Articles

Arabic morphology is complex, partly be- cause of its richness, and partly because of common irregular word forms, such as broken plurals (which resemble singular nouns), and nouns with irregular gender (feminine nouns that look masculine and vice versa). In addition, Arabic morpho- syntactic agreement interacts with the lex- ical …...

Microblogging websites such as Twitter offer a wealth of insight into a popu- lation’s current mood. Automated ap- proaches to identify general sentiment to- ward a particular topic often perform two steps: Topic Identification and Sentiment Analysis. Topic Identification first identi- fies tweets that are relevant to a desired topic …...

We present UBY, a large-scale lexical- semantic resource combining a wide range of information from expert-constructed and collaboratively constructed resources for English and German. It currently contains nine resources in two lan- guages: Wikipedia,English WordNet, Wiktionary, FrameNet and VerbNet, German Wikipedia, Wiktionary and GermaNet, and multilingual OmegaWiki modeled according to …...

The search in patent databases is a risky business compared to the search in other domains. A single document that is relevant but overlooked during a patent search can turn into an expensive proposition. While recent research engages in specialized mod- els and algorithms to improve the effective- ness of …...

Text prediction is the task of suggesting text while the user is typing. Its main aim is to reduce the number of keystrokes that are needed to type a text. In this paper, we address the influence of text type and do- main differences on text prediction quality. By training …...

This paper describes Subcat-LMF, an ISO- LMF compliant lexicon representation for- mat featuring a uniform representation of subcategorization frames (SCFs) for the two languages English and German. Subcat-LMF is able to represent SCFs at a very fine-grained level. We utilized Subcat- LMF to standardize lexicons with large- scale SCF information: …...

We evaluate measures of contextual fitness on the task of detecting real-word spelling errors. For that purpose, we extract nat- urally occurring errors and their contexts from the Wikipedia revision history. We show that such natural errors are better suited for evaluation than the previously used artificially created errors. In …...

In this paper we extend our work described in (Dinu et al., 2011) by adding more con- jugational rules to the labelling system in- troduced there, in an attempt to capture the entire dataset of Romanian verbs ex- tracted from (Barbu, 2007), and we em- ploy machine learning techniques to …...

We apply topic modelling to automatically induce word senses of a target word, and demonstrate that our word sense induction method can be used to automatically de- tect words with emergent novel senses, as well as token occurrences of those senses. We start by exploring the utility of stan- dard …...

We present a model of semantic processing of spoken language that (a) is robust against ill-formed input, such as can be expected from automatic speech recognisers, (b) re- spects both syntactic and pragmatic con- straints in the computation of most likely interpretations, (c) uses a principled, ex- pressive semantic representation …...

Whether automatically extracted or human generated, open-domain factual knowledge is often available in the form of semantic annotations (e.g., composed-by) that take one or more specific instances (e.g., rhap- sody in blue, george gershwin) as their ar- guments. This paper introduces a method for converting flat sets of instance-level annotations …...

We investigate the problem of domain adaptation for parallel data in Statistical Machine Translation (SMT). While tech- niques for domain adaptation of monolin- gual data can be borrowed for parallel data, we explore conceptual differences between translation model and language model do- main adaptation and their effect on per- formance, …...

We describe a set of experiments using au- tomatically labelled data to train supervised classifiers for multi-class emotion detection in Twitter messages with no manual inter- vention. By cross-validating between mod- els trained on different labellings for the same six basic emotion classes, and testing on manually labelled data, we …...

We present experiments with part-of- speech tagging for Bulgarian, a Slavic lan- guage with rich inflectional and deriva- tional morphology. Unlike most previous work, which has used a small number of grammatical categories, we work with 680 morpho-syntactic tags. We combine a large morphological lexicon with prior linguis- tic knowledge …...

It is not always clear how the differences in intrinsic evaluation metrics for a parser or classifier will affect the performance of the system that uses it. We investigate the relationship between the intrinsic evalua- tion scores of an interpretation component in a tutorial dialogue system and the learn- ing …...

In this paper, we extend the work on using latent cross-language topic models for iden- tifying word translations across compara- ble corpora. We present a novel precision- oriented algorithm that relies on per-topic word distributions obtained by the bilin- gual LDA (BiLDA) latent topic model. The algorithm aims at harvesting …...

Previous work on treebank parsing with discontinuous constituents using Linear Context-Free Rewriting systems (LCFRS) has been limited to sentences of up to 30 words, for reasons of computational com- plexity. There have been some results on binarizing an LCFRS in a manner that min- imizes parsing complexity, but the present …...

In this paper, we address statistical ma- chine translation of public conference talks. Modeling the style of this genre can be very challenging given the shortage of available in-domain training data. We investigate the use of a hybrid LM, where infrequent words are mapped into classes. Hybrid LMs are used …...

Coordination disambiguation remains a dif- ficult sub-problem in parsing despite the frequency and importance of coordination structures. We propose a method for disam- biguating coordination structures. In this method, dual decomposition is used as a framework to take advantage of both HPSG parsing and coordinate structure analysis with alignment-based local …...

Kernel based methods dominate the current trend for various relation extraction tasks including protein-protein interaction (PPI) extraction. PPI information is critical in un- derstanding biological processes. Despite considerable efforts, previously reported PPI extraction results show that none of the approaches already known in the literature is consistently better than other …...