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» A Trainable Document Summarizer
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SIGIR
2004
ACM
15 years 5 months ago
Focused named entity recognition using machine learning
In this paper we study the problem of finding most topical named entities among all entities in a document, which we refer to as focused named entity recognition. We show that th...
Li Zhang, Yue Pan, Tong Zhang
EMNLP
2008
15 years 1 months ago
Selecting Sentences for Answering Complex Questions
Complex questions that require inferencing and synthesizing information from multiple documents can be seen as a kind of topicoriented, informative multi-document summarization. I...
Yllias Chali, Shafiq R. Joty
DNIS
2007
Springer
117views Database» more  DNIS 2007»
15 years 6 months ago
Semantic Tracking in Peer-to-Peer Topic Maps Management
This paper presents a collaborative semantic tracking framework based on topic maps which aims to integrate and organize the data/information resources that spread throughout the I...
Asanee Kawtrakul, Chaiyakorn Yingsaeree, Fré...
PLSA
1994
15 years 3 months ago
Languages and Interactive Software Development
Abstract. Most software is developed using interactive computing systems and substantial compute-power. Considerable assistance can be given to the developer by providing language-...
Susan L. Graham
AAAI
2007
15 years 2 months ago
A Meta-learning Approach for Selecting between Response Automation Strategies in a Help-desk Domain
We present a corpus-based approach for the automation of help-desk responses to users’ email requests. Automation is performed on the basis of the similarity between a request a...
Yuval Marom, Ingrid Zukerman, Nathalie Japkowicz