Articles

We explore Debatepedia, a community- authored encyclopedia of sociopolitical de- bates, as evidence for inferring a low- dimensional, human-interpretable representa- tion in the domain of issues and positions. We introduce a generative model positing latent topics and cross-cutting positions that gives special treatment to person mentions and opin- ion words. …...

A very valuable piece of information in news- paper articles is the tonality of extracted state- ments. For the analysis of tonality of newspa- per articles either a big human effort is needed, when it is carried out by media analysts, or an automated approach which has to be as …...

Different demographics, e.g., gender or age, can demonstrate substantial variation in their language use, particularly in informal contexts such as social media. In this paper we focus on learning gender differences in the use of sub- jective language in English, Spanish, and Rus- sian Twitter data, and explore cross-cultural differences …...

Event schema induction is the task of learning high-level representations of complex events (e.g., a bombing) and their entity roles (e.g., perpetrator and victim) from unlabeled text. Event schemas have important connections to early NLP research on frames and scripts, as well as modern applications like template extraction. Recent research …...

Wikification, commonly referred to as Disam- biguation to Wikipedia (D2W), is the task of identifying concepts and entities in text and disambiguating them into the most specific corresponding Wikipedia pages. Previous ap- proaches to D2W focused on the use of lo- cal and global statistics over the given text, Wikipedia …...

The distributional hypothesis, which states that words that occur in similar contexts tend to have similar meanings, has inspired sev- eral Web mining algorithms for paraphras- ing semantically equivalent phrases. Unfortu- nately, these methods have several drawbacks, such as confusing synonyms with antonyms and causes with effects. This paper intro- …...

Microblog messages pose severe challenges for current sentiment analysis techniques due to some inherent characteristics such as the length limit and informal writing style. In this paper, we study the problem of extracting opinion targets of Chinese microblog messag- es. Such fine-grained word-level task has not been well investigated in …...

This paper introduces IQPs (Integer Quadratic Programs) as a way to model joint inference for the task of concept recognition in clinical domain. IQPs make it possible to easily in- corporate soft constraints in the optimization framework and still support exact global infer- ence. We show that soft constraints give …...

Previous approaches for automated essay scoring (AES) learn a rating model by min- imizing either the classification, regression, or pairwise classification loss, depending on the learning algorithm used. In this paper, we argue that the current AES systems can be further improved by taking into account the agreement between human …...

Cross-lingual topic modelling has applications in machine translation, word sense disam- biguation and terminology alignment. Multi- lingual extensions of approaches based on la- tent (LSI), generative (LDA, PLSI) as well as explicit (ESA) topic modelling can induce an interlingual topic space allowing documents in different languages to be mapped into …...

We develop a novel generative model of con- versation that jointly captures both the top- ical content and the speech act type asso- ciated with each utterance. Our model ex- presses both token emission and state tran- sition probabilities as log-linear functions of separate components corresponding to topics and speech …...

Chambers and Jurafsky (2009) demonstrated that event schemas can be automatically in- duced from text corpora. However, our analy- sis of their schemas identifies several weak- nesses, e.g., some schemas lack a common topic and distinct roles are incorrectly mixed into a single actor. It is due in part to …...

We present an approach to learning bilin- gual n-gram correspondences from relevance rankings of English documents for Japanese queries. We show that directly optimizing cross-lingual rankings rivals and complements machine translation-based cross-language in- formation retrieval (CLIR). We propose an ef- ficient boosting algorithm that deals with very large cross-product spaces …...

We introduce a class of probabilistic con- tinuous translation models called Recur- rent Continuous Translation Models that are purely based on continuous representations for words, phrases and sentences and do not rely on alignments or phrasal translation units. The models have a generation and a condi- tioning aspect. The generation …...

Translation into morphologically rich lan- guages is an important but recalcitrant prob- lem in MT. We present a simple and effec- tive approach that deals with the problem in two phases. First, a discriminative model is learned to predict inflections of target words from rich source-side annotations. Then, this model …...

We introduce dependency relations into deci- phering foreign languages and show that de- pendency relations help improve the state-of- the-art deciphering accuracy by over 500%. We learn a translation lexicon from large amounts of genuinely non parallel data with decipherment to improve a phrase-based ma- chine translation system trained with …...

Aspect extraction is one of the key tasks in sentiment analysis. In recent years, statistical models have been used for the task. However, such models without any domain knowledge often produce aspects that are not interpreta- ble in applications. To tackle the issue, some knowledge-based topic models have been proposed, …...

We propose a novel approach to sentiment analysis for a low resource setting. The in- tuition behind this work is that sentiment expressed towards an entity, targeted senti- ment, may be viewed as a span of sentiment expressed across the entity. This represen- tation allows us to model sentiment detec- …...

Predicting the success of literary works is a curious question among publishers and aspir- ing writers alike. We examine the quantitative connection, if any, between writing style and successful literature. Based on novels over several different genres, we probe the predic- tive power of statistical stylometry in discrim- inating successful …...

Continuous space word representations ex- tracted from neural network language mod- els have been used effectively for natural lan- guage processing, but until recently it was not clear whether the spatial relationships of such representations were interpretable. Mikolov et al. (2013) show that these representations do capture syntactic and semantic …...