Investigating metaphorical language in sentiment analysis: A sense-to-sentiment perspective

Intuition dictates that figurative language and especially metaphorical expressions should convey sentiment. It is the aim of this work to validate this intuition by showing that figurative language (metaphors) appearing in a sentence drive the polarity of that sentence. Towards this target, the current article proposes an approach for sentiment analysis of sentences where figurative language plays a dominant role. This approach applies Word Sense Disambiguation aiming to assign polarity to word senses rather than tokens. Sentence polarity is determined using the individual polarities for metaphorical senses as well as other contextual information. Experimental evaluation shows that the proposed method achieves high scores in comparison with other state-of-the-art approaches tested on the same corpora. Finally, experimental results provide supportive evidence that this method is also well suited for corpora consisting of literal and figurative language sentences. © 2012 ACM

Construction and repair: A hybrid approach to search in CSPs

In order to obtain a solution to a constraint satisfaction problem, constructive methods iteratively extend a consistent partial assignment until all problem variables are instantiated. If the current partial assignment is proved to be inconsistent, it is then necessary to backtrack and perform alternative instantiations. On the other hand, reparative methods iteratively repair an inconsistent complete assignment until it becomes consistent. In this research, we investigate an approach which allows for the combination of constructive and reparative methods, in the hope of exploiting their intrinsic advantages and circumventing their shortcomings. Initially, we discuss a general hybrid method called cr and then proceed to specify its parameters in order to provide a fully operational search method called cnr. The reparative stage therein is of particular interest: we employ techniques borrowed from local search and propose a general cost function for evaluating partial assignments. In addition, we present experimental results on the open-shop scheduling problem. The new method is compared against specialized algorithms and exhibits outstanding performance, yielding solutions of high quality and even improving the best known solution to a number of instances

Specification of Semantic Trajectories Supporting Data Transformations for Analytics: The datAcron Ontology

Motivated by real-life emerging needs in critical domains, this paper proposes a coherent and generic ontology for the representation of semantic trajectories, in association to related events and contextual information, to support analytics. The main contribution of the proposed ontology is twofold: (a) The representation of semantic trajectories at varying, interlinked levels of spatio-Temporal analysis, (b) enabling data transformations that can support analytics tasks. The paper presents the ontology in detail, in connection to other well-known ontologies, and demonstrates how data is represented at varying levels of analysis, enabling the required data transformations. The benefits of the representation are shown in the context of supporting visual analytics tasks in the air-Traffic management domain

Non-linear Programming Method for Buffer Allocation in Unreliable Production Lines

International audienceThis paper proposes a new algorithm based on a non-linear programming approach to deal with the buffer allocation problem in the case of unreliable production lines. Processing, failure and repair times are assumed to be random variables exponentially distributed. The proposed approach can be used to solve the different versions of the buffer allocation problem: primal, dual and generalized.This method is based on the modeling and the analysis of the serial production line using an equivalent machines method. The idea is to model the different possible states of each buffer using dedicated birth-death Markov processes to calculate the blockage and starvation probabilities of each machine. Then, each original machine is replaced by an equivalent one taking into account these probabilities.A comparative study based on different test instances issued from the literature is presented and discussed. The obtained results show the effectiveness and the accuracy of the proposed approach

A semantic mixed reality framework for shared cultural experiences ecosystems

This paper presents SemMR, a semantic framework for modelling interactions between human and non-human entities and managing reusable and optimized cultural experiences, towards a shared cultural experience ecosystem that might seamlessly accommodate mixed reality experiences. The SemMR framework synthesizes and integrates interaction data into semantically rich reusable structures and facilitates the interaction between different types of entities in a symbiotic way, within a large, virtual, and fully experiential open world, promoting experience sharing at the user level, as well as data/application interoperability and low-effort implementation at the software engineering level. The proposed semantic framework introduces methods for low-effort implementation and the deployment of open and reusable cultural content, applications, and tools, around the concept of cultural experience as a semantic trajectory or simply, experience as a trajectory (eX-trajectory). The methods facilitate the collection and analysis of data regarding the behaviour of users and their interaction with other users and the environment, towards optimizing eX-trajectories via reconfiguration. The SemMR framework supports the synthesis, enhancement, and recommendation of highly complex reconfigurable eX-trajectories, while using semantically integrated disparate and heterogeneous related data. Overall, this work aims to semantically manage interactions and experiences through the eX-trajectory concept, towards delivering enriched cultural experiences. © 2020 by the authors. Licensee MDPI, Basel, Switzerland