Articles

We propose to directly measure the impor- tance of queries in the source domain to the target domain where no rank labels of doc- uments are available, which is referred to as query weighting. Query weighting is a key step in ranking model adaptation. As the learning object of ranking …...

Marking up search queries with linguistic an- notations such as part-of-speech tags, cap- italization, and segmentation, is an impor- tant part of query processing and understand- ing in information retrieval systems. Due to their brevity and idiosyncratic structure, search queries pose a challenge to existing NLP tools. To address this …...

Searching documents that are similar to a query document is an important component in modern information retrieval. Some ex- isting hashing methods can be used for effi- cient document similarity search. However, unsupervised hashing methods cannot incor- porate prior knowledge for better hashing. Although some supervised hashing methods can derive …...

We consider a semi-supervised setting for do- main adaptation where only unlabeled data is available for the target domain. One way to tackle this problem is to train a generative model with latent variables on the mixture of data from the source and target domains. Such a model would cluster …...

We describe an exact decoding algorithm for syntax-based statistical translation. The ap- proach uses Lagrangian relaxation to decom- pose the decoding problem into tractable sub- problems, thereby avoiding exhaustive dy- namic programming. The method recovers ex- act solutions, with certificates of optimality, on over 97% of test examples; it has …...

This paper proposes a new method for ap- proximate string search, specifically candidate generation in spelling error correction, which is a task as follows. Given a misspelled word, the system finds words in a dictionary, which are most “similar” to the misspelled word. The paper proposes a probabilistic approach to …...

Active Learning (AL) has been proposed as a technique to reduce the amount of annotated data needed in the context of supervised clas- sification. While various simulation studies for a number of NLP tasks have shown that AL works well on goldstandard data, there is some doubt whether the approach …...

In the present paper, we propose the ef- fective usage of function words to generate generalized translation rules for forest-based translation. Given aligned forest-string pairs, we extract composed tree-to-string translation rules that account for multiple interpretations of both aligned and unaligned target func- tion words. In order to constrain the …...

We propose methods for estimating the prob- ability that an entity from an entity database is associated with a web search query. Asso- ciation is modeled using a query entity click graph, blending general query click logs with vertical query click logs. Smoothing tech- niques are proposed to address the …...

In this work, we tackle the task of ma- chine translation (MT) without parallel train- ing data. We frame the MT problem as a de- cipherment task, treating the foreign text as a cipher for English and present novel meth- ods for training translation models from non- parallel text. 1...

In this work we propose methods to label probabilistic synchronous context-free gram- mar (PSCFG) rules using only word tags, generated by either part-of-speech analysis or unsupervised word class induction. The proposals range from simple tag-combination schemes to a phrase clustering model that can incorporate an arbitrary number of features. Our …...

We report applications of language technology to analyzing historical documents in the Database for the Study of Modern Chinese Thoughts and Literature (DSMCTL). We studied two historical issues with the reported techniques: the conceptualization of “huaren” (華人, Chinese people) and the attempt to institute constitutional monarchy in the late Qing …...

Definite Anaphora in Chinese Texts Tyne Liang∗ and Jyun-Hua Cheng∗ Abstract Anaphora is a rhetorical device commonly used in written texts. It denotes the use of terms referring to previously-mentioned entities, concepts, or events. In this paper, the definite anaphora in Chinese texts is addressed and empirical approaches to tackle …...

Automatic speaker-identification (SID) has long been an important research topic. It is aimed at identifying who among a set of enrolled persons spoke a given utterance. This study extends the conventional SID problem to examining if an SID system trained using speech data can identify the singing voices of the …...

This paper analyzes the effect of the struc- tural variation of sentences on parsing per- formance. We examine the performance of both shallow and deep parsers for two sen- tence constructions: imperatives and ques- tions. We first prepare an annotated cor- pus for each of these sentence construc- tions by …...

Real document collections do not fit the inde- pendence assumptions asserted by most statis- tical topic models, but how badly do they vi- olate them? We present a Bayesian method for measuring how well a topic model fits a corpus. Our approach is based on posterior predictive checking, a method …...

Dependency structure, as a first step towards semantics, is believed to be helpful to improve translation quality. However, previous works on dependency structure based models typi- cally resort to insertion operations to complete translations, which make it difficult to spec- ify ordering information in translation rules. In our model of …...

Automatically produced texts (e.g. transla- tions or summaries) are usually evaluated with n-gram based measures such as BLEU or ROUGE, while the wide set of more sophisti- cated measures that have been proposed in the last years remains largely ignored for practical purposes. In this paper we first present an …...

We propose a sentence generation strategy that describes images by predicting the most likely nouns, verbs, scenes and prepositions that make up the core sentence structure. The input are initial noisy estimates of the objects and scenes detected in the image using state of the art trained detectors. As predicting …...

We offer a simple, effective, and scalable method for statistical machine translation pa- rameter tuning based on the pairwise approach to ranking (Herbrich et al., 1999). Unlike the popular MERT algorithm (Och, 2003), our pairwise ranking optimization (PRO) method is not limited to a handful of parameters and can easily …...