We describe two methods to perform sentiment analysis both on long and short texts written in Spanish language. We first present an unsupervised method based on dependency parsing which calculates the semantic orientation (SO) of the sentences in order to classify the polarity. We then propose a hybrid approach which uses the computed SO and lexico-syntactic knowledge as features for a supervis...

This study focuses on using hybrid n-grams as grammar rules for detecting grammatical errors and providing corrections in Filipino. These grammar rules are derived from grammatically-correct and tagged texts which are made up of part-of-speech (POS) tags, lemmas, and surface words sequences. Due to the structure of the rules used by this system, it presents an opportunity to have an unsupervise...

Augmenting formal medical knowledge is neither manually nor automatically straightforward. However, this process can benefit from rich information in narrative texts, such as scientific publications. Snomed-supervised relation extraction has been proposed as an approach for mining knowledge from texts in an unsupervised way. It can catch not only superclass/subclass relations but also existenti...

We present in this article a hybrid approach to automatically tokenize Vietnamese text. The approach combines both finite-state automata technique, regular expression parsing and the maximal-matching strategy which is augmented by statistical methods to resolve ambiguities of segmentation. The Vietnamese lexicon in use is compactly represented by a minimal finite-state automaton. A text to be t...

The tasks of entity extraction, recognition, and linking are largely affected by the nature of the textual documents being analyzed. In fact, a lot of research efforts have focused on improving each task for both formal text (such as newswire documents) and for informal text (such as tweets). In this work, we propose a so-called hybrid approach that aims to be agnostic of the document type. Two...

Hybrid index structures support access to heterogeneous data types in multiple columns. Several experiments confirm the improved efficiency of these hybrid access structures. Yet, very little is known about the worst case time and space complexity of them. This paper aims to close this gap by introducing a theoretical framework supporting the analysis of hybrid index structures. This framework ...

US youths’ lives are increasingly divided between the academic requirements of school and immersion in new media and culture outside school. Educators can help bridge in-school and out-ofschool literacy practices by encouraging students to engage with hybrid texts that draw on multiple modes of representation. In this paper, we analyze the ‘disconnect’ between academic literacy and new media, d...

We present an approach for extracting relations from texts that exploits linguistic and empirical strategies, by means of a pipeline method involving a parser, partof-speech tagger, named entity recognition system, pattern-based classification and word sense disambiguation models, and resources such as ontology, knowledge base and lexical databases. The relations extracted can be used for vario...

Named entity recognition (NER) has been extensively studied for the names of genes and gene products but there are few proposed solutions for phenotypes. Phenotype terms are expected to play a key role in inferring gene function in complex heritable diseases but are intrinsically difficult to analyse due to their complex semantics and scale. In contrast to previous approaches we evaluate state-...