Francisco Viveros-Jiménez's research while affiliated with Instituto Politécnico Nacional and other places

Publications (8)

Article
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It is well-known that the lack of quality data is a major problem for information retrieval engines. Web articles are flooded with non-relevant data such as advertising and related links. Moreover, some of these ads are loaded in a randomized way every time you hit a page, so the HTML document will be different and hashing of the content will be no...
Article
This paper describes a novel algorithm for numerical optimization, called Simple Adaptive Climbing (SAC). SAC is a simple efficient single-point approach that does not require a careful fine-tunning of its two parameters. SAC algorithm shares many similarities with local optimization heuristics, such as random walk, gradient descent, and hill-climb...
Conference Paper
The Simplified Lesk Algorithm (SLA) is frequently used for word sense disambiguation. It disambiguates by calculating the overlap of a set of dictionary definitions (senses) and the context words. The algorithm is simple and fast, but it has relatively low accuracy. We propose simple strategies for the context window selection that improve the perf...
Conference Paper
This paper describes a novel algorithm for numerical optimization, which we call Simple Adaptive Climbing ( SAC ). SAC is a simple efficient single-point approach that does not require a careful fine-tunning of its two parameters. Our algorithm has a close resemblance to local optimization heuristics such as random walk, gradient descent and, hill-...
Article
Full-text available
This paper presents an empirical comparison of some evolutionary algorithms to solve numerical optimization problems. The aim of the paper is to test a micro-evolutionary algorithm called Elitist evolution, originally designed to work with small populations, on a set of diverse test problems (unimodal, multimodal, separable, non-separable, shifted,...
Article
Full-text available
Micro-population Evolutionary Algorithms (μ-EAs) are useful tools for optimization purposes. They can be used as optimizers for unconstrained, constraint and multi-objective problems. μ-EAs distinctive feature is the usage of very small populations. A novel μ-EA named Elitistic Evolution (EEv) is proposed in this paper. EEv is designed to solve hig...

Citations

... In recent years, the research on web page segmentation technology has been widely concerned, and has made a wealth of research results [12]. Web page segmentation technology is based on the visual characteristics of people, summarizes some rules of web page segmentation, and then realizes web page segmentation based on these rules [13], [14]. Since then, many researchers have proposed many improved web page segmentation technologies based on this method [15], [16], but the idea of rule-based segmentation technology has no essential change. ...
... Note that our current study handles sentences as sequences of stemmed words, where the context of every word consisting of the words surrounding it in the sentence, is used as the main feature for semantic disambiguation, and subsequently for sentiment analysis (cf. Background Section 2.3). As for the WSD process, we combine: i) the well known simplified LESK algorithm [56], with ii) a simple and efficient heuristic method to handle the special case of direct affective words (i.e., words which directly carry sentiments or emotions). The simplified LESK algorithm compares the target word's context (its surrounding words in a sentence) with the contexts of its different possible meanings (concepts) in the lexical KB (where the context of a given concept consists of the set of synonymous terms and gloss descriptions of its surrounding concepts in the KB graph), and chooses the concept whose context is most similar to the target word context as its proper (disambiguated) meaning [56]. ...
... En cuanto a la disponibilidad de este tipo de recursos en otros idiomas, el número es muy limitado. Para el español, destacan el Spanish Emotion Lexicon (SEL) (Sidorov et al., 2012) y el Improved Spanish Opinion Lexicon (iSOL) (Molina-González et al., 2013). Otros métodos basados en este enfoque también tratan de explotar la sintaxis de las palabras clave mediante el uso de etiquetadores POS y, aunque suelen obtener buena precisión, sufren de una baja cobertura (recall ) porque muchos textos no contienen palabras afectivas a pesar de transmitir emociones (Gupta et al., 2017). ...
... Population size is one of the most critical parameters in metaheuristic algorithms. Metaheuristic algorithms with a large population size usually provide better results than small population size since a large population size supports higher diversity for the population, leading to higher exploration ability due to the recombination of its diverse members [20,36]. Nevertheless, sometimes it is more effective to use a small population size. ...
... This is reminiscent of types of search algorithms such as adaptive step size or adaptive mesh models which use large steps to map out the territory, and smaller steps where more accuracy is necessary. See for instance Figlewski and Gao (1999) or Jimnez et al. (2013). Thus we propose the use of three different optimization methods. ...
... The procedure starts by initialising the population of individuals with random genes (although other approaches can be followed in order to reduce the convergence time [33], [34]). The population's size is a crucial factor for the correct convergence of the GA because it causes more diversity in the population and ensures that a large amount of the parameter space is being explored. ...
... In this approach, the diversity is preserved by considering two simple but fast mutation operators in a nominal convergence manner, that work together in a reinitialization process [68] . An other type of EAs, called elitistic evolution (EEv), is proposed for optimizing high-dimensional problems in [69], which works without using complex mechanisms such as Hessian or covariance matrix. This approach utilizes adaptive and elitism behaviour, in which a single adaptive parameter controls the evolutionary operators to provide reasonable local and global search abilities [69] . ...