Articles

Classes Based on Discourse Structure Boris Galitsky Knowledge Trail Inc. San-Francisco, USA bgalitsky@hotmail.com Dmitry Ilvovsky National Research Universi- ty Higher School of Eco- nomics, Moscow, Russia dilvovsky@hse.ru Sergey O. Kuznetsov National Research Universi- ty Higher School of Eco- nomics, Moscow, Russia skuznetsov@hse.ru Abstract The problem of classifying text with respect …...

This paper contributes a joint embedding model for predicting relations between a pair of entities in the scenario of rela- tion inference. It differs from most stand- alone approaches which separately oper- ate on either knowledge bases or free texts. The proposed model simultaneously learn- s low-dimensional vector representation- s …...

Definition Extraction (DE) is the task to ex- tract textual definitions from naturally occur- ring text. It is gaining popularity as a prior step for constructing taxonomies, ontologies, auto- matic glossaries or dictionary entries. These fields of application motivate greater interest in well-formed encyclopedic text from which to extract definitions, …...

In this paper we propose an approach for identifying syntactic behaviours related to lexical items and linking them to the meanings. This approach is based on the analysis of the textual content presented in LMF normalized dictionaries by means of Definition and Context classes. The main particularity of these contents …...

The present research exploits the large amount of linguistic resources developed into the Lexicon-grammar paradigm in the domain of the Opinion Mining. Grounded on the Semantic Predicates theory, the proposed system is able to automatically match the syntactic structures selected by special classes of verbs, indicating positive or negative Sentiment, …...

This paper investigates the use of seman- tic preferences for ontology population. It draws on a new resource, the Pattern Dic- tionary of English Verbs, which lists se- mantic categories expected in each syn- tactic slot of a verb pattern. Knowledge of semantic preferences is used to drive and control …...

Summarizing opinions expressed in online forums can potentially benefit many peo- ple. However, special characteristics of this problem may require changes to stan- dard text summarization techniques. In this work, we present our initial attempt at extractive summarization of opinionated online forum threads. Given the nature of user generated content …...

Product review mining is an important task that can benefit both businesses and con- sumers. Lately a number of models com- bining collaborative filtering and content analysis to model reviews have been pro- posed, among which the Hidden Factors as Topics (HFT) model is a notable one. In this work, …...

Linguistic annotation is time-consuming and expensive. One common annotation task is to mark entities – such as names of people, places and organisations – in text. In a document, many segments of text often contain no entities at all. We show that these segments are worth skip- ping, and demonstrate …...

Determining the temporal order of events in a text is difficult. However, it is crucial to the extraction of narratives, plans, and context. We suggest that a simple, estab- lished framework of tense and aspect pro- vides a viable model for ordering a sub- set of events and times in …...

Brown clustering, an unsupervised hier- archical clustering technique based on n- gram mutual information, has proven use- ful in many NLP applications. However, most uses of Brown clustering employ the same default configuration; the appropri- ateness of this configuration has gone pre- dominantly unexplored. Accordingly, we present information for practitioners …...

We present ongoing work in linguistic pro- cessing of hashtags in Twitter text, with the goal of supplying normalized hashtag content to be used in more complex natural language processing (NLP) tasks. Hashtags represent collectively shared topic designators with considerable surface variation that can ham- per semantic interpretation. Our normaliza- …...

We investigate in this paper the degree of overlap between synonym sets of trans- lated word pairs across three languages: French, English and Romanian. We use for this purpose a French Synonym Dic- tionary, a Romanian Synonym Dictionary, Princeton’s WordNet and Google Trans- late API. We build a database contain- …...

In this paper we investigate how readabil- ity varies between texts originally writ- ten in English and texts translated into English. For quantification, we analyze several factors that are relevant in as- sessing readability – shallow, lexical and morpho-syntactic features – and we em- ploy the widely used Flesch-Kincaid for- …...

We explore the impact of adding distri- butional knowledge to a state-of-the-art coreference resolution system. By inte- grating features based on word and context expansions from a distributional thesaurus (DT), automatically mined IS-A relation- ships and shallow syntactical clues into the Berkeley system (Durrett and Klein, 2013), we are able …...

Efficient music information retrieval (MIR) require to have meta information about music along with content based information in the knowledge base. Dis- cussion forums on music are rich sources of information gathered from a wider audience. Taking into consideration the nature of text in these web resources, the yield of …...

Event Detection (ED) is an Information Extraction task which involves identifying instances of specified types of events in text. Most recent research on Event De- tection relies on pattern-based or feature- based approaches, trained on annotated corpora, to recognize combinations of event triggers, arguments, and other con- textual information. These …...

Event Detection (ED), one aspect of In- formation Extraction, involves identifying instances of specified types of events in text. Much of the research on ED has been based on the specifications of the 2005 ACE [Automatic Content Extrac- tion] event task1, and the associated an- notated corpus. However, as the …...

This article tackles the Authorship Attri- bution task according to the language in- dependence issue. We propose an alterna- tive of variable length character n-grams features in supervised methods: maximal repeats in strings. When character n- grams are by essence redundant, maximal repeats are a condensed way to represent any …...

This paper presents a Constraint Grammar- based pedagogical proofing tool for Danish. The system recognizes not only spelling errors, but also grammatical errors in otherwise correctly spelled words, and categorizes errors for WORD-integrated pedagogical comments. Possible spelling corrections are prioritized from context, and grammatical corrections generated by a morphological module. …...