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Many were using phones, presumably to distribute words and pictures on social media in the absence of TV coverage.
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It also requires at least that would-be hearers are not prevented from comprehending the intended meaning of those sounds and scrawls-otherwise there is not free speech, merely the freedom to produce and distribute word-like sounds and scrawls.
A number of commentators have developed Mackinnon's claims in the face of Dworkin's response, arguing that freedom of speech (even negative freedom of speech) requires more than simply being free to produce and distribute word-like sounds and symbols.
Milton wants to dominate the highly fragmented $60 billion market for adult entertainment by taking early advantage of forthcoming broadband channels for distributing words and pictures over the internet.
For example, Joseph et al. [ 24] classified them into three categories: clustering-based, distributional and distributed word representations.
Solving the distributed word count problem is an example.
They learn distributed word and text representations and achieve state-of-the-art results on a range of NLP tasks.
Figure 2 First, we used a distributed word representations, i.e., Skip-gram model proposed by Mikolov et al.[13], to obtain the word embedding.
The solved problem is the distributed word count problem, and datasets are text files with various sizes ranging from 50 to 400 MB.
The use of distributed word representations (word embeddings) can be seen in several works of this area in tasks such as classification [88, 152, 153], summarization [154], and information retrieval [155].
The benefit of distributed word representations obtained with a neural language model (or even with a skip-gram model) is more evident when it comes to tagging words that did not appear in the supervised training data, but that are part of the model's vocabulary.
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