Todd

Todd or Todds may refer to:

See also

George Michael

Georgios Kyriacos Panayiotou (born 25 June 1963), better known by his stage name George Michael, is an English singer, songwriter and record producer. Michael rose to fame during the 1980s and 1990s with his style of post-disco dance-pop. He has also been characterised as a blue-eyed soul singer, although his material draws more from middle-of-the-road pop than soul music.

As one of the world's best-selling music artists, Michael has sold more than 80 million records worldwide. His 1987 debut solo album, Faith, has on its own sold more than 20 million copies worldwide. Michael has garnered seven number one singles in the UK and eight number one hits on the Billboard Hot 100 in the US. In 2008, Billboard magazine ranked Michael the 40th most successful artist on the Billboard Hot 100 Top All-Time Artists list.

Michael has won numerous music awards throughout his 30-year career, including three Brit Awards—winning Best British Male twice, four MTV Video Music Awards, four Ivor Novello Awards, three American Music Awards, and two Grammy Awards from eight nominations.

Word-sense disambiguation

In computational linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing and ontology. WSD is identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings. The solution to this problem impacts other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference et cetera.

The human brain is quite proficient at word-sense disambiguation. The fact that natural language is formed in a way that requires so much of it is a reflection of that neurologic reality. In other words, human language developed in a way that reflects (and also has helped to shape) the innate ability provided by the brain's neural networks. In computer science and the information technology that it enables, it has been a long-term challenge to develop the ability in computers to do natural language processing and machine learning.

To date, a rich variety of techniques have been researched, from dictionary-based methods that use the knowledge encoded in lexical resources, to supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, to completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date.