Articles

In current dependency parsing models, con- ventional features (i.e. base features) defined over surface words and part-of-speech tags in a relatively high-dimensional feature space may suffer from the data sparseness problem and thus exhibit less discriminative power on unseen data. In this paper, we propose a novel semi-supervised approach to …...

Describing the main event of an image in- volves identifying the objects depicted and predicting the relationships between them. Previous approaches have represented images as unstructured bags of regions, which makes it difficult to accurately predict meaningful relationships between regions. In this pa- per, we introduce visual dependency represen- tations …...

The rapid development of Web2.0 leads to significant information redundancy. Espe- cially for a complex news event, it is diffi- cult to understand its general idea within a single coherent picture. A complex event of- ten contains branches, intertwining narratives and side news which are all called storylines. In this …...

Building search engines that can respond to spoken queries with spoken content requires that the system not just be able to find useful responses, but also that it know when it has heard enough about what the user wants to be able to do so. This paper describes a simula- …...

Assigning a positive or negative score to a word out of context (i.e. a word’s prior polar- ity) is a challenging task for sentiment analy- sis. In the literature, various approaches based on SentiWordNet have been proposed. In this paper, we compare the most often used tech- niques together with …...

This paper presents a novel approach to deter- mine textual similarity. A layered methodol- ogy to transform text into logic forms is pro- posed, and semantic features are derived from a logic prover. Experimental results show that incorporating the semantic structure of sen- tences is beneficial. When training data is …...

We present a method for automatically acquir- ing knowledge for case alternation between the passive and active voices in Japanese. By leveraging several linguistic constraints on al- ternation patterns and lexical case frames ob- tained from a large Web corpus, our method aligns a case frame in the passive voice …...

A precise syntacto-semantic analysis of En- glish requires a large detailed lexicon with the possibility of treating multiple tokens as a sin- gle meaning-bearing unit, a word-with-spaces. However parsing with such a lexicon, as in- cluded in the English Resource Grammar, can be very slow. We show that we can …...

In this paper we report an empirical study on semi-supervised Chinese word segmenta- tion using co-training. We utilize two seg- menters: 1) a word-based segmenter lever- aging a word-level language model, and 2) a character-based segmenter using character- level features within a CRF-based sequence labeler. These two segmenters are initially …...

One of the language phenomena that n-gram language model fails to capture is the topic in- formation of a given situation. We advance the previous study of the Bayesian topic language model by Wallach (2006) in two directions: one, investigating new priors to alleviate the sparseness problem caused by dividing …...

NLP models have many and sparse features, and regularization is key for balancing model overfitting versus underfitting. A recently re- popularized form of regularization is to gen- erate fake training data by repeatedly adding noise to real data. We reinterpret this noising as an explicit regularizer, and approximate it with …...

Hypernym discovery aims to extract such noun pairs that one noun is a hypernym of the other. Most previous methods are based on lexical patterns but perform badly on open- domain data. Other work extracts hypernym relations from encyclopedias but has limited coverage. This paper proposes a simple yet ef- …...

Why do certain combinations of words such as “disadvantageous peace” or “metal to the petal” appeal to our minds as interesting ex- pressions with a sense of creativity, while other phrases such as “quiet teenager”, or “geometrical base” not as much? We present statistical explorations to understand the char- acteristics …...

It has recently been shown that different NLP models can be effectively combined using dual decomposition. In this paper we demon- strate that PCFG-LA parsing models are suit- able for combination in this way. We exper- iment with the different models which result from alternative methods of extracting a gram- …...

While much work has considered the problem of latent attribute inference for users of social media such as Twitter, little has been done on non-English-based content and users. Here, we conduct the first assessment of latent at- tribute inference in languages beyond English, focusing on gender inference. We find that …...

Recent investigations into grounded models of language have shown that holistic views of language and perception can provide higher performance than independent views. In this work, we improve a two-dimensional multi- modal version of Latent Dirichlet Allocation (Andrews et al., 2009) in various ways. (1) We outperform text-only models in …...

This paper studies the problem of identifying users who use multiple userids to post in so- cial media. Since multiple userids may belong to the same author, it is hard to directly apply supervised learning to solve the problem. This paper proposes a new method, which still uses supervised learning …...

While large-scale discriminative training has triumphed in many NLP problems, its defi- nite success on machine translation has been largely elusive. Most recent efforts along this line are not scalable (training on the small dev set with features from top ∼100 most fre- quent words) and overly complicated. We in- …...

This paper addresses the problem of produc- ing a diverse set of plausible translations. We present a simple procedure that can be used with any statistical machine translation (MT) system. We explore three ways of using di- verse translations: (1) system combination, (2) discriminative reranking with rich features, and (3) …...

We present a novel translation model, which simultaneously exploits the constituency and dependency trees on the source side, to com- bine the advantages of two types of trees. We take head-dependents relations of dependency trees as backbone and incorporate phrasal n- odes of constituency trees as the source side of …...