4 research outputs found
Query-Based Summarization using Rhetorical Structure Theory
Research on Question Answering is focused mainly on classifying the question type and finding
the answer. Presenting the answer in a way that suits the userâs needs has received little
attention. This paper shows how existing question answering systemsâwhich aim at finding
precise answers to questionsâcan be improved by exploiting summarization techniques to extract
more than just the answer from the document in which the answer resides. This is done
using a graph search algorithm which searches for relevant sentences in the discourse structure,
which is represented as a graph. The Rhetorical Structure Theory (RST) is used to create a
graph representation of a text document. The output is an extensive answer, which not only
answers the question, but also gives the user an opportunity to assess the accuracy of the answer
(is this what I am looking for?), and to find additional information that is related to the question,
and which may satisfy an information need. This has been implemented in a working multimodal
question answering system where it operates with two independently developed question
answering modules
An Ontology- Based Multi-Document Summarization in Apocalypse Management
With the problem of extended information resources and the remarkable evaluate of data removal, the require of having automated summarization techniques revealed up. As summarization is needed the most at present searching information on the internet, where the user moves for a specific space of passion as per his question, area centered on summaries would provide the best. Ontology based summarization system for is provided. The ontology is a subjective model, which gives the important framework for semantic representation of textual data. In our suggested system implement the hierarchical levels of ontology to even more enhance the high summary and to execute hierarchical text classification in the field of earth quake management. We signify a scientific study of different techniques in which ontology has been applied for summarization practice. Comprehensive experiments on a selection of press launch appropriate to 2011 Sikkim earth quake illustrate that ontology centered multiple documents summarization techniques outperforms other baselines with regards to the conclusion top quality. Also we are designing a Hierarchical clustering algorithm instead of K-means clustering algorithm for better precision. It is found that the greater part of the current techniques often focus on sentence scoring and less attention is given to the appropriate information content in various records