Articles

Online discussion forums are a valuable means for users to resolve specific information needs, both interactively for the participants and statically for users who search/browse over historical thread data. However, the com- plex structure of forum threads can make it difficult for users to extract relevant informa- tion. The discourse …...

In this paper we present ULISSE, an unsu- pervised linguistically–driven algorithm to se- lect reliable parses from the output of a de- pendency parser. Different experiments were devised to show that the algorithm is robust enough to deal with the output of different parsers and with different languages, as well …...

Feature feedback is an alternative to instance labeling when seeking supervision from hu- man experts. Combination of instance and feature feedback has been shown to reduce the total annotation cost for supervised learning. However, learning problems may not benefit equally from feature feedback. It is well un- derstood that the …...

We present a computational model of lan- guage learning via a sequence of interactions between a teacher and a learner. Experiments learning limited sublanguages of 10 natural languages show that the learner achieves a high level of performance after a reasonable number of interactions, the teacher can pro- duce meaning-preserving …...

Sociolinguistic theories (e.g., Lakoff (1973)) postulate that women’s language styles differ from that of men. In this paper, we explore statistical techniques that can learn to iden- tify the gender of authors in modern English text, such as web blogs and scientific papers. Although recent work has shown the efficacy …...

Subjectivity word sense disambiguation (SWSD) is automatically determining which word instances in a corpus are being used with subjective senses, and which are being used with objective senses. SWSD has been shown to improve the performance of contextual opinion analysis, but only on a small scale and using manually developed …...

Crisis-affected populations are often able to maintain digital communications but in a sudden-onset crisis any aid organizations will have the least free resources to process such communications. Information that aid agen- cies can actually act on, ‘actionable’ informa- tion, will be sparse so there is great poten- tial to (semi)automatically …...

Automatic extraction of opinion holders and targets (together referred to as opinion entities) is an important subtask of senti- ment analysis. In this work, we attempt to accurately extract opinion entities from Urdu newswire. Due to the lack of re- sources required for training role labelers and dependency parsers (as …...

We develop an approach to biomedical event extraction using a search-based structured pre- diction framework, SEARN, which converts the task into cost-sensitive classification tasks whose models are learned jointly. We show that SEARN improves on a simple yet strong pipeline by 8.6 points in F-score on the BioNLP 2009 shared …...

While many computational models have been created to explore how children might learn to segment words, the focus has largely been on achieving higher levels of performance and exploring cues suggested by artificial learning experiments. We propose a broader focus that includes designing models that display prop- erties of infants’ …...

We show how punctuation can be used to im- prove unsupervised dependency parsing. Our linguistic analysis confirms the strong connec- tion between English punctuation and phrase boundaries in the Penn Treebank. However, approaches that naively include punctuation marks in the grammar (as if they were words) do not perform well …...

We use an automatic pipeline of word tokenization, stemming, POS tagging, and vocalization to perform real-world Arabic dependency parsing. In spite of the high accuracy on the modules, the very few errors in tokenization, which reaches an accuracy of 99.34%, lead to a drop of more than 10% in parsing, …...

The connection between part-of-speech (POS) categories and morphological properties is well-documented in linguistics but underuti- lized in text processing systems. This pa- per proposes a novel model for morphologi- cal segmentation that is driven by this connec- tion. Our model learns that words with com- mon affixes are likely to …...

During language acquisition, children learn to segment speech into phonemes, syllables, morphemes, and words. We examine word segmentation specifically, and explore the possibility that children might have general- purpose chunking mechanisms to perform word segmentation. The Voting Experts (VE) and Bootstrapped Voting Experts (BVE) algo- rithms serve as computational models …...

This paper shows that the performance of history-based models can be significantly im- proved by performing lookahead in the state space when making each classification deci- sion. Instead of simply using the best ac- tion output by the classifier, we determine the best action by looking into possible se- quences …...

Natural language systems trained on labeled data from one domain do not perform well on other domains. Most adaptation algorithms proposed in the literature train a new model for the new domain using unlabeled data. How- ever, it is time consuming to retrain big mod- els or pipeline systems. Moreover, …...

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 this world in a human manner. We present a simple yet effec- tive approach …...

We describe the extension and objective eval- uation of a network1 of semantically related noun senses (or concepts) that has been au- tomatically acquired by analyzing lexical co- occurrence in Wikipedia. The acquisition pro- cess makes no use of the metadata or links that have been manually built into the …...

The problem of authorship attribution – at- tributing texts to their original authors – has been an active research area since the end of the 19th century, attracting increased interest in the last decade. Most of the work on au- thorship attribution focuses on scenarios with only a few candidate …...

This paper makes two contributions to the area of single-word based word alignment for bilingual sentence pairs. Firstly, it integrates the – seemingly rather different – works of (Bodrumlu et al., 2009) and the standard prob- abilistic ones into a single framework. Secondly, we present two algorithms to opti- mize …...