In this paper, we investigate extractive multi-document summarisation algorithms over newswire corpora. Examining recent findings, baseline algorithms, and state-of-the-art systems is pertinent given the current research interest in event tracking and summarisation. We first reproduce previous findings from the literature, validating that automatic summarisation evaluation is a useful proxy for manual evaluation, and validating that several state-of-the-art systems with similar automatic evaluation scores create different summaries from one another. Following this verification of previous findings, we then reimplement various baseline and state-of-the-art summarisation algorithms, and make several observations from our experiments....
Many articles on the same news are daily published by online newspapers and by various social media....
The production of accurate and complete multiple-document summaries is challenged by the complexit...
This work proposes a trainable system for summarizing news and obtaining an approximate argumentati...
In this paper, we investigate extractive multi-document summarisation algorithms over newswire corp...
This thesis investigates whether the summarisation of news-worthy events can be improved by using ev...
Since 2001, the Document Understanding Conferences have been the forum for researchers in automatic ...
This paper describes a multidocument summarizer built upon research into the detection of new inform...
International audienceIn this paper, we present a novel approach for automatic summarization. CBSEAS...
We describe a task-based evaluation to determine whether multi-document summaries measurably improve...
In the period since 2004, many novel sophisticated approaches for generic multi-document summarizati...
International audienceIn this paper, we present a novel approach for automatic summarization. Our sy...
We describe a task-based evaluation to determine whether multi-document summaries measurably improve...
Publicly available data grows exponentially through web services and technological advancements. To ...
952-962Due to the presence of large amounts of data and its exponential level generation, the manual...
Natural Language Processing is booming with its applications in the real world, one of which is Text...
Many articles on the same news are daily published by online newspapers and by various social media....
The production of accurate and complete multiple-document summaries is challenged by the complexit...
This work proposes a trainable system for summarizing news and obtaining an approximate argumentati...
In this paper, we investigate extractive multi-document summarisation algorithms over newswire corp...
This thesis investigates whether the summarisation of news-worthy events can be improved by using ev...
Since 2001, the Document Understanding Conferences have been the forum for researchers in automatic ...
This paper describes a multidocument summarizer built upon research into the detection of new inform...
International audienceIn this paper, we present a novel approach for automatic summarization. CBSEAS...
We describe a task-based evaluation to determine whether multi-document summaries measurably improve...
In the period since 2004, many novel sophisticated approaches for generic multi-document summarizati...
International audienceIn this paper, we present a novel approach for automatic summarization. Our sy...
We describe a task-based evaluation to determine whether multi-document summaries measurably improve...
Publicly available data grows exponentially through web services and technological advancements. To ...
952-962Due to the presence of large amounts of data and its exponential level generation, the manual...
Natural Language Processing is booming with its applications in the real world, one of which is Text...
Many articles on the same news are daily published by online newspapers and by various social media....
The production of accurate and complete multiple-document summaries is challenged by the complexit...
This work proposes a trainable system for summarizing news and obtaining an approximate argumentati...