Articles

Nilsson and Nivre (2009) introduced a tree- based model of persons’ eye movements in reading. The individual variation between readers reportedly made application across readers impossible. While a tree-based model seems plausible for eye movements, we show that competitive results can be obtained with a linear CRF model. Increasing the …...

Recently, much research focuses on event s- toryline generation, which aims to produce a concise, global and temporal event summary from a collection of articles. Generally, each event contains multiple sub-events and the sto- ryline should be composed by the componen- t summaries of all the sub-events. However, different sub-events …...

Personal profile information on social media like LinkedIn.com and Facebook.com is at the core of many interesting applications, such as talent recommendation and contextual advertis- ing. However, personal profiles usually lack or- ganization confronted with the large amount of available information. Therefore, it is always a challenge for people to …...

A common form of sarcasm on Twitter con- sists of a positive sentiment contrasted with a negative situation. For example, many sarcas- tic tweets include a positive sentiment, such as “love” or “enjoy”, followed by an expression that describes an undesirable activity or state (e.g., “taking exams” or “being ignored”). …...

In this paper we propose a two-stage method to acquire contradiction relations between typed lexico-syntactic patterns such as Xdrug prevents Ydisease and Ydisease caused by Xdrug. In the first stage, we train an SVM classifier to detect contradiction pattern pairs in a large web archive by exploiting the exci- tation …...

Creating a language-independent meaning representation would benefit many cross- lingual NLP tasks. We introduce the first un- supervised approach to this problem, learn- ing clusters of semantically equivalent English and French relations between referring expres- sions, based on their named-entity arguments in large monolingual corpora. The clusters can be used …...

Studies of the graph of dictionary definitions (DD) (Picard et al., 2009; Levary et al., 2012) have revealed strong semantic coherence of local topological structures. The techniques used in these papers are simple and the main results are found by understanding the struc- ture of cycles in the directed graph …...

This study explores the feasibility of perform- ing Chinese word segmentation (CWS) and POS tagging by deep learning. We try to avoid task-specific feature engineering, and use deep layers of neural networks to discover relevant features to the tasks. We leverage large-scale unlabeled data to improve internal representa- tion of …...

We derive a spectral method for unsupervised learning of Weighted Context Free Grammars. We frame WCFG induction as finding a Han- kel matrix that has low rank and is linearly constrained to represent a function computed by inside-outside recursions. The proposed al- gorithm picks the grammar that agrees with a …...

Coreference resolution is a well known clus- tering task in Natural Language Processing. In this paper, we describe the Latent Left Linking model (L3M), a novel, principled, and linguis- tically motivated latent structured prediction approach to coreference resolution. We show that L3M admits efficient inference and can be augmented with …...

We introduce a novel discriminative model for phrase-based monolingual alignment using a semi-Markov CRF. Our model achieves state- of-the-art alignment accuracy on two phrase- based alignment datasets (RTE and para- phrase), while doing significantly better than other strong baselines in both non-identical alignment and phrase-only alignment. Addi- tional experiments highlight …...

In this paper, we analyze a novel set of fea- tures for the task of automatic edit category classification. Edit category classification as- signs categories such as spelling error correc- tion, paraphrase or vandalism to edits in a doc- ument. Our features are based on differences between two versions of …...

While inversion transduction grammar (ITG) is well suited for modeling ordering shifts between languages, how to make applying the two reordering rules (i.e., straight and inverted) dependent on actual blocks being merged remains a challenge. Unlike previous work that only uses boundary words, we pro- pose to use recursive autoencoders …...

This paper describes a factored approach to incorporating soft source syntactic constraints into a hierarchical phrase-based translation system. In contrast to traditional approaches that directly introduce syntactic constraints to translation rules by explicitly decorating them with syntactic annotations, which often ex- acerbate the data sparsity problem and cause other problems, …...

Chinese word segmentation and part-of- speech tagging (S&T) are fundamental steps for more advanced Chinese language processing tasks. Recently, it has at- tracted more and more research interests to exploit heterogeneous annotation cor- pora for Chinese S&T. In this paper, we propose a unified model for Chinese S&T with heterogeneous …...

The performance of nearest neighbor methods is degraded by the presence of hubs, i.e., ob- jects in the dataset that are similar to many other objects. In this paper, we show that the classical method of centering, the transforma- tion that shifts the origin of the space to the data …...

Machine translation benefits from system combination. We propose flexible interaction of hypergraphs as a novel technique combin- ing different translation models within one de- coder. We introduce features controlling the interactions between the two systems and ex- plore three interaction schemes of hiero and forest-to-string models—specification, gener- alization, and interchange. …...

This paper proposes a multi-objective opti- mization framework which supports heteroge- neous information sources to improve align- ment in machine translation system combi- nation techniques. In this area, most of techniques usually utilize confusion networks (CN) as their central data structure to com- pact an exponential number of an potential …...

This paper proposes a novel approach that uti- lizes a machine learning method to improve pivot-based statistical machine translation (SMT). For language pairs with few bilingual data, a possible solution in pivot-based SMT using another language as a "bridge" to gen- erate source-target translation. However, one of the weaknesses is …...

We present a simple and novel classifier-based preordering approach. Unlike existing pre- ordering models, we train feature-rich dis- criminative classifiers that directly predict the target-side word order. Our approach com- bines the strengths of lexical reordering and syntactic preordering models by performing long-distance reorderings using the structure of the parse …...