Articles

For the majority of the world’s languages, the number of linguistic resources (e.g., an- notated corpora and parallel data) is very limited. Consequently, supervised methods, as well as many unsupervised methods, can- not be applied directly, leaving these lan- guages largely untouched and unnoticed. In this paper, we describe the …...

Web search personalization has been well studied in the recent few years. Relevance feedback has been used in various ways to improve relevance of search results. In this paper, we propose a novel usage of rele- vance feedback to effectively model the pro- cess of query formulation and better char- …...

In this paper, we report our work on incor- porating syntactic and morphological infor- mation for English to Hindi statistical ma- chine translation. Two simple and compu- tationally inexpensive ideas have proven to be surprisingly effective: (i) reordering the English source sentence as per Hindi syntax, and (ii) using the …...

Bracketing Transduction Grammar (BTG) has been well studied and used in statistical machine translation (SMT) with promising results. However, there are two major issues for BTG-based SMT. First, there is no effec- tive mechanism available for predicting or- ders between neighboring blocks in the orig- inal BTG. Second, the computational …...

Aiming at acquiring semantic relations be- tween events from a large corpus, this paper proposes several extensions to a state-of-the- art method originally designed for entity re- lation extraction, reporting on the present re- sults of our experiments on a Japanese Web corpus. The results show that (a) there are …...

We present a cross-lingual projection frame- work for temporal annotations. Auto- matically obtained TimeML annotations in the English portion of a parallel corpus are transferred to the German translation along a word alignment. Direct projection augmented with shallow heuristic knowl- edge outperforms the uninformed baseline by 6.64% F1-measure for events, …...

In this paper, we propose a machine learning approach to rhetorical role identification from legal documents. In our approach, we annotate roles in sample documents with the help of legal experts and take them as training data. Conditional random field model has been trained with the data to perform rhetorical …...

We present the results of research with the goal of automatically creating a multilin- gual thesaurus based on the freely available resources of Wikipedia and WordNet. Our goal is to increase resources for natural language processing tasks such as machine translation targeting the Japanese-Spanish language pair. Given the scarcity of …...

We present a novel algorithm for the acqui- sition of multilingual lexical taxonomies (in- cluding hyponymy/hypernymy, meronymy and taxonomic cousinhood), from monolin- gual corpora with minimal supervision in the form of seed exemplars using discriminative learning across the major WordNet seman- tic relationships. This capability is also ex- tended robustly …...

This paper proposes a method for identify- ing synonymous relations in a bilingual lex- icon, which is a set of translation-equivalent term pairs. We train a classifier for identi- fying those synonymous relations by using spelling variations as main clues. We com- pared two approaches: the direct identifi- cation of …...

We present a modular system for detection and correction of errors made by non- native (English as a Second Language = ESL) writers. We focus on two error types: the incorrect use of determiners and the choice of prepositions. We use a decision- tree approach inspired by contextual spelling systems …...

Computer users increasingly need to pro- duce text written in multiple languages. However, typical computer interfaces re- quire the user to change the text entry soft- ware each time a different language is used. This is cumbersome, especially when lan- guage changes are frequent. To solve this problem, we propose …...

Selecting appropriate features to represent an entity pair plays a key role in the task of relation recognition. However, existing syntactic features or lexical features cannot capture the interaction between two enti- ties because of the dearth of annotated rela- tional corpus specialized for relation recog- nition. In this paper, …...

Document retrieval is a critical component of question answering (QA), yet little work has been done towards statistical modeling of queries and towards automatic generation of high quality query content for QA. This paper introduces a new, cluster-based query expansion method that learns queries known to be successful when applied …...

This paper proposes a corpus-based ap- proach for answering why-questions. Con- ventional systems use hand-crafted patterns to extract and evaluate answer candidates. However, such hand-crafted patterns are likely to have low coverage of causal expres- sions, and it is also difficult to assign suit- able weights to the patterns by …...

A lightweight extraction method derives text snippets associated to dates from the Web. The snippets are organized dynamically into answers to definition questions. Experi- ments on standard test question sets show that temporally-anchored text snippets allow for efficiently answering definition ques- tions at accuracy levels comparable to the best systems, …...

This paper presents an approach to the translation of compound words without the need for bilingual training text, by mod- eling the mapping of literal component word glosses (e.g. “iron-path”) into flu- ent English (e.g. “railway”) across mul- tiple languages. Performance is improved by adding component-sequence and learned- morphology models …...

Numerative classifiers are ubiquitous in many Asian languages. This paper pro- poses a method to construct a taxonomy of numerative classifiers based on a noun- classifier agreement database. The taxon- omy defines superordinate-subordinate rela- tion among numerative classifiers and rep- resents the relations in tree structures. The experiments to construct …...

s using Conditional Random Fields Kenji Hirohata† hirohata@nii.ac.jp Naoaki Okazaki† okazaki@is.s.u-tokyo.ac.jp Sophia Ananiadou‡ sophia.ananiadou@manchester.ac.uk †Graduate School of Information Science and Technology, University of Tokyo 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan Mitsuru Ishizuka† ishizuka@i.u-tokyo.ac.jp ‡School of Computer Science, University of Manchester National Centre for Text Mining (NaCTeM) Manchester Interdisciplinary Biocentre, 131 …...

We present a general approach to formally modelling corpora with multi-layered anno- tation, thereby inducing a lexicon model in a typed logical representation language, OWL DL. This model can be interpreted as a graph structure that offers flexible querying func- tionality beyond current XML-based query languages and powerful methods for …...