Articles

This paper introduces a new class of tem- poral expression – named temporal ex- pressions – and methods for recognis- ing and interpreting its members. The commonest temporal expressions typically contain date and time words, like April or hours. Research into recognising and in- terpreting these typical expressions is ma- …...

For efficient diagnosis processes, the mul- titude of heterogeneous medical data re- quires seamless integration. In order to automatically align radiology reports and images based on the pathological anatom- ical entities they describe, a preceding sen- tence classification is necessary. However, the lexical resource used has to contain se- mantic …...

In opinion mining, many linguistic struc- tures, called contextual valence shifters, may modify the prior polarity of items. Some systems of sentiment analysis have tried to take these shifters into account, but few studies have focused on the identifica- tion of all these structures and their impact on polarized words. …...

In this paper, we present an agglomera- tive hierarchical clustering algorithm for labelling morphs. The algorithm aims to capture allomorphs and homophonous morphemes for a deeper analysis of seg- mentation results of a morphological seg- mentation system. Most morphological segmentation systems focus only on seg- mentation rather than labelling morphs …...

The emergence of social media (networks, blogs, web forums) has given people numer- ous opportunities to share their personal sto- ries, including details of their health. Although users mostly post under assumed nicknames, state-of-the-art text analysis techniques can combine texts from different media and use that linkage to identify private …...

Twitter is the largest source of microblog text, responsible for gigabytes of human discourse every day. Processing microblog text is diffi- cult: the genre is noisy, documents have lit- tle context, and utterances are very short. As such, conventional NLP tools fail when faced with tweets and other microblog text. …...

Current approaches to document-level sentiment analysis rely on local informa- tion, e.g., the words within the given doc- ument. We try to achieve better perfor- mance by incorporating global context of the sentiment target (e.g., a movie or a product). We assume that sentiment la- bels of reviews about the …...

Extraction of structured information from text corpora involves identifying entities and the relationship between entities ex- pressed in unstructured text. We propose a novel iterative pattern induction method to extract relation tuples exploiting lexi- cal and shallow syntactic pattern of a sen- tence. We start with a single pattern to …...

We compare two different methods in domain adaptation applied to constituent parsing: parser combination and co- training, each used to transfer information from the source domain of news to the tar- get domain of natural dialogs, in a set- ting without annotated data. Both methods outperform the baselines and reach …...

General natural language processing and text-to-speech applications require certain (lexical level) processing steps in order to solve some frequent tasks such as lemmatization, syllabification, lexical stress prediction and phonetic transcription. These steps usually require knowledge of the word’s lexical composition (derivative morphology, inflectional affixes, etc.). For known words all applications …...

This paper describes a text-reading tool that makes extensive use of widely- available NLP tools and resources to aid non-native English speakers overcome language related hindrances while reading a text. It is a web-based tool, that can be accessed from browsers running on PCs or tablets, and provides the reader …...

Sentiment analysis is currently a very dy- namic field in Computational Linguistics. Research herein has concentrated on the development of methods and resources for different types of texts and various lan- guages. Nonetheless, the implementa- tion of a multilingual system that is able to classify sentiment expressed in various languages …...

We present ASemiNER, a semi- supervised algorithm for identifying Named Entities (NEs) in Arabic text. ASemiNER does not require annotated training data, or gazetteers. It also can be easily adapted to handle more than the three standard NE types (Person, Location, and Organisation). To our knowledge, our algorithm is the …...

We present in this paper an unsupervised approach to recognize events, time and place expressions in Ara- bic texts. Arabic is a resource –scarce language and we don’t easily have at hand annotated corpora, lexi- cons and other needed NLP tools. We show in this work that we can recognize …...

Our study focuses on opinion mining of several medi- cal forums dedicated to Hearing Loss (HL). Surgeries related to HL are the most common surgeries in North America; thus, they affect many patients and their families. We have extracted the opinions of people from these forums related to stigma of …...

This paper introduces a method for im- proving tree edit distance (TED) for tex- tual entailment. We explore two ways of improving TED: we extend the standard TED to use edit operations that apply to subtrees as well as to single nodes; and we use the ‘artificial bee colony’ algorithm …...

In this paper, we present ASMA, a fast and efficient system for automatic seg- mentation and fine grained part of speech (POS) tagging of Modern Standard Ara- bic (MSA). ASMA performs segmenta- tion both of agglutinative and of inflec- tional morphological boundaries within a word. In this work, we compare …...

This paper proposes a combined model for POS tagging, dependency parsing and co-reference resolution for Bulgarian — a pro-drop Slavic language with rich mor- phosyntax. We formulate an extension of the MSTParser algorithm that allows the simultaneous handling of the three tasks in a way that makes it possible for …...

This work introduces a machine learn- ing approach to the identification of men- tion heads needed for multilingual coref- erence resolution (MCR). We evaluate the method and compare it to a heuristic base- line and a rule-based approach, which are widely used in coreference resolution sys- tems. We use the …...

In Computational Linguistics, building lexical-semantic networks and validat- ing contained relations are paramount issues as well as adding some reasoning skills in order to enrich these knowledge bases. In this paper we devise an in- ference engine which aims at producing new "potential" relations from already existing ones in the …...