Human-made query-based summaries commonly contain information not explicitly asked for. They answer the user query, but also provide supporting information. In order to find this information in the source text, a graph is used to model the strength and type of relations between sentences of the query and document cluster, based on various features. The resulting extracts rank second in overall readability in the DUC 2006 evaluation. Employment of better question answering methods is the key to improve also content-based evaluation results
Effective extraction of query relevant information present within documents on the web is a nontriv-...
In this paper, a query-based summarization method, which uses a combination of semantic relations be...
When a user is served with a ranked list of relevant doc-uments by the standard document search engi...
Research on Question Answering is focused mainly on classifying the question type and finding the an...
In this paper we report an initial study on the effectiveness of query-biased summaries for a questi...
In this paper we report on the effectiveness of query-biased summaries for a question-answering task...
We investigate a new training paradigm for extractive summarization. Traditionally, human abstracts ...
This paper presents a survey of recent extractive query-based summarization techniques. We explore a...
International audienceQuery-focused summaries of foreign-language, retrieved documents can help a us...
We investigate the effectiveness of using semantic and context features for extracting document summ...
A summary is a shortened version of a text that contains the main points of the original content. Au...
We present an approach for extractive, query-focused, single-document summarisation of medical text....
Research on question answering dates back to the 1960s but has more recently been revisited as part ...
Evidence-based medicine practice requires medical practitioners to rely on the best available eviden...
Modern search engines display a summary for each ranked document that is returned in response to a q...
Effective extraction of query relevant information present within documents on the web is a nontriv-...
In this paper, a query-based summarization method, which uses a combination of semantic relations be...
When a user is served with a ranked list of relevant doc-uments by the standard document search engi...
Research on Question Answering is focused mainly on classifying the question type and finding the an...
In this paper we report an initial study on the effectiveness of query-biased summaries for a questi...
In this paper we report on the effectiveness of query-biased summaries for a question-answering task...
We investigate a new training paradigm for extractive summarization. Traditionally, human abstracts ...
This paper presents a survey of recent extractive query-based summarization techniques. We explore a...
International audienceQuery-focused summaries of foreign-language, retrieved documents can help a us...
We investigate the effectiveness of using semantic and context features for extracting document summ...
A summary is a shortened version of a text that contains the main points of the original content. Au...
We present an approach for extractive, query-focused, single-document summarisation of medical text....
Research on question answering dates back to the 1960s but has more recently been revisited as part ...
Evidence-based medicine practice requires medical practitioners to rely on the best available eviden...
Modern search engines display a summary for each ranked document that is returned in response to a q...
Effective extraction of query relevant information present within documents on the web is a nontriv-...
In this paper, a query-based summarization method, which uses a combination of semantic relations be...
When a user is served with a ranked list of relevant doc-uments by the standard document search engi...