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» Learning Probabilistic Models of Word Sense Disambiguation
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AAAI
2008
15 years 5 days ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
SIGIR
2004
ACM
15 years 3 months ago
An effective approach to document retrieval via utilizing WordNet and recognizing phrases
Noun phrases in queries are identified and classified into four types: proper names, dictionary phrases, simple phrases and complex phrases. A document has a phrase if all content...
Shuang Liu, Fang Liu, Clement T. Yu, Weiyi Meng
CCIA
2007
Springer
15 years 4 months ago
Semantic disambiguation of taxonomies
Polysemy is one of the most difficult problems when dealing with natural language resources. Consequently, automated ontology learning from textual sources (such as web resources) ...
David Sánchez, Antonio Moreno
NAACL
2003
14 years 11 months ago
A Context-Sensitive Homograph Disambiguation in Thai Text-to-Speech Synthesis
Homograph ambiguity is an original issue in Text-to-Speech (TTS). To disambiguate homograph, several efficient approaches have been proposed such as part-of-speech (POS) n-gram, B...
Virongrong Tesprasit, Paisarn Charoenpornsawat, Vi...
LREC
2010
153views Education» more  LREC 2010»
14 years 11 months ago
Homographic Ideogram Understanding Using Contextual Dynamic Network
Conventional methods for disambiguation problems have been using statistical methods with co-occurrence of words in their contexts. It seems that human-beings assign appropriate w...
Jun Okamoto, Shun Ishizaki