Inteligencia Artif.Pub Date : 2019-02-27DOI: 10.4114/INTARTIF.VOL22ISS63PP81-100
Antonela Tommasel, J. Rodriguez, D. Godoy
{"title":"An experimental study on feature engineering and learning approaches for aggression detection in social media","authors":"Antonela Tommasel, J. Rodriguez, D. Godoy","doi":"10.4114/INTARTIF.VOL22ISS63PP81-100","DOIUrl":"https://doi.org/10.4114/INTARTIF.VOL22ISS63PP81-100","url":null,"abstract":"With the widespread of modern technologies and social media networks, a new form of bullying occurring anytime and anywhere has emerged. This new phenomenon, known as cyberaggression or cyberbullying, refers to aggressive and intentional acts aiming at repeatedly causing harm to other person involving rude, insulting, offensive, teasing or demoralising comments through online social media. As these aggressions represent a threatening experience to Internet users, especially kids and teens who are still shaping their identities, social relations and well-being, it is crucial to understand how cyberbullying occurs to prevent it from escalating. Considering the massive information on the Web, the developing of intelligent techniques for automatically detecting harmful content is gaining importance, allowing the monitoring of large-scale social media and the early detection of unwanted and aggressive situations. Even though several approaches have been developed over the last few years based both on traditional and deep learning techniques, several concerns arise over the duplication of research and the difficulty of comparing results. Moreover, there is no agreement regarding neither which type of technique is better suited for the task, nor the type of features in which learning should be based. The goal of this work is to shed some light on the effects of learning paradigms and feature engineering approaches for detecting aggressions in social media texts. In this context, this work provides an evaluation of diverse traditional and deep learning techniques based on diverse sets of features, across multiple social media sites. ","PeriodicalId":176050,"journal":{"name":"Inteligencia Artif.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129234467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inteligencia Artif.Pub Date : 2018-11-12DOI: 10.4114/INTARTIF.VOL21ISS62PP134-144
Rey Benjamin M. Baquirin, P. Fernandez
{"title":"Artificial Neural Network (ANN) in a Small Dataset to determine Neutrality in the Pronunciation of English as a Foreign Language in Filipino Call Center Agents","authors":"Rey Benjamin M. Baquirin, P. Fernandez","doi":"10.4114/INTARTIF.VOL21ISS62PP134-144","DOIUrl":"https://doi.org/10.4114/INTARTIF.VOL21ISS62PP134-144","url":null,"abstract":"Artificial Neural Networks (ANNs) have continued to be efficient models in solving classification problems. In this paper, we explore the use of an A NN with a small dataset to accurately classify whet her Filipino call center agents’ pronunciations are neutral or not based on their employer’s standards. Isolated utterances of the \u0000ten most commonly used words in the call center were recorded from eleven agents creating a dataset of \u0000110 utterances. Two learning specialists were consulted to establish ground truths and Cohen’s Kappa was computed as 0.82, validating the reliability of the dataset. The first thirteen Mel-Frequency Cepstral Coefficients (MFCCs) were then extracted from each word and an ANN was trained with Ten-fold Stratified Cross Validation. \u0000Experimental results on the model recorded a classification accuracy of 89.60% supported by an overall F-Score \u0000of 0.92.","PeriodicalId":176050,"journal":{"name":"Inteligencia Artif.","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127706613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inteligencia Artif.Pub Date : 2018-11-09DOI: 10.4114/INTARTIF.VOL22ISS63PP114-133
P. V. C. Souza, A. J. Guimarães, V. Araújo, T. S. Rezende, V. Araújo
{"title":"Fuzzy Neural Networks based on Fuzzy Logic Neurons Regularized by Resampling Techniques and Regularization Theory for Regression Problems","authors":"P. V. C. Souza, A. J. Guimarães, V. Araújo, T. S. Rezende, V. Araújo","doi":"10.4114/INTARTIF.VOL22ISS63PP114-133","DOIUrl":"https://doi.org/10.4114/INTARTIF.VOL22ISS63PP114-133","url":null,"abstract":"This paper presents a novel learning algorithm for fuzzy logic neuron based on neural networks and fuzzy systems able to generate accurate and transparent models. The learning algorithm is based on ideas from Extreme Learning Machine [36], to achieve a low time complexity, and regularization theory, resulting in sparse and accurate models. A compact set of incomplete fuzzy rules can be extracted from the resulting network topology. Experiments considering regression problems are detailed. Results suggest the proposed approach as a promising alternative for pattern recognition with a good accuracy and some level of interpretability.","PeriodicalId":176050,"journal":{"name":"Inteligencia Artif.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129699412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inteligencia Artif.Pub Date : 2018-10-01DOI: 10.4114/INTARTIF.VOL21ISS62PP103-113
O. Gasquet, Dominique Longin, F. Maris, P. Régnier, Maël Valais
