Articles

The anchor words algorithm performs provably efficient topic model inference by finding an approximate convex hull in a high-dimensional word co-occurrence space. However, the existing greedy al- gorithm often selects poor anchor words, reducing topic quality and interpretability. Rather than finding an approximate con- vex hull in a high-dimensional space, …...

We present a model for the automatic se- mantic analysis of requirements elicitation documents. Our target semantic repre- sentation employs live sequence charts, a multi-modal visual language for scenario- based programming, which can be directly translated into executable code. The ar- chitecture we propose integrates sentence- level and discourse-level processing …...

In this paper, we demonstrate that significant performance gains can be achieved in CCG semantic parsing by introducing a linguistically moti- vated grammar induction scheme. We present a new morpho-syntactic fac- tored lexicon that models systematic variations in morphology, syntax, and semantics across word classes. The grammar uses domain-independent facts …...

We present methods to control the lexicon size when learning a Combinatory Cate- gorial Grammar semantic parser. Existing methods incrementally expand the lexicon by greedily adding entries, considering a single training datapoint at a time. We pro- pose using corpus-level statistics for lexi- con learning decisions. We introduce vot- ing …...

Numerous works in Statistical Machine Translation (SMT) have attempted to iden- tify better translation hypotheses obtained by an initial decoding using an improved, but more costly scoring function. In this work, we introduce an approach that takes the hypotheses produced by a state-of- the-art, reranked phrase-based SMT sys- tem, and …...

Recent work by Cherry (2013) has shown that directly optimizing phrase-based re- ordering models towards BLEU can lead to significant gains. Their approach is lim- ited to small training sets of a few thou- sand sentences and a similar number of sparse features. We show how the ex- pected BLEU …...

s Identifying parallel web pages from bi- lingual web sites is a crucial step of bi- lingual resource construction for cross- lingual information processing. In this paper, we propose a link-based approach to distinguish parallel web pages from bi- lingual web sites. Compared with the ex- isting methods, which only …...

Analyses of computer aided translation typi- cally focus on either frontend interfaces and human effort, or backend translation and machine learnability of corrections. How- ever, this distinction is artificial in prac- tice since the frontend and backend must work in concert. We present the first holis- tic, quantitative evaluation of …...

The combinatorial space of translation derivations in phrase-based statistical ma- chine translation is given by the intersec- tion between a translation lattice and a tar- get language model. We replace this in- tractable intersection by a tractable relax- ation which incorporates a low-order up- perbound on the language model. Exact …...

We put forward the hypothesis that high- accuracy sentiment analysis is only pos- sible if word senses with different polar- ity are accurately recognized. We pro- vide evidence for this hypothesis in a case study for the adjective “hard” and propose contextually enhanced sentiment lexicons that contain the information necessary …...

We present a weakly supervised approach for learning hashtags, hashtag patterns, and phrases associated with five emotions: AFFEC- TION, ANGER/RAGE, FEAR/ANXIETY, JOY, and SADNESS/DISAPPOINTMENT. Starting with seed hashtags to label an initial set of tweets, we train emotion classifiers and use them to learn new emotion hashtags and hash- tag …...

Recently, work in NLP was initiated on a type of opinion inference that arises when opinions are expressed toward events which have positive or negative effects on entities (+/-effect events). This paper addresses methods for creating a lexicon of such events, to support such work on opinion inference. Due to …...

Casual online forums such as Reddit, Slashdot and Digg, are continuing to in- crease in popularity as a means of com- munication. Detecting disagreement in this domain is a considerable challenge. Many topics are unique to the conversa- tion on the forum, and the appearance of disagreement may be much …...

Microblog has become a major plat- form for information about real-world events. Automatically discovering real- world events from microblog has attracted the attention of many researchers. Howev- er, most of existing work ignore the impor- tance of emotion information for event de- tection. We argue that people’s emotion- al reactions …...

Dependency parsing is a core task in NLP, and it is widely used by many applica- tions such as information extraction, ques- tion answering, and machine translation. In the era of social media, a big chal- lenge is that parsers trained on traditional newswire corpora typically suffer from the domain …...

In this paper we first exploit cash-tags (“$” fol- lowed by stocks’ ticker symbols) in Twitter to build a stock network, where nodes are stocks connected by edges when two stocks co-occur frequently in tweets. We then employ a labeled topic model to jointly model both the tweets and the …...

Demographic lexica have potential for widespread use in social science, economic, and business applications. We derive predic- tive lexica (words and weights) for age and gender using regression and classification models from word usage in Facebook, blog, and Twitter data with associated demographic labels. The lexica, made publicly available,1 achieved …...

A poll consists of a question and a set of predefined answers from which voters can select. We present the new problem of vote prediction on comments, which involves determining which of these answers a voter selected given a comment she wrote after voting. To address this task, we ex- …...

Estimating questions’ difficulty levels is an important task in community question answering (CQA) services. Previous stud- ies propose to solve this problem based on the question-user comparisons extract- ed from the question answering threads. However, they suffer from data sparseness problem as each question only gets a lim- ited number …...

Much recent work focuses on formal in- terpretation of natural question utterances, with the goal of executing the resulting structured queries on knowledge graphs (KGs) such as Freebase. Here we address two limitations of this approach when ap- plied to open-domain, entity-oriented Web queries. First, Web queries are rarely well- …...