Example of EAGLi interface. Here, the user can provide a question to EAGLi and as a  response receives a list of answers
Fig. 2. The workflow of the Q-A approach. Here, Input Q+A is a generator of queries based on  the conjunction of question with provided answers

Références

Documents relatifs

This report describes the task Machine reading of biomedical texts about Alzheimer’s disease, which is a pilot task of the Question An- swering for Machine Reading Evaluation

The rest of the paper is structured as follows: Section 2 details the general architecture of our Question Answering system for Machine Reading Evaluation and the new

Thus, we decided to convert each pair of a question and a potential answer into the best supporting declarative sentence.. In our case this was done manually, but in future

We hope that exploiting better or tuned versions of the tools for syntactic and se- mantic analysis of text, the index expansion approach can provide an effective solu- tion to

Similar to recent research on finding important segments of biomedical text for document summarization [3], here we explore various information retrieval- based strategies to

The presented systems were built starting from the main components of our QA systems (the question processing and information retrieval modules) to which new

We investigated two forms of information expansion to improve over this baseline: (1) statistical expansion of the test document with sentences from the topical background corpus,

QA4MR [12] is related to some topics in the fields of information retrieval and natural language processing (NLP), such as question answering [11], reading comprehension [9]