Articles

We present a simple, logic-based archi- tecture for solving math problems writ- ten in natural language. A problem is firstly translated to a logical form. It is then rewritten into the input language of a solver algorithm and finally the solver finds an answer. Such a clean decomposi- tion of …...

Automated lexicon acquisition from cor- pora represents one way that large datasets can be leveraged to provide resources for a variety of NLP tasks. Our work applies techniques popularized in sentiment lexi- con acquisition and topic modeling to the broader task of creating a stylistic lexicon. A novel aspect of …...

The main challenge in hierarchical multi- label text classification is how to leverage hierarchically organized labels. In this pa- per, we propose to exploit dependencies among multiple labels to be output, which has been left unused in previous studies. To do this, we first formalize this task as a structured …...

A concept can be linguistically expressed in various syntactic constructions. Such syntactic variations spoil the effectiveness of incorporating dependencies between words into information retrieval systems. This paper presents an information re- trieval method for normalizing syntactic variations via predicate-argument struc- tures. We conduct experiments on stan- dard test collections and …...

Automatic keyphrase extraction aims to pick out a set of terms as a representa- tion of a document without manual assign- ment efforts. Supervised and unsupervised graph-based ranking methods have been s- tudied for this task. However, previous methods usually computed importance s- cores of words under the assumption of …...

Query segmentation is to split a query into a sequence of non-overlapping segments that completely cover all tokens in the query. The majority of methods are unsupervised, how- ever, they are usually not as accurate as su- pervised methods due to the lack of guidance from labeled data. In this …...

We explore the feasibility of contextual healthiness classification of food items. We present a detailed analysis of the lin- guistic phenomena that need to be taken into consideration for this task based on a specially annotated corpus extracted from web forum entries. For automatic classi- fication, we compare a supervised …...

Mining online discussions to extract an- swers is an important research problem. Methods proposed in the past used super- vised classifiers trained on labeled data. But, collecting training data for each target forum is labor intensive and time consum- ing, thus limiting their deployment. A re- cent approach had proposed …...

The objective of the present contribution is to give a survey of the annotation of information structure in the Czech part of the Prague Czech-English Dependency Treebank. We re- port on this first step in the process of building a parallel annotation of information structure in this corpus, and elaborate …...

. In this article, we present the notions of local and global algorithms, for the word sense disambiguation of texts. A local algorithm allows to calculate the semantic similarity between two lexical objects. Global algorithms propagate local measures at the upper level. We use this notion to compare an ant …...

. Using distributional analysis methods to compute semantic proximity links between words has become commonplace in NLP. This paper focuses on the issues of evaluating a dis- tributional resource. We consider that setting up an evaluation procedure is a first step towards the characterization of the resource, and a way …...

. We propose two discriminative strategies to integrate compound word recognition in a parsing context: (i) compound pregrouping with Conditional Random Fields before parsing, (ii) reranking parses with a maximum entropy model after parsing. These discriminative models integrate features dedicated to compounds, some of theme being computed from external lexical …...

. In the biomedical field, using of specialized terms is key to access information. How- ever, in most Indo-European languages, these terms are complex morphological structures. The presented work aims at identifying the various meaningful components of these terms and use them to improve biomedical Information Retrieval (IR). We present …...

In this paper we describe the system used to participate in the sub task 5b in the Phrasal Se- mantics challenge (task 5) in SemEval 2013. This sub task consists in discriminating lit- eral and figurative usage of phrases with compositional and non-compositional mean- ings in context. The proposed approach …...

This paper presents our approach used for cross-lingual textual entailment task (task 8) organized within SemEval 2013. Cross- lingual textual entailment (CLTE) tries to de- tect the entailment relationship between two text fragments in different languages. We solved this problem in three steps. Firstly, we use a off-the-shelf machine translation …...

The measurement of phrasal semantic relat- edness is an important metric for many nat- ural language processing applications. In this paper, we present three approaches for mea- suring phrasal semantics, one based on a se- mantic network model, another on a distribu- tional similarity model, and a hybrid between the …...

This paper describes the IIRG 1 system en- tered in SemEval-2013, the 7th International Workshop on Semantic Evaluation. We partic- ipated in Task 5 Evaluating Phrasal Semantics. We have adopted a token-based approach to solve this task using 1) Na¨ıve Bayes methods and 2) Word Overlap methods, both of which …...

This paper describes the specifications and results of UMCC_DLSI-(EPS) system, which participated in the first Evaluating Phrasal Semantics of SemEval-2013. Our supervised system uses different kinds of semantic features to train a bagging classifier used to select the correct similarity option. Related to the different features we can highlight the …...

In this paper, we present a system, UTTime, which we submitted to TempEval-3 for Task C: Annotating temporal relations. The sys- tem uses logistic regression classifiers and ex- ploits features extracted from a deep syntactic parser, including paths between event words in phrase structure trees and their path lengths, and …...

This paper describes a system for temporal processing of text, which participated in the Temporal Evaluations 2013 campaign. The system employs a number of machine learning classifiers to perform the core tasks of: identi- fication of time expressions and events, recog- nition of their attributes, and estimation of temporal links …...