[PDF] Top 20 New Tools for Web-Scale N-grams

... While the web provides a fantastic linguistic resource, col- lecting and processing data at web-scale is beyond the reach of most academic laboratories. Previous approaches have relied on search ... See full document

... discovery tools at the Virtual Academic Library Environment (VALE) 2010 Annual Conference was used to identify these products (Yang and Wagner, ...discovery tools are considered separately from commercial, ... See full document

... Chang (1995) proposed a system that replaces each character in the sentence based on the confusion set and estimates the probability of all modified sentences according to a bigram language model built from a newspaper ... See full document

... the web, which employs a preprocessor for queries, and a postprocessor for search results on top of a traditional web search ...large-scale n-gram corpora. The approach is limited to short ... See full document

... learners. Web technology in particular stands as a medium with great educational value, mainly due to its ability to grant access to training material without any spatial or temporal constraints, thus motivating ... See full document

... ABSTRACT Basic research in pattern formation is concerned with the generation of phenotypes and tissues. It can therefore lead to new tools for medical research. These include phenotypic screening assays, ... See full document

... refined N-gram to the Wikipedia anchor text community resulting in a reduction in the information gap between N-grams, which are conceptually same but do not match ...of N-grams to ... See full document

... Most of the prior work of using knowledge sources focused on encoding them as additional features in supervised learning models. However, for some domains such as financial analysis very few annotated training corpora ... See full document

... Studying natural language, and especially how people describe the world around them can help us better understand the visual world. In turn, it can also help us in the quest to generate natural language that describes ... See full document

... a new N-gram corpus with N-grams of length 1-5 that we created from the same 1 tril- lion word snapshot of the web as Google N-grams Version 1 (Brants and Franz, 2006), ... See full document

... To write a focused book rather than an encyclopedia, we need to assume some background for you, the reader. We’re assuming that you know HTML and have created Web sites with HTML. Consequently, although we use ... See full document

... Table 6: Possible wrong tokens. We chose the best candidates that can re- place each word in the sentence and gener- ate new sentences with each one of the can- didates in his different combinations. Is easy to ... See full document

... Note that the model is not limited to using POS information. Rather, many other informa- tion sources could be used (supertags, additional morphology features, etc.), allowing to model dif- ferent translation properties. ... See full document

... word forms appear after a given preposition? Which ones should I learn by rote and which ones follow rules? The persistence of such questions indicates that this is an important challenge to be addressed— we should aim ... See full document

... ter n-grams), which was trained on both the train- ing and development data yielded the best test-set performance out of all our submitted ...character n-gram fea- tures were very powerful when ... See full document

... To what extent the syntactic structure of a lan- guage is linear is a question of typology and dif- fers widely between languages. The use of n- grams for linguistic applications and analyses is a method ... See full document

... As noted by Yamamoto and Church (2001) and shown in Fig. 2, GMI and RIDF do not exhibit apparent correla- tion. Multiword terms are concentrated in the upper half of the plot giving GMI more discriminative power than ... See full document

... Methods focused on meta info such as docu- ment URL (Resnik and Smith, 2003), publication dates or document structure, may work well on small structured corpora but suffer from sparsity and unreliability of meta info in ... See full document

... character n-gram representations. However, as with word-based features, character n-grams are unable to incorporate sequential information from documents in their original form (in terms of the ... See full document

... ter n-grams for complex word idenfitication start- ing from the assumption that character sequences in complex words are often different than those in simple ...with n-grams of different ... See full document