Articles

We propose a model for Chinese poem generation based on recurrent neural net- works which we argue is ideally suited to capturing poetic content and form. Our generator jointly performs content selec- tion (“what to say”) and surface realization (“how to say”) by learning representations of individual characters, and their …...

Transforming a natural language (NL) question into a corresponding logical form (LF) is central to the knowledge-based question answering (KB-QA) task. Un- like most previous methods that achieve this goal based on mappings between lex- icalized phrases and logical predicates, this paper goes one step further and pro- poses a …...

This paper presents a system which learns to answer questions on a broad range of topics from a knowledge base using few hand-crafted features. Our model learns low-dimensional embeddings of words and knowledge base constituents; these representations are used to score natural language questions against candidate an- swers. Training our …...

Text classification methods for tasks like factoid question answering typi- cally use manually defined string match- ing rules or bag of words representa- tions. These methods are ineffective when question text contains very few individual words (e.g., named entities) that are indicative of the answer. We introduce a recursive neural …...

Keyboard layout errors and homoglyphs in cross-language queries impact our abil- ity to correctly interpret user informa- tion needs and offer relevant results. We present a machine learning approach to correcting these errors, based largely on character-level n-gram features. We demonstrate superior performance over rule-based methods, as well as a …...

Wikipedia’s link structure is a valuable resource for natural language processing tasks, but only a fraction of the concepts mentioned in each article are annotated with hyperlinks. In this paper, we study how to augment Wikipedia with additional high-precision links. We present 3W, a system that identifies concept mentions in …...

In this paper we examine the lexical substitu- tion task for the medical domain. We adapt the current best system from the open domain, which trains a single classifier for all instances using delexicalized features. We show sig- nificant improvements over a strong baseline coming from a distributional thesaurus (DT). …...

Non-linear mappings of the form P(ngram)γ and log(1+τP(ngram)) log(1+τ) are applied to the n-gram probabilities in five trainable open-source language identifiers. The first mapping reduces classification errors by 4.0% to 83.9% over a test set of more than one million 65-character strings in 1366 languages, and by 2.6% to 76.7% …...

When documents and queries are pre- sented in different languages, the com- mon approach is to translate the query into the document language. While there are a variety of query translation approaches, recent research suggests that combining multiple methods into a single ”structured query” is the most effective. In this …...

A major challenge in document clustering re- search arises from the growing amount of text data written in different languages. Previ- ous approaches depend on language-specific solutions (e.g., bilingual dictionaries, sequen- tial machine translation) to evaluate document similarities, and the required transformations may alter the original document semantics. To cope …...

We provide a comparative study be- tween neural word representations and traditional vector spaces based on co- occurrence counts, in a number of com- positional tasks. We use three differ- ent semantic spaces and implement seven tensor-based compositional models, which we then test (together with simpler ad- ditive and multiplicative …...

In this paper, we propose an automatic identification model, capable of extract- ing expressions of locations (EoLs) within Twitter messages. Moreover, we partici- pated in the competition of ALTA Shared Task 2014 and our best-performing system is ranked among the top 3 systems (2nd in the public leaderboard). In our …...

This paper describes the strategy and the results of a location mining system used for the ALTA-2014 shared task competi- tion. The task required the participants to identify the location mentions in 1003 Twitter test messages given a separate an- notated training set of 2000 messages. We present an architecture …...

This paper describes our system in the ALTA shared task 2014. The task is to identify location mentions in Twitter mes- sages, such as place names and point-of- interests (POIs). We formulated the task as a sequential labelling problem, and ex- plored various features on top of a condi- tional …...

This year was the fifth in the ALTA se- ries of shared tasks. The topic of the 2014 ALTA shared task was to identify location information in tweets. As in past com- petitions, we used Kaggle in Class as the framework for submission, evaluation and communication with the participants. In …...

Studying the structure of given names and how they associate with gender and eth- nicity is an interesting research topic that has recently found practical uses in vari- ous areas. Given the paucity of annotated name data, we develop and make avail- able a new dataset containing 14k given names. …...

We outline the first application of Native Language Identification (NLI) to Finnish learner data. NLI is the task of predicting an author’s first language using writings in an acquired language. Using data from a new learner corpus of Finnish — a lan- guage typology quite different from others previously investigated, …...

We evaluate the use of Deep Belief Net- works as classifiers in a text categorisa- tion task (assigning category labels to doc- uments) in the biomedical domain. Our preliminary results indicate that compared to Support Vector Machines, Deep Belief Networks are superior when a large set of training examples is …...

Statistical Machine Translation (SMT) is a well-known and well established data- driven approach used for language trans- lation. The focus of this work is to de- velop a statistical machine translation sys- tem for Sri Lankan languages, Sinhala and Tamil language pair. This paper presents a systematic investigation of how …...

We present a study of a dataset of ta- bles from biomedical research publica- tions. Our aim is to identify characteris- tics of biomedical tables that pose chal- lenges for the task of extracting informa- tion from tables, and to determine which parts of research papers typically contain information that …...