D. Moldovan

Publications278
h-index48
Citations9,246
Highly Influential Citations510
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On the semantics of noun compounds
TLDR
An analysis is performed using two sets of semantic classification categories: a list of 8 prepositional paraphrases previously proposed by Lauer and a new set of 35 semantic relations introduced by us. Expand
Partitioning and Mapping Algorithms into Fixed Size Systolic Arrays
TLDR
A technique for partitioning and mapping algorithms into VLSI systolic arrays is presented and an approach to algorithm partitioning which is also based on algorithm transformations is presented. Expand
Automatic Discovery of Part-Whole Relations
TLDR
This paper presents a supervised, semantically intensive, domain independent approach for the automatic detection of part-whole relations in text and demonstrates the importance of word sense disambiguation for this task. Expand
FALCON: Boosting Knowledge for Answer Engines
TLDR
FALCON, an answer engine that integrates different forms of syntactic, semantic and pragmatic knowledge for the goal of achieving better performance is discussed. Expand
COGEX: A Logic Prover for Question Answering
TLDR
The idea of automated reasoning applied to question answering is introduced and the feasibility of integrating a logic prover into a Question Answering system is shown. Expand
Models for the Semantic Classification of Noun Phrases
TLDR
An approach for detecting semantic relations in noun phrases using a learning algorithm to automatically label complex nominals, genitives and adjectival noun phrases with the corresponding semantic relation. Expand
LCC Tools for Question Answering
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eXtended WordNet: progress report
Performance issues and error analysis in an open-domain question answering system
TLDR
The overall performance of a state-of-the-art Question Answering system depends on the depth of natural language processing resources and the tools used for answer finding. Expand
LASSO: A Tool for Surfing the Answer Net
TLDR
The architecture, operation and results obtained with the Lasso system developed in the Natural Language Processing Laboratory at SMU, which relies on a combination of syntactic and semantic techniques, and lightweight abductive inference to answers. Expand
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