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» A Trainable Document Summarizer
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SIGIR
2004
ACM
14 years 29 days 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
13 years 9 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»
14 years 1 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
13 years 11 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
13 years 10 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