Articles

A challenge for search systems is to de- tect not only when an item is relevant to the user’s information need, but also when it contains something new which the user has not seen before. In the TREC novelty track, the task was to highlight sentences containing relevant and new …...

Entity detection and tracking (EDT) is the task of identifying textual mentions of real-world entities in documents, ex- tending the named entity detection and coreference resolution task by consider- ing mentions other than names (pronouns, definite descriptions, etc.). Like NE tag- ging and coreference resolution, most so- lutions to the …...

This paper presents a maximum entropy word alignment algorithm for Arabic- English based on supervised training data. We demonstrate that it is feasible to cre- ate training material for problems in ma- chine translation and that a mixture of su- pervised and unsupervised methods yields superior performance. The probabilistic model …...

We present a discriminative, large- margin approach to feature-based matching for word alignment. In this framework, pairs of word tokens re- ceive a matching score, which is based on features of that pair, including mea- sures of association between the words, distortion between their positions, sim- ilarity of the orthographic …...

This paper presents a novel approach to combining different word alignments. We view word alignment as a pattern classifi- cation problem, where alignment combi- nation is treated as a classifier ensemble, and alignment links are adorned with lin- guistic features. A neural network model is used to learn word alignments …...

The accuracy of event extraction is lim- ited by a number of complicating factors, with errors compounded at all sages in- side the Information Extraction pipeline. In this paper, we present methods for re- covering automatically from errors com- mitted in the pipeline processing. Recov- ery is achieved via post-processing …...

Browsing through large volumes of spoken audio is known to be a challenging task for end users. One way to alleviate this prob- lem is to allow users to gist a spoken audio document by glancing over a transcript generated through Automatic Speech Rec- ognition. Unfortunately, such transcripts typically contain …...

Recognition errors hinder the prolifera- tion of speech recognition (SR) systems. Based on the observation that recogni- tion errors may result in ungrammatical sentences, especially in dictation appli- cation where an acceptable level of ac- curacy of generated documents is indis- pensable, we propose to incorporate two kinds of linguistic …...

In this paper, we use the information re- dundancy in multilingual input to correct errors in machine translation and thus im- prove the quality of multilingual sum- maries. We consider the case of multi- document summarization, where the input documents are in Arabic, and the output summary is in English. …...

The paper proposes a Constrained Entity- Alignment F-Measure (CEAF) for evaluating coreference resolution. The metric is com- puted by aligning reference and system entities (or coreference chains) with the constraint that a system (reference) entity is aligned with at most one reference (system) entity. We show that the best alignment …...

This paper investigates automatic identi- fication of Information Structure (IS) in texts. The experiments use the Prague Dependency Treebank which is annotated with IS following the Praguian approach of Topic Focus Articulation. We auto- matically detect t(opic) and f(ocus), us- ing node attributes from the treebank as basic features and …...

We present a novel mechanism for im- proving reference resolution by using the output of a relation tagger to rescore coreference hypotheses. Experiments show that this new framework can im- prove performance on two quite different languages -- English and Chinese. 1...

We propose an approach to summarization exploiting both lexical information and the output of an automatic anaphoric re- solver, and using Singular Value Decom- position (SVD) to identify the main terms. We demonstrate that adding anaphoric information results in significant perfor- mance improvements over a previously developed system, in which …...

. This paper suggests a methodology which is aimed to extract the terminologically relevant collocations for translation purposes. Our basic idea is to use a hybrid method which combines the statistical method and linguistic rules. The extraction system used in our work operated at three steps: (1) Tokenization and POS …...

. Corpus-based stochastic language models have achieved significant success in speech recognition, but construction of a corpus pertaining to a specific application is a difficult task. This paper introduces a Case-Based Reasoning system to generate natural language corpora. In comparison to traditional natural language generation approaches, this system overcomes the …...

. Our research aims at developing a system that paraphrases written language text to spoken language style. In such a system, it is important to distinguish between appropriate and inappropriate words in an input text for spoken language. We call this task lexical choice for paraphrasing. In this paper, we …...

. Linguistic information can help improve evaluation of simi- larity between documents; however, the kind of linguistic information to be used depends on the task. In this paper, we show that distributions of syntactic structures capture the way works are written and accurately identify individual books more than 76% of …...

. This paper presents an empirical study on four techniques of lan- guage model adaptation, including a maximum a posteriori (MAP) method and three discriminative training models, in the application of Japanese Kana-Kanji conversion. We compare the performance of these methods from various angles by adapting the baseline model to …...

. The paper introduces a method for interpreting novel noun compounds with semantic relations. The method is built around word similarity with pre- tagged noun compounds, based on WordNet::Similarity. Over 1,088 training instances and 1,081 test instances from the Wall Street Journal in the Penn Treebank, the proposed method was …...

. Mining terminology translation from a large amount of Web data can be applied in many fields such as reading/writing assistant, machine translation and cross-language information retrieval. How to find more comprehensive re- sults from the Web and obtain the boundary of candidate translations, and how to remove irrelevant noises …...