Articles

We present a new, efficient unsupervised approach to the segmentation of corpora into multiword units. Our method involves initial decomposition of common n-grams into segments which max- imize within-segment predictability of words, and then further refinement of these segments into a multiword lexicon. Evaluating in four large, distinct corpora, we …...

Motivated by evidence in psycholinguistics and cognition, we propose a hierarchical distributed semantic model (DSM) that consists of low-dimensional manifolds built on semantic neighbor- hoods. Each semantic neighborhood is sparsely encoded and mapped into a low-dimensional space. Global operations are decomposed into local operations in multiple sub-spaces; results from these …...

This paper presents a first version of LinkPeople, an entity-centric system for coreference reso- lution of person entities. The approach combines (i) a multi-pass architecture which takes advan- tage of entity features at document-level with (ii) a set of linguistically-motivated constraints and rules which allows the system to restrict the …...

Compositional Distributional Semantics Models (CDSMs) are traditionally seen as an entire dif- ferent world with respect to Tree Kernels (TKs). In this paper, we show that under a suitable regime these two approaches can be regarded as the same and, thus, structural information and distributional semantics can successfully cooperate in …...

In this paper, we address the issue of building and improving a distributional thesaurus. We first show that existing tools from the information retrieval domain can be directly used in order to build a thesaurus with state-of-the-art performance. Secondly, we focus more specifically on improving the obtained thesaurus, seen as …...

Structured distributional semantic models aim to improve upon simple vector space models of semantics by hypothesizing that the meaning of a word is captured more effectively through its relational — rather than its raw distributional — signature. In accordance, they extend the vector space paradigm by structuring elements with relational …...

In recent years, the problem of finite-state constraint grammar (CG) parsing has received renewed attention. Several compilers have been proposed to convert CG rules to finite-state transducers. While these formalisms serve their purpose as proofs of the concept, the performance of the generated transducers lags behind other CG implementations and …...

Microblogging services have attracted hundreds of millions of users to publish their status, ideas and thoughts, everyday. These microblog posts have also become one of the most attractive and valuable resources for applications in different areas. The task of identifying the main targets of microblogs is an important and essential …...

Detecting opinion relation is a crucial step for fine-gained opinion summarization. A valid opin- ion relation has three requirements: a correct opinion word, a correct opinion target and the linking relation between them. Previous works prone to only verifying two of these requirements for opinion extraction, while leave the other …...

Community Question Answering (CQA) websites such as Quora are widely used for users to get high quality answers. Users are the most important resource for CQA services, and the awareness of user expertise at early stage is critical to improve user experience and reduce churn rate. However, due to the …...

Topic modelling has been popularly used to discover latent topics from text documents. Most existing models work on individual words. That is, they treat each topic as a distribution over words. However, using only individual words has several shortcomings. First, it increases the co-occurrences of words which may be incorrect …...

In this paper we present a novel method for unsupervised coreference resolution. We introduce a precision-oriented inference method that scores a candidate entity of a mention based on the most informative mention pair relation between the given mention entity pair. We introduce an infor- mativeness score for determining the most …...

When assessing child language development, researchers have traditionally had to choose be- tween easily computable metrics focused on superficial aspects of language, and more expressive metrics that are carefully designed to cover specific syntactic structures and require substantial and tedious labor. Recent work has shown that existing expressive metrics for …...

Consumers’ purchase decisions are in- creasingly influenced by user-generated online reviews. Accordingly, there has been growing concern about the poten- tial for posting deceptive opinion spam— fictitious reviews that have been deliber- ately written to sound authentic, to de- ceive the reader. In this paper, we ex- plore generalized approaches …...

We present a method that learns word em- bedding for Twitter sentiment classifica- tion in this paper. Most existing algorithm- s for learning continuous word represen- tations typically only model the syntactic context of words but ignore the sentimen- t of text. This is problematic for senti- ment analysis as …...

Recently, researchers have begun explor- ing methods of scoring student essays with respect to particular dimensions of qual- ity such as coherence, technical errors, and prompt adherence. The work on modeling prompt adherence, however, has been focused mainly on whether individ- ual sentences adhere to the prompt. We present a …...

We introduce ConnotationWordNet, a con- notation lexicon over the network of words in conjunction with senses. We formulate the lexicon induction problem as collec- tive inference over pairwise-Markov Ran- dom Fields, and present a loopy belief propagation algorithm for inference. The key aspect of our method is that it is …...

Natural touch interfaces, common now in devices such as tablets and smartphones, make it cumbersome for users to select text. There is a need for a new text selec- tion paradigm that goes beyond the high acuity selection-by-mouse that we have re- lied on for decades. In this paper, we …...

It is very import for Chinese language pro- cessing with the aid of an efficient input method engine (IME), of which pinyin- to-Chinese (PTC) conversion is the core part. Meanwhile, though typos are in- evitable during user pinyin inputting, ex- isting IMEs paid little attention to such big inconvenience. In …...

Instructor intervention in student discus- sion forums is a vital component in Massive Open Online Courses (MOOCs), where personalized interaction is limited. This paper introduces the problem of pre- dicting instructor interventions in MOOC forums. We propose several prediction models designed to capture unique aspects of MOOCs, combining course informa- …...