Specific and sensitive tools for the diagnosis and monitoring of accidents by venomous animals are urgently needed. Several diagnostic and monitoring assays have been developed; however, they have ...not yet reached the clinic. This has resulted in late diagnoses, which represents one of the main causes of progression from mild to severe disease. Human blood is a protein-rich biological fluid that is routinely collected in hospital settings for diagnostic purposes, which can translate research progress from the laboratory to the clinic. Although it is a limited view, blood plasma proteins provide information about the clinical picture of envenomation. Proteome disturbances in response to envenomation by venomous animals have been identified, allowing mass spectrometry (MS)-based plasma proteomics to emerge as a tool in a range of clinical diagnostics and disease management that can be applied to cases of venomous animal envenomation. Here, we provide a review of the state of the art on routine laboratory diagnoses of envenomation by snakes, scorpions, bees, and spiders, as well as a review of the diagnostic methods and the challenges encountered. We present the state of the art on clinical proteomics as the standardization of procedures to be performed within and between research laboratories, favoring a more excellent peptide coverage of candidate proteins for biomarkers. Therefore, the selection of a sample type and method of preparation should be very specific and based on the discovery of biomarkers in specific approaches. However, the sample collection protocol (e.g., collection tube type) and the processing procedure of the sample (e.g., clotting temperature, time allowed for clotting, and anticoagulant used) are equally important to eliminate any bias.
In this paper we present the development of a text simplification system for Spanish. Text simplification is the adaptation of a text for the special needs of certain groups of readers, such as ...language learners, people with cognitive difficulties, and elderly people, among others. There is a clear need for simplified texts, but manual production and adaptation of existing text is labour-intensive and costly. Automatic simplification is a field which attracts growing attention in Natural Language Processing, but, to the best of our knowledge, there are no existing simplification tools for Spanish. We present a corpus study which aims to identify the operations a text simplification system needs to carry out in order to produce an output similar to what human editors produce when they simplify news texts. We also present a first prototype for automatic simplification, which shows that the most important simplification operations can be successfully treated.
In this paper we present an automatic text simplification system for Spanish which intends to make texts more accessible for users with cognitive disabilities. This system aims at reducing the ...structural complexity of Spanish sentences in that it converts complex sentences in two or more simple sentences and therefore reduces reading difficulty.
The rate at which information about music is being created and shared on the web is growing exponentially. However, the challenge of making sense of all this data remains an open problem. In this ...paper, we present and evaluate an Information Extraction pipeline aimed at the construction of a Music Knowledge Base. Our approach starts off by collecting thousands of stories about songs from the songfacts.com website. Then, we combine a state-of-the-art Entity Linking tool and a linguistically motivated rule-based algorithm to extract semantic relations between entity pairs. Next, relations with similar semantics are grouped into clusters by exploiting syntactic dependencies. These relations are ranked thanks to a novel confidence measure based on statistical and linguistic evidence. Evaluation is carried out intrinsically, by assessing each component of the pipeline, as well as in an extrinsic task, in which we evaluate the contribution of natural language explanations in music recommendation. We demonstrate that our method is able to discover novel facts with high precision, which are missing in current generic as well as music-specific knowledge repositories.
•A system that constructs a Music Knowledge Base entirely from scratch.•A method for clustering and scoring relations in a Relation Extraction pipeline.•Reveals music facts absent from knowledge repositories (e.g. Wikipedia).•Explains music recommendations in natural language.
Identifying the correct meaning of words in context or discovering new word senses is particularly useful for several tasks such as question answering, information extraction, information retrieval, ...and text summarization. However, specially in the context of user-generated contents and on-line communication (e.g. Twitter), new meanings are continuously crafted by speakers as the result of existing words being used in novel contexts. Consequently, lexical semantics inventories and systems have difficulties to cope with semantic drifting problems. In this work, we propose an approach to induce and disambiguate word senses of some target words in collections of short texts, such as tweets, through the use of fuzzy lexico-semantic patterns that we define as sequences of Morpho-semantic Components (MSC). We learn these patterns, that we call MSC+ patterns, from text data automatically. Experimental results show that instances of some MSC+ patterns arise in a number of tweets, but sometimes using different words to convey the sense of the respective MSC in some tweets where pattern instances appear. The exploitation of MSC+ patterns when they induce semantics on target words enable effective word sense disambiguation mechanisms leading to improvements in the state of the art.
•The use of fuzzy lexico-semantic patterns in WSI/WSD systems.•The use of Morpho-semantic Components (MSC) in WSI/WSD systems.•An algorithm to mining sequences of MSC.•Two methods implemented as a prototype to evaluate the proposed approach.•Experimental results showing improvements over existing methods.
•We developed the first lexical simplification for Spanish.•Human-informed evaluation of the system.•Comparison of two WSD strategies.•Comparison of two lexical resources.•Software and dataset made ...available for testing and verification.
In this paper we study the effect of different lexical resources for selecting synonyms and strategies for word sense disambiguation in a lexical simplification system for the Spanish language. The resources used for the experiments are the Spanish EuroWordNet, the Spanish Open Thesaurus and a combination of both. As for the synonym selection strategies, we have used both local and global contexts for word sense disambiguation. We present a novel evaluation framework in lexical simplification that takes into account the level of ambiguity of the word to be simplified. The evaluation compares various instances of the lexical simplification system, a gold standard, and a baseline. The paper presents an in-depth qualitative error analysis of the results.
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