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An agent-based model for the spread of the Dengue fever: a swarm platform simulation approach
TLDR
This work proposes an agent-based model of the spread of the dengue fever arbovirosis, where agents interact between themselves and the environment representing the process of dissemination of the disease. Expand
Multi-sense embeddings through a word sense disambiguation process
TLDR
A novel approach called Most Suitable Sense Annotation (MSSA) is proposed, that disambiguates and annotates each word by its specific sense, considering the semantic effects of its context. Expand
The Continuing Reinvention of Content-Based Retrieval: Multimedia Is Not Dead
TLDR
It is argued that the next grand challenge for the multimedia community will be understanding and formally modeling the flow of life around us, over many modalities and scales, which will require supplementing generic signal/sensor-based retrieval with syntactical, semantic, and pragmatics-based approaches. Expand
Principles of Agent-Oriented Programming
In the early of 1970s the Artificial Intelligence (AI) was defined as a system based on the Von Neumann model (with a single control center) and the concepts of traditional Psychology. In the late ofExpand
Keyword Extraction Through Contextual Semantic Analysis of Documents
TLDR
Two alternative approaches to extract concept-terms based on semantic features embedded in textual documents extracted from Wikipedia are explored, one of which extends the concept of Word Sense Disambiguation (WSD) and the second enhances the theory behind traditional lexical chains. Expand
Enhanced word embeddings using multi-semantic representation through lexical chains
TLDR
This work proposes two novel algorithms, called Flexible Lexical Chain II and Fixed Lexical chain II, that combine the semantic relations derived from lexical chains, prior knowledge from lexicals databases, and the robustness of the distributional hypothesis in word embeddings as building blocks forming a single system. Expand
Pairwise Multi-Class Document Classification for Semantic Relations between Wikipedia Articles
TLDR
This paper model the problem of finding the relationship between two documents as a pairwise document classification task, and suggests that classifying semantic relations between documents is a solvable task and motivates the development of a recommender system based on the evaluated techniques. Expand
Semantic Feature Structure Extraction From Documents Based on Extended Lexical Chains
TLDR
This paper explores the degree of cohesion among a document’s words using lexical chains as a semantic representation of its meaning using WordNet as a lexical database and develops a text document representation that can be used for semantic document retrieval. Expand
Automated refactoring of ATL model transformations: a search-based approach
TLDR
This paper proposes a fully-automated search-based approach to refactor model transformations based on a multi-objective algorithm that recommends the best refactoring sequence optimizing a set of ATL-based quality metrics. Expand
Modeling Artificial Life Through Multi-Agent Based Simulation
The Multi-Agent Based Simulation (MABS) area is placed at the intersection of two distinct areas: Distributed Artificial Intelligence (DAI) and Computational Simulation. This field of researchExpand
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