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Identifying Semitic Roots: Machine Learning with Linguistic Constraints
Linguistic Constraints Root
2015/9/6
Words in Semitic languages are formed by combining two morphemes: a root and a pattern. The
root consists of consonants only, by default three, and the pattern is a combination of vowels
and consona...
Classifying Non-Sentential Utterances in Dialogue: A Machine Learning Approach
Machine Learning Approach Dialogue
2015/9/2
In this article we use well-known machine learning methods to tackle a novel task, namely
the classification of non-sentential utterances (NSUs) in dialogue. We introduce a fine-grained
...
A Machine Learning Approach to Modeling Scope Preferences
Machine Learning Approac Modeling Scope Preferences
2015/8/28
This article describes a corpus-based investigation of quantifier scope preferences. Following recent work on multimodular grammar frameworks in theoretical linguistics and a long history of combining...
Improving Accuracy in Word Class Tagging through the Combination of Machine Learning Systems
Word Class Tagging Machine Learning Systems
2015/8/26
We examine how differences in language models, learned by different data-driven systems performing the same NLP task, can be exploited to yield a higher accuracy than the best individual system. We do...
A Machine Learning Approach to Coreference Resolution of Noun Phrases
Noun Phrases Coreference Resolution
2015/8/26
In this paper, we present a learning approach to coreference resolution of noun phrases in unrestricted text. The approach learns from a small, annotated corpus and the task includes resolving
not ju...
Bootstrapping Morphological Analyzers by Combining Human Elicitation and Machine Learning
Morphological Analyzers Combining Human Elicitation Machine Learning
2015/8/26
This paper presents a semiautomatic technique for developing broad-coverage finite-state morphological analyzers for use in natural language processing applications. It consists of three components—el...
Legal Docket-Entry Classification: Where Machine Learning stumbles
Legal Docket-Entry Classification Machine Learning stumbles
2015/6/12
We investigate the problem of binary text classification in the domain of legal docket entries.This work presents an illustrative instance of a domain-specific problem where the stateof-the-art Machin...