{"title":"Compact Tree Encodings for Planning as QBF","authors":"O. Gasquet, Dominique Longin, F. Maris, P. Régnier, Maël Valais","doi":"10.4114/INTARTIF.VOL21ISS62PP103-113","DOIUrl":"https://doi.org/10.4114/INTARTIF.VOL21ISS62PP103-113","url":null,"abstract":"Considerable improvements in the technology and performance of SAT solvers has made their use possible for the resolution of various problems in artificial intelligence, and among them that of generating plans. Recently, promising Quantified Boolean Formula (QBF) solvers have been developed and we may expect that in a near future they become as efficient as SAT solvers. So, it is interesting to use QBF language that allows us to produce more compact encodings. We present in this article a translation from STRIPS planning problems into quantified propositional formulas. We introduce two new Compact Tree Encodings: CTE-EFA based on Explanatory frame axioms, and CTE-OPEN based on causal links. Then we compare both of them to CTE-NOOP based on No-op Actions proposed in [Cashmore et al. 2012]. In terms of execution time over benchmark problems, CTE-EFA and CTE-OPEN always performed better than CTE-NOOP.","PeriodicalId":176050,"journal":{"name":"Inteligencia Artif.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123845201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inteligencia Artif.Pub Date : 2018-09-25DOI: 10.4114/INTARTIF.VOL21ISS62PP91-102
Ingo Jost, J. Valiati
{"title":"Deep Learning Applied on Rened Opinion Review Datasets","authors":"Ingo Jost, J. Valiati","doi":"10.4114/INTARTIF.VOL21ISS62PP91-102","DOIUrl":"https://doi.org/10.4114/INTARTIF.VOL21ISS62PP91-102","url":null,"abstract":"Deep Learning has been successfully applied in hard to solve areas, such as image recognition and audioclassification. However, Deep Learning has not yet reached the same performance when employed in textual data,including Opinion Mining. In models that implement a deep architecture, Deep Learning is characterized by theautomatic feature selection step. The impact of previous data refinement in the pre-processing step before theapplication of Deep Learning is investigated to identify opinion polarity. This refinement includes the use of aclassical procedure of textual content and a popular feature selection technique. The results of the experimentsovercome the results of the current literature with the Deep Belief Network application in opinion classification.In addition to overcoming the results, their presentation is broader than the related works, considering the changeof parameter variables. We prove that combining feature selection with a basic preprocessing step, aiming toincrease data quality, might achieve promising results with Deep Belief Network implementation.","PeriodicalId":176050,"journal":{"name":"Inteligencia Artif.","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116473197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inteligencia Artif.Pub Date : 2018-09-18DOI: 10.4114/INTARTIF.VOL21ISS62PP67-74
Christian Muise
{"title":"Characterizing and Computing All Delete-Relaxed Dead-ends","authors":"Christian Muise","doi":"10.4114/INTARTIF.VOL21ISS62PP67-74","DOIUrl":"https://doi.org/10.4114/INTARTIF.VOL21ISS62PP67-74","url":null,"abstract":"Dead-end detection is a key challenge in automated planning, and it is rapidly growing in popularity. Effective dead-end detection techniques can have a large impact on the strength of a planner, and so the effective computation of dead-ends is central to many planning approaches. One of the better understood techniques for detecting dead-ends is to focus on the delete relaxation of a planning problem, where dead-end detection is a polynomial-time operation. In this work, we provide a logical characterization for not just a single dead-end, but for every delete-relaxed dead-end in a planning problem. With a logical representation in hand, one could compile the representation into a form amenable to effective reasoning. We lay the ground-work for this larger vision and provide a preliminary evaluation to this end","PeriodicalId":176050,"journal":{"name":"Inteligencia Artif.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130204136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inteligencia Artif.Pub Date : 2018-09-11DOI: 10.4114/INTARTIF.VOL21ISS62PP75-90
G. Behnke, Susanne Biundo-Stephan
{"title":"X and more Parallelism. Integrating LTL-Next into SAT-based Planning with Trajectory Constraints while Allowing for even more Parallelism","authors":"G. Behnke, Susanne Biundo-Stephan","doi":"10.4114/INTARTIF.VOL21ISS62PP75-90","DOIUrl":"https://doi.org/10.4114/INTARTIF.VOL21ISS62PP75-90","url":null,"abstract":"Linear temporal logic (LTL) provides expressive means to specify temporally extended goals as well as preferences.Recent research has focussed on compilation techniques, i.e., methods to alter the domain ensuring that every solution adheres to the temporally extended goals.This requires either new actions or an construction that is exponential in the size of the formula.A translation into boolean satisfiability (SAT) on the other hand requires neither.So far only one such encoding exists, which is based on the parallel $exists$-step encoding for classical planning.We show a connection between it and recently developed compilation techniques for LTL, which may be exploited in the future.The major drawback of the encoding is that it is limited to LTL without the X operator.We show how to integrate X and describe two new encodings, which allow for more parallelism than the original encoding.An empirical evaluation shows that the new encodings outperform the current state-of-the-art encoding.","PeriodicalId":176050,"journal":{"name":"Inteligencia Artif.","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121728966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inteligencia Artif.Pub Date : 2018-09-09DOI: 10.4114/INTARTIF.VOL21ISS62PP53-66
