Articles

A method for deriving an approximately labeled dependency treebank from the Thai Categorial Grammar Treebank has been implemented. The method involves a lexical dictionary for assigning depen- dency directions to the CG types associ- ated with the grammatical entities in the CG bank, falling back on a generic map- ping …...

Treebanks are valuable resources for nat- ural language processing (NLP). There is much work in NLP which converts treebanks from one representation (e.g., phrase structure) to another (e.g., depen- dency) before applying machine learning. This paper provides a framework in which to think about the question of when such a …...

This paper presents work on extending the ad- verbial entries of LGLex, a NLP oriented syn- tactic resource for French. Adverbs were ex- tracted from the Lexicon-Grammar tables of both simple adverbs ending in –ment „–ly‟ (Molinier and Levrier, 2000) and compound adverbs (Gross, 1986; 1990). This work relies on …...

In this paper, we first carry out an investi- gation on two existing pivot strategies for statistical machine transliteration, namely system-based and model-based strategies, to figure out the reason why the previous model-based strategy performs much worse than the system-based one. We then propose a joint alignment algorithm to op- …...

We propose a bootstrapping algorithm which successfully resolves two funda- mental tasks: morphology acquisition and the acquisition of a subset of functional words. Given the outputs of these funda- mental tasks, we build a nearly state-of-art morphology analyzer performing with a F1-score of 80.94%; also, we can improve the baseline …...

There is serious data sparseness problem in Chinese dictionary stored in a double- array trie. This paper proposes six com- pression methods by code mapping and code dividing to make it more compact, and a metric called Resource Consump- tion Ratio is proposed to evaluate these methods. Under the proposed …...

We propose a new subjectivity classi- fication at the segment level that is more appropriate for discourse-based sen- timent analysis. Our approach automati- cally distinguish between subjective non- evaluative and objective segments and be- tween implicit and explicit opinions, by using local and global context features. 1...

In this paper, we shall introduce a system for extracting the keyphrases for the rea- son of authors’ opinion from product re- views. The datasets for two fairly different product review domains related to movies and mobile phones were constructed semi- automatically based on the pros and cons entered by …...

Existing research on sentiment analysis mainly uses sentiment words and phrases to determine sentiments expressed in documents and sen- tences. Techniques have also been developed to find such words and phrases using dictiona- ries and domain corpora. However, there are still other types of words and phrases that do not …...

s Written in Portuguese Vin´ıcius Mour˜ao Alves de Souza State University of Maring´a Maring´a, PR, Brazil, 87020-900 vsouza@din.uem.br Val´eria Delisandra Feltrim State University of Maring´a Maring´a, PR, Brazil, 87020-900 valeria.feltrim@din.uem.br Abstract SciPo is a system whose ultimate goal is to support novice writers in produc- ing academic texts in Brazilian …...

This paper presents a hierarchical Bayesian model based on latent Dirichlet allocation (LDA), called subjLDA, for sentence-level subjectivity detection, which automatically identifies whether a given sentence expresses opinion or states facts. In contrast to most of the existing methods relying on either labelled corpora for classifier train- ing or linguistic …...

We present a model that represents word meaning in context by vectors which are modified according to the words in the tar- get’s syntactic context. Contextualization of a vector is realized by reweighting its components, based on distributional infor- mation about the context words. Evalua- tion on a paraphrase ranking …...

This paper describes a new Markov Logic approach for Japanese Predicate-Argument (PA) relation extraction. Most previous work built separated classifiers correspond- ing to each case role and independently identified the PA relations, neglecting de- pendencies (constraints) between two or more PA relations. We propose a method which collectively extracts PA …...

Domain adaptation (DA), which involves adapting a classifier developed from source to target data, has been studied intensively in recent years. However, when DA for word sense disambiguation (WSD) was carried out, the optimal DA method varied according to the properties of the source and target data. This pa- per …...

Multi-modality manifold-ranking is re- cently used successfully in topic-focused multi-document summarization. This ap- proach is based on Bag-Of-Words (BOW) assumption where the pair-wise similar- ity values between sentences are computed using the standard cosine similarity mea- sure (TF*IDF). However, the major lim- itation of the TF*IDF approach is that it …...

Relational lasso is a method that incor- porates feature relations within machine learning. By using automatically obtained noisy relations among features, relational lasso learns an additional penalty parame- ter per feature, which is then incorporated in terms of a regularizer within the target optimization function. Relational lasso has been tested …...

Recent large-scale hierarchical classifica- tion tasks typically have tens of thousand- s of classes as well as a large number of samples, for which the dominant solution is the top-down method due to computa- tional complexity. However, the top-down method suffers from accuracy deficiency, that is, its accuracy is generally …...

Parsing discourse is a challenging natural language processing task. In this paper we take a data driven approach to iden- tify arguments of explicit discourse con- nectives. In contrast to previous work we do not make any assumptions on the span of arguments and consider parsing as a token-level sequence …...

We address the problem of joint part-of-speech (POS) tagging and dependency parsing in Chi- nese. In Chinese, some POS tags are often hard to disambiguate without considering long- range syntactic information. Also, the traditional pipeline approach to POS tagging and depen- dency parsing may suffer from the problem of error …...

We present results from improving vec- tor space based extraction summarizers. The summarizer uses Random Indexing and Page Rank to extract those sentences whose importance are ranked highest for a document, based on vector similarity. Originally the summarizer used only word vectors based on the words in the docu- ment …...