Articles

This paper discusses a new approach to training of transliteration model from unlabeled data for transliteration extraction. We start with an inquiry into the formulation of transliteration model by considering different transliteration strategies as a multi-view problem, where each view exploits a natural division of transliteration features, such as phoneme- …...

We propose a method for learning semantic categories of words with minimal supervi- sion from web search query logs. Our me- thod is based on the Espresso algorithm (Pantel and Pennacchiotti, 2006) for ex- tracting binary lexical relations, but makes important modifications to handle query log data for the task …...

We propose a method that incorporates paraphrase information from the Web to boost the performance of a supervised re- lation extraction system. Contextual infor- mation is extracted from the Web using a semi-supervised process, and summarized by skip-bigram overlap measures over the entire extract. This allows the capture of lo- …...

We describe our effort in developing a Named Entity Recognition (NER) system for Hindi using Maximum Entropy (Max- Ent) approach. We developed a NER an- notated corpora for the purpose. We have tried to identify the most relevant features for Hindi NER task to enable us to develop an efficient …...

This study presents a method to automat- ically acquire paraphrases using bilingual corpora, which utilizes the bilingual de- pendency relations obtained by projecting a monolingual dependency parse onto the other language sentence based on statisti- cal alignment techniques. Since the para- phrasing method is capable of clearly disam- biguating the …...

Chinese named entity recognition (NER) has re- cently been viewed as a classification or sequence labeling problem, and many approaches have been proposed. However, they tend to address this problem without considering linguistic informa- tion in Chinese NEs. We propose a new framework based on probabilistic graphical models with first- …...

Recognizing the emotive meaning of text can add another dimension to the under- standing of text. We study the task of automatically categorizing sentences in a text into Ekman’s six basic emotion cate- gories. We experiment with corpus-based features as well as features derived from two emotion lexicons. One lexicon …...

Combining different metrics into a single measure of quality seems the most direct and natural way to improve over the quality of individual metrics. Recently, several ap- proaches have been suggested (Kulesza and Shieber, 2004; Liu and Gildea, 2007; Al- brecht and Hwa, 2007a). Although based on different assumptions, these …...

In this paper, we address the problem of knowing when to stop the process of active learning. We propose a new statistical learning approach, called minimum expected error strategy, to defining a stopping criterion through estimation of the classifier’s expected error on future unlabeled examples in the active learning process. …...

We address the problem of sentiment and objectivity classification of product re- views in Chinese. Our approach is distinct- ive in that it treats both positive / negative sentiment and subjectivity / objectivity not as distinct classes but rather as a con- tinuum; we argue that this is desirable from …...

We propose a machine learning based method of sentiment classification of sen- tences using word-level polarity. The polari- ties of words in a sentence are not always the same as that of the sentence, because there can be polarity-shifters such as negation ex- pressions. The proposed method models the polarity-shifters. …...

We consider the problem of 1 identifying product features and opinion words in a unified process from Chinese customer re- views when only a much small seed set of opinion words is available. In particular, we consider a problem setting motivated by the task of identifying product features with opinion …...

Named entity (NE) translation plays an important role in many applications. In this paper, we focus on translating NEs from Korean to Chinese to improve Korean-Chinese cross-language informa- tion retrieval (KCIR). The ideographic nature of Chinese makes NE translation difficult because one syllable may map to several Chinese characters. We …...

Searching and reading the Web is one of the principal methods used to seek out infor- mation to resolve problems about technol- ogy in general and digital devices in partic- ular. This paper addresses the problem of text mining in the digital devices domain. In particular, we address the task …...

We analyze the linguistic behaviour of par- ticipants in bilateral electronic negotiations, and discover that particular language char- acteristics are in contrast with face-to-face negotiations. Language patterns in the later part of electronic negotiation are highly in- dicative of the successful or unsuccessful outcome of the process, whereas in face-to- …...

An approach to solving the problem of au- tomatic briefing generation from non-textual events can be segmenting the task into two major steps, namely, extraction of briefing templates and learning aggregators that col- late information from events and automati- cally fill up the templates. In this paper, we describe two …...

Most of the current Chinese word alignment tasks often adopt word segmentation systems firstly to identify words. However, word-mismatching problems exist between languages and will degrade the performance of word alignment. In this paper, we propose two unsupervised methods to adjust word segmentation to make the tokens 1-to-1 mapping as …...

In human translation, translators first make draft translations and then modify them. This paper analyses these modifications, in order to identify the features that trigger modification. Our goal is to construct a sys- tem that notifies (English-to-Japanese) vol- unteer translators of awkward translations. After manually classifying the basic modifi- cation …...

We propose a new method of selecting hy- potheses for machine transliteration. We generate a set of Chinese, Japanese, and Ko- rean transliteration hypotheses for a given English word. We then use the set of translit- eration hypotheses as a guide to finding rel- evant Web pages and mining contextual …...

We propose a general approach for trans- lating Chinese unknown words (UNK) for SMT. This approach takes advantage of the properties of Chinese word composition rules, i.e., all Chinese words are formed by sequential characters. According to the proposed approach, the unknown word is re-split into a subword sequence followed …...