Anastasios Alexiadis, I. Refanidis, I. Sakellariou
{"title":"Integrating Meeting and Individual Events Scheduling","authors":"Anastasios Alexiadis, I. Refanidis, I. Sakellariou","doi":"10.4114/INTARTIF.VOL21ISS62PP53-66","DOIUrl":"https://doi.org/10.4114/INTARTIF.VOL21ISS62PP53-66","url":null,"abstract":"\u0000 \u0000 \u0000Automated meeting scheduling is the task of reaching an agreement on a time slot to schedule a new meeting, taking into account the participants’ preferences over various aspects of the problem. Such a negotiation is commonly performed in a non-automated manner, that is, the users decide whether they can reschedule existing individual activities and, in some cases, already scheduled meetings in order to accommodate the new meeting request in a particular time slot, by inspecting their schedules. In this work, we take advantage of SelfPlanner, an automated system that employs greedy stochastic optimization algorithms to schedule individual activities under a rich model of preferences and constraints, and we extend that work to accommodate meetings. For each new meeting request, participants decide whether they can accommodate the meeting in a particular time slot by employing SelfPlanner’s underlying algorithms to automatically reschedule existing individual activities. Time slots are prioritized in terms of the number of users that need to reschedule existing activities. An agreement is reached as soon as all agents can schedule the meeting at a particular time slot, without anyone of them experiencing an overall utility loss, that is, taking into account also the utility gain from the meeting. This dynamic multi-agent meeting scheduling approach has been tested on a variety of test problems with very promising results. \u0000 \u0000 \u0000","PeriodicalId":176050,"journal":{"name":"Inteligencia Artif.","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123129843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inteligencia Artif.Pub Date : 2018-09-07DOI: 10.4114/INTARTIF.VOL21ISS62PP1-12
Jorge E. Camargo, Vladimir Vargas-Calderón, Nelson Vargas, Liliana Calderón-Benavides
{"title":"Sentiment polarity classification of tweets using a extended dictionary","authors":"Jorge E. Camargo, Vladimir Vargas-Calderón, Nelson Vargas, Liliana Calderón-Benavides","doi":"10.4114/INTARTIF.VOL21ISS62PP1-12","DOIUrl":"https://doi.org/10.4114/INTARTIF.VOL21ISS62PP1-12","url":null,"abstract":"With the purpose of classifying text based on its sentiment polarity (positive or negative), we proposed an extension of a 68,000 tweets corpus through the inclusion of word definitions from a dictionary of the Real Academia Espa~{n}ola de la Lengua (RAE). A set of 28,000 combinations of 6 Word2Vec and support vector machine parameters were considered in order to evaluate how positively would affect the inclusion of a RAE's dictionary definitions classification performance. We found that such a corpus extension significantly improve the classification accuracy. Therefore, we conclude that the inclusion of a RAE's dictionary increases the semantic relations learned by Word2Vec allowing a better classification accuracy.","PeriodicalId":176050,"journal":{"name":"Inteligencia Artif.","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132589105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inteligencia Artif.Pub Date : 2018-09-07DOI: 10.4114/INTARTIF.VOL21ISS62PP25-39
T. Roehr
{"title":"A Constraint-based Mission Planning Approach for Reconfigurable Multi-Robot Systems","authors":"T. Roehr","doi":"10.4114/INTARTIF.VOL21ISS62PP25-39","DOIUrl":"https://doi.org/10.4114/INTARTIF.VOL21ISS62PP25-39","url":null,"abstract":"The application of reconfigurable multi-robot systems introduces additional degrees of freedom to design robotic missions compared to classical multi-robot systems. To allow for autonomous operation of such systems, planning approaches have to be investigated that cannot only cope with the combinatorial challenge arising from the increased flexibility of modular systems, but also exploit this flexibility to improve for example the safety of operation. While the problem originates from the domain of robotics it is of general nature and significantly intersects with operations research. This paper suggests a constraint-based mission planning approach, and presents a set of revised definitions for reconfigurable multi-robot systems including the representation of the planning problem using spatially and temporally qualified resource constraints. Planning is performed using a multi-stage approach and a combined use of knowledge-based reasoning, constraint-based programming and integer linear programming. The paper concludes with the illustration of the solution of a planned example mission.","PeriodicalId":176050,"journal":{"name":"Inteligencia Artif.","volume":"1020 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133842913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}