Search results
Results From The WOW.Com Content Network
The bag-of-words model (BoW) is a model of text which uses a representation of text that is based on an unordered collection (a "bag") of words. It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity.
It consists of about 1,000,000 words of running English prose text, made up of 500 samples from randomly chosen publications. Each sample is 2,000 or more words (ending at the first sentence-end after 2,000 words, so that the corpus contains only complete sentences).
One of the first writers to have attempted to provide the sentence meaning through context is Chinese linguist Yuen Ren Chao (1997). [9] Chao's poem, entitled Making Sense Out of Nonsense: The Story of My Friend Whose "Colorless Green Ideas Sleep Furiously" (after Noam Chomsky) was published in 1971. This poem attempts to explain what ...
The sentence can be given as a grammatical puzzle [7] [8] [9] or an item on a test, [1] [2] for which one must find the proper punctuation to give it meaning. Hans Reichenbach used a similar sentence ("John where Jack had...") in his 1947 book Elements of Symbolic Logic as an exercise for the reader, to illustrate the different levels of language, namely object language and metalanguage.
Hence, a native speaker would rate this sentence as odd, or unacceptable, because the meaning does not make sense according to the English lexicon. [6] Tree structure of the sentence "Colourless green ideas sleep furiously." Thus, for Chomsky a grammatical string is not necessarily a meaningful one.
An alternative direction is to aggregate word embeddings, such as those returned by Word2vec, into sentence embeddings. The most straightforward approach is to simply compute the average of word vectors, known as continuous bag-of-words (CBOW). [9] However, more elaborate solutions based on word vector quantization have also been proposed.
Scrambling is a syntactic phenomenon wherein sentences can be formulated using a variety of different word orders without a substantial change in meaning. Instead the reordering of words, from their canonical position, has consequences on their contribution to the discourse (i.e., the information's "newness" to the conversation).
for every sense of the word being disambiguated one should count the number of words that are in both the neighborhood of that word and in the dictionary definition of that sense; the sense that is to be chosen is the sense that has the largest number of this count. A frequently used example illustrating this algorithm is for the context "pine ...