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Liam Scanlon

dblp:270/6459 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2020
0000-0001-7105-7440ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval
evaluation
0.412020
Evaluation of Cross Domain Text Summarization · SIGIR 2020
Information retrieval › text summarization
headline generation
0.412020
Evaluation of Cross Domain Text Summarization · SIGIR 2020
Information retrieval
text summarization
0.412020
Evaluation of Cross Domain Text Summarization · SIGIR 2020

Methods — techniques the papers use, named apart from their topics

extractive-abstractive summarization · 0.4
YearPublicationVenuePosition
2020 Evaluation of Cross Domain Text Summarization
abstract
Extractive-abstractive hybrid summarization can generate readable, concise summaries for long documents. Extraction-then-abstraction and extraction-with-abstraction are two representative approaches to hybrid summarization. But their general performance is yet to be evaluated by large scale experiments.We examined two state-of-the-art hybrid summarization algorithms from three novel perspectives: we applied them to a form of headline generation not previously tried, we evaluated the generalization of the algorithms by testing them both within and across news domains; and we compared the automatic assessment of the algorithms to human comparative judgments. It is found that an extraction-then-abstraction hybrid approach outperforms an extraction-with-abstraction approach, particularly for cross-domain headline generation.
Liam Scanlon, Xiuzhen Zhang 0001, Mark Sanderson
SIGIR1