SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
The teachable language comprehender: a simulation program and theory of language
Communications of the ACM
An Adapted Lesk Algorithm for Word Sense Disambiguation Using WordNet
CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
Introduction to the special issue on word sense disambiguation: the state of the art
Computational Linguistics - Special issue on word sense disambiguation
An adaptive information retrieval system based on associative networks
APCCM '04 Proceedings of the first Asian-Pacific conference on Conceptual modelling - Volume 31
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 2
Word sense disambiguation: A survey
ACM Computing Surveys (CSUR)
Word sense disambiguation with spreading activation networks generated from thesauri
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
SENSEVAL '01 The Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems
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An unsupervised, knowledge-based, parametric approach to Word Sense Disambiguation is proposed based on the well-known cognitive architecture ACT-R. In this work, the target word is disambiguated based on surrounding context words using an accumulator model of memory search and it is realized by incorporating RACE/A with ACT-R 6.0. In this process, a spreading activation network is built following the strategies of Tsatsaronis et al. proposed in [5] using the chunks and their relations in the declarative memory system of ACT-R and the lexical representation has been achieved by integrating WordNet with the cognitive architecture. The resulting Word Sense Disambiguation system is evaluated using the test data set from English Lexical Sample task of Senseval-2 and overall accuracy of the proposed algorithm is 44.74% which outperforms all the participating Word Sense Disambiguation Systems.