Articles

We study a problem with pairwise ranking optimization (PRO): that it tends to yield too short translations. We find that this is partially due to the inadequate smoothing in PRO’s BLEU+1, which boosts the precision component of BLEU but leaves the brevity penalty unchanged, thus destroying the balance between the …...

The paper presents results of clustering terms extracted from economic articles in Polish Wikipedia. First, we describe the method of automatic term extraction supported by linguistic knowledge. Then, we define different types of term similarities used in the clustering experiment. Term similarities are based on Polish Wordnet and morphosyntactic analysis …...

One of the main issues in a word alignment task is the difficulty of handling function words that do not have direct translations which we call unique function words. They are often aligned to some words in the other language incorrectly. This is prominent in language pairs with very different …...

In this paper, we introduce an application of matrix factorization to produce corpus-derived, distribu- tional models of semantics that demonstrate cognitive plausibility. We find that word representations learned by Non-Negative Sparse Embedding (NNSE), a variant of matrix factorization, are sparse, effective, and highly interpretable. To the best of our knowledge, …...

In this paper, we propose the use of spans in addition to edges in noun compound analysis. A span is a sequence of words that can represent a noun compound. Compared with edges, spans have good properties in terms of semi-supervised parsing. They can be reliably extracted from a huge …...

This paper presents a supervised machine learning approach to incrementally learn and segment affixes using generic background knowledge. We used Prolog script to split affixes from the Amharic word for further morphological analysis. Amharic, a Semitic language, has very complex inflectional and derivational verb morphology, with many possible prefixes and …...

This paper presents a novel approach to document-based discourse analysis by performing a global A* search over the space of possible structures while optimizing a global criterion over the set of potential coherence relations. Existing approaches to discourse analysis have so far relied on greedy search strategies or restricted themselves …...

In this paper, we propose a weakly supervised system, YouCat, for categorizing Youtube videos into different genres like Comedy, Horror, Romance, Sports and Technology The system takes a Youtube video url as input and gives it a belongingness score for each genre. The key aspects of this work can be …...

We propose a lightweight method for using discourse relations for polarity detection of tweets. This method is targeted towards the web-based applications that deal with noisy, unstructured text, like the tweets, and cannot afford to use heavy linguistic resources like parsing due to frequent failure of the parsers to handle …...

Psycholinguistic phenomenon of communication accommodation (Giles et al., 1991) is probably one of the most important contributions in the interdisciplinary field of linguistics, psychology, information, and communication theory. Existing works have applied this theory to various domains like gesture, linguistics, backchannels, and even social media like tweets. In this work, …...

In this paper, we present a new method that improves the alignment of equivalent terms monolingually acquired from bilingual comparable corpora: the Compositional Method with Context-Based Projection (CMCBP). Our overall objective is to identify and to translate high specialized terminology made up of multi-word terms acquired from comparable corpora. Our …...

In the present work we raise the hypothesis that eye-movements when reading texts reveal task performance, as measured by the level of understanding of the reader. With the objective of testing that hypothesis, we introduce a framework to integrate geometric information of eye-movements and text layout into natural language processing …...

The easy-first non-directional dependency parser has demonstrated its advantage over transition based dependency parsers which parse sentences from left to right. This work investigates easy-first method on Chinese POS tagging, dependency parsing and joint tagging and dependency parsing. In particular, we generalize the easy-first dependency parsing algorithm to a general …...

We study the multi-tweet summarization task, which aims to find representative tweets from a given set of tweets. Multi-tweet summarization allows people to quickly grasp the essential meaning of a large number of tweets. It can also be used as a pre-processing component for information extraction tasks on tweets. The …...

Recent study shows that parsing accuracy can be largely improved by the joint optimization of part-of-speech (POS) tagging and dependency parsing. However, the POS tagging task does not benefit much from the joint framework. We argue that the fundamental reason behind is because the POS features are overwhelmed by the …...

Features for Robust Cross-Domain Chinese Word Segmentation LI Xiaoqing1, WANG Kun1, ZONG Chengqing1 and SU Keh-Yih2 (1) National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China (2) Behavior Design Corporation, Taiwan {xqli, kunwang, cqzong}@nlpr.ia.ac.cn, kysu@bdc.com.tw ABSTRACT Current character-based approaches are not robust for cross domain …...

Currently, Chinese event extraction systems suffer much from the low quality of annotated event corpora and the high ratio of pseudo trigger mentions to true ones. To resolve these two issues, this paper proposes a joint model of trigger identification and event type determination. Besides, several trigger filtering schemas are …...

Current Chinese event extraction systems suffer much from the low recall due to unknown triggers. To resolve this problem, this paper firstly introduces morphological structures to better represent the compositional semantics inside Chinese triggers and then proposes a mechanism to automatically identify the head morpheme (either verb or noun) as …...

There are many abbreviation and non-standard tokens in SMS and Twitter messages. Nor- malizing these non-standard tokens will ease natural language processing modules for these domains. Recently, character-level machine translation (MT) and sequence labeling methods have been used for this normalization task, and demonstrated competitive performance. In this paper, we …...

Update summarization is a new challenge which combines salience ranking with novelty detection. Previous researches usually convert novelty detection to the problem of redundancy removal or salience re-ranking, and seldom explore the birth, splitting, merging and death of aspects for a given topic. In this paper, we borrow the idea …...