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» Using Information Extraction to Improve Document Retrieval
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CORR
2011
Springer
173views Education» more  CORR 2011»
14 years 11 months ago
Probability Based Clustering for Document and User Properties
Information Retrieval systems can be improved by exploiting context information such as user and document features. This article presents a model based on overlapping probabilistic...
Thomas Mandl, Christa Womser-Hacker
CICLING
2008
Springer
15 years 6 months ago
On Ontology Based Abduction for Text Interpretation
Abstract. Text interpretation can be considered as the process of extracting deep-level semantics from unstructured text documents. Deeplevel semantics represent abstract index str...
Irma Sofia Espinosa Peraldi, Atila Kaya, Sylvia Me...
ECIR
2004
Springer
15 years 6 months ago
Complex Linguistic Features for Text Classification: A Comprehensive Study
Abstract. Previous researches on advanced representations for document retrieval have shown that statistical state-of-the-art models are not improved by a variety of different ling...
Alessandro Moschitti, Roberto Basili
CORR
2007
Springer
135views Education» more  CORR 2007»
15 years 4 months ago
AMIEDoT: An annotation model for document tracking and recommendation service
The primary objective of document annotation in whatever form, manual or electronic is to allow those who may not have control to original document to provide personal view on inf...
Charles A. Robert
AIRS
2004
Springer
15 years 10 months ago
Document Clustering Using Linear Partitioning Hyperplanes and Reallocation
This paper presents a novel algorithm for document clustering based on a combinatorial framework of the Principal Direction Divisive Partitioning (PDDP) algorithm [1] and a simpli...
Canasai Kruengkrai, Virach Sornlertlamvanich, Hito...