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殺人

Introducing Domain and Typing Bias in Automata Inferencerings that belong to the language and eventually strings that do not. In this paper, we present a generic setting allowing to express domain and typing background knowledge. Algorithmic solutions are provided to introduce this additional information efficiently in the classical state-merging automat

防水

Representing Languages by Learnable Rewriting Systemse represent these languages. Among the formalisms that allow to define classes of languages, the one of string-rewriting systems (SRS) has outstanding properties. Indeed, SRS are expressive enough to define, in a uniform way, a noteworthy and non trivial class of languages that contains all the regu

Amorous

A Divide-and-Conquer Approach to Acquire Syntactic Categoriesclassify function words from unannotated corpora. Then, the acquired information is used in two different learning processes. On the one hand, it is used to learn morpho-syntactic categories of nouns and, on the other, it turns out to be useful to also induce syntactic/semantic relationships between

去才蔑視

Grammatical Inference Using Suffix Treesd according to a context-free grammar. The framework produces good results even when simple techniques are used. However, the techniques used so far have computational drawbacks, resulting in limitations with respect to the amount of language data to be used. In this article, we propose a new alignm

表被動

Learning Stochastic Finite Automata learnability of these finite state machines. In the setting of identification in the limit with probability one, we prove that stochastic deterministic finite automata cannot be identified from only a polynomial quantity of data. If concerned with approximation results, they become .-learnable if t

Diastole

馬籠頭

A Corpus-Driven Context-Free Approximation of Head-Driven Phrase Structure GrammarI [2], into context-free grammars (CFGs). The method is unsound in that it does . generate a CFG whose language is a true superset of the language accepted by the original UBG. It is a corpus-driven method in that it relies on a corpus of parsed sentences and generates broader CFGs when given more i

thwart

惡臭

embolus

Music Listening, Emotions, Age and Context,ful, recursive models can be used to account for more complex mappings, it has been argued that the input-output relations underlying most usual natural language pairs are essentially rational. Moreover, the relative simplicity of these mappings has recently lead to the development of techniques for