Abstract
Due to the rapid growth of structured/unstructured and user-generated data (e.g., social media sites) volume of data is becoming too big or it moves too fast or it exceeds current processing capacity and so traditional data processing applications are inadequate. Computational Intelligence with Concept-based approaches can detect sentiments analyzing the concept based on text expressions without analyzing the singlef words as in the purely syntactical techniques. On human-centric intelligent systems Semantic networks can simulate the human complex frames in a reasoning process providing efficient association and inference mechanisms, while ontology can be used to fill the gap between human and Computational Intelligence for a task domain. For an evolving environment it is necessary to understand what knowledge is required for a task domain with an adaptive ontology matching. To reflect the evolving knowledge this paper considers ontologies based on folksonomies according to a new concept structure called “Folksodriven” to represent folksonomies. To solve the problems inherent an uncontrolled vocabulary of the folksonomy it is presented a Folksodriven Structure Network (FSN): a folksonomy tags suggestions built from the relations among the Folksodriven tags (FD tags). It was observed that the properties of the FSN depend mainly on the nature, distribution, size and the quality of the reinforcing FD tags. So, the studies on the transformational regulation of the FD tags are regarded to be important for an adaptive folksonomies classifications in an evolving environment used by Intelligent Systems to represent the knowledge sharing. The chapter starts from the discussion on the deformation exhibiting linear behavior on FSN based on folksonomy tags chosen by different user on web site resources. Then it’s formulated a constitutive law on FSN investigating towards a systematic mathematical analysis on stress analysis and equations of motion for an evolving ontology matching on an environment defined by the users’ folksonomy choice. The adaptive ontology matching and the elastodynamics are merged to obtain what we can call the elasto-adaptive-dynamics methodology of the FSN. Furthermore it is shown the last development defining a hyperelastic dynamic considering the internal folksonomy behavior of the stress and strain from original to deformed configuration.
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Notes
- 1.
“folks” derives from the Old English “folc” (meaning ’people’), of Old High Germanic origin “folc”, related to German “volk”; while “taxonomy” derives from the Greek words “taxis” (meaning ‘order’, ’arrangement’) and “nomos” (‘law’ or ‘science’).
- 2.
Nonlinear means that output isn’t directly proportional to input, or that a change in one variable doesn’t produce a proportional change or reaction in the related variable(s). In other words, a system’s values at one time aren’t proportional to the values at an earlier time.
- 3.
A dynamical system is anything that moves, changes, or evolves in time. Hence, chaos deals with what the experts like to refer to as dynamical-systems theory (the study of phenomena that vary with time) or nonlinear dynamics (the study of nonlinear movement or evolution).
- 4.
Quasiperiodicity in the general definition also includes incommensurately modulated FSN as well as composite FSN. Here, we will not discuss these cases, which either can be seen as periodic modification of an underlying basic structure or as a kind of intergrowth of periodic structures.
- 5.
Spinning consolidation: the growing of FD tags connections around the original FD tag.
- 6.
Collapse: when links between FD tags shrink together abruptly and completely to a direct link with a main FD tag.
- 7.
A phonon is a quantum mechanical definition of the lattice vibration that uniformly oscillates at the same frequency. It is known as the “normal mode” in classical mechanics. According to it any arbitrary lattice vibration can be described as a superposition of the elementary vibrations described by the phonon (cfr. Fourier analysis—[12]).
- 8.
Similar to phonon, phason is associated with nodes of lattice motion, considered here as FD tags. However, whereas phonons are related to translation of FD tags, phasons are associated with FD tags rearrangements.
- 9.
According to classical physic the Hooke’s law (law of elasticity), is depicted by \(F=-kx\) Where the movement of the end of the spring is expressed by x respect its equilibrium position. F depicts the spring restoring force and k is the spring (or rate) constant.
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Dal Mas, M. (2016). Hyperelastic-Based Adaptive Dynamics Methodology in Knowledge Acquisition for Computational Intelligence on Ontology Engineering of Evolving Folksonomy Driven Environment. In: Pedrycz, W., Chen, SM. (eds) Sentiment Analysis and Ontology Engineering. Studies in Computational Intelligence, vol 639. Springer, Cham. https://doi.org/10.1007/978-3-319-30319-2_7
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