Jan Broekaert

Faizal Hafiz, Jan Broekaert, Davide La Torre et al.

This study proposes a new framework to evolve efficacious yet parsimonious neural architectures for the movement prediction of stock market indices using technical indicators as inputs. In the light of a sparse signal-to-noise ratio under the Efficient Market hypothesis, developing machine learning methods to predict the movement of a financial market using technical indicators has shown to be a challenging problem. To this end, the neural architecture search is posed as a multi-criteria optimization problem to balance the efficacy with the complexity of architectures. In addition, the implications of different dominant trading tendencies which may be present in the pre-COVID and within-COVID time periods are investigated. An $ε-$ constraint framework is proposed as a remedy to extract any concordant information underlying the possibly conflicting pre-COVID data. Further, a new search paradigm, Two-Dimensional Swarms (2DS) is proposed for the multi-criteria neural architecture search, which explicitly integrates sparsity as an additional search dimension in particle swarms. A detailed comparative evaluation of the proposed approach is carried out by considering genetic algorithm and several combinations of empirical neural design rules with a filter-based feature selection method (mRMR) as baseline approaches. The results of this study convincingly demonstrate that the proposed approach can evolve parsimonious networks with better generalization capabilities.

Diederik Aerts, Jan Broekaert, Liane Gabora et al.

Theories of natural language and concepts have been unable to model the flexibility, creativity, context-dependence, and emergence, exhibited by words, concepts and their combinations. The mathematical formalism of quantum theory has instead been successful in capturing these phenomena such as graded membership, situational meaning, composition of categories, and also more complex decision making situations, which cannot be modeled in traditional probabilistic approaches. We show how a formal quantum approach to concepts and their combinations can provide a powerful extension of prototype theory. We explain how prototypes can interfere in conceptual combinations as a consequence of their contextual interactions, and provide an illustration of this using an intuitive wave-like diagram. This quantum-conceptual approach gives new life to original prototype theory, without however making it a privileged concept theory, as we explain at the end of our paper.

Lorena Pérez-García, Jan Broekaert, Nicole Note

Current social and activist movements find the opportunity in social media to effectively impact on the agenda of governing bodies and create `global' perceptions -- it is often claimed. Content related to the social and activist movements is online, to be accessed, supported or disputed and distributed from virtually anywhere at any time, in the public sphere of the Internet. This activity allows the enlargement of social movements and would increase the empowerment in the concerned communities. The aim of this explorative study is to assess whether the temporal evolution of the Normalised Web Distance (NWD) --as defined by Cilibrasi & Vitányi (2007)-- between identifying terms concerning this activism could be used to measure the progress or decline of social empowerment through the Internet. The NWD relies on the page count number of single and joint queries, which in our study have been registered using a freely available web browser (e.g. Google Search) providing a time search window for temporal query results. To explore this meta-data technique, we introduce the case of a perceived Wirikuta online movement, which originated in Mexico with the aim to protect the Huichols' sacred land and water resources from open mining projects for silver ore. We conducted a small scale Internet study relating the key terms `Wirikuta', `Huichol', and `Wixarika' and their co-occurrence with seven positive qualifiers (e.g. `sacred land'), five negative qualifiers (e.g. `violence') and one neutral qualifier (`table') over time, annually from 1994 till 2013. We confirm close semantic clustering over time of traditional indigeneous identity terms of the Huichol, and observe a slight convergence of key terms to `mines' and less pronounced to `sacred land' and a divergence with respect to `ancestors' indicating a complex image of a tendency of empowerment.

Diederik Aerts, Jan Broekaert, Sandro Sozzo et al.

The mathematical formalism of quantum theory has been successfully used in human cognition to model decision processes and to deliver representations of human knowledge. As such, quantum cognition inspired tools have improved technologies for Natural Language Processing and Information Retrieval. In this paper, we overview the quantum cognition approach developed in our Brussels team during the last two decades, specifically our identification of quantum structures in human concepts and language, and the modeling of data from psychological and corpus-text-based experiments. We discuss our quantum-theoretic framework for concepts and their conjunctions/disjunctions in a Fock-Hilbert space structure, adequately modeling a large amount of data collected on concept combinations. Inspired by this modeling, we put forward elements for a quantum contextual and meaning-based approach to information technologies in which 'entities of meaning' are inversely reconstructed from texts, which are considered as traces of these entities' states.

Diederik Aerts, Jan Broekaert, Sandro Sozzo et al.

In recent years, quantum-based methods have promisingly integrated the traditional procedures in information retrieval (IR) and natural language processing (NLP). Inspired by our research on the identification and application of quantum structures in cognition, more specifically our work on the representation of concepts and their combinations, we put forward a 'quantum meaning based' framework for structured query retrieval in text corpora and standardized testing corpora. This scheme for IR rests on considering as basic notions, (i) 'entities of meaning', e.g., concepts and their combinations and (ii) traces of such entities of meaning, which is how documents are considered in this approach. The meaning content of these 'entities of meaning' is reconstructed by solving an 'inverse problem' in the quantum formalism, consisting of reconstructing the full states of the entities of meaning from their collapsed states identified as traces in relevant documents. The advantages with respect to traditional approaches, such as Latent Semantic Analysis (LSA), are discussed by means of concrete examples.

Diederik Aerts, Jan Broekaert, Liane Gabora et al.

People use conjunctions and disjunctions of concepts in ways that violate the rules of classical logic, such as the law of compositionality. Specifically, they overextend conjunctions of concepts, a phenomenon referred to as the Guppy Effect. We build on previous efforts to develop a quantum model that explains the Guppy Effect in terms of interference. Using a well-studied data set with 16 exemplars that exhibit the Guppy Effect, we developed a 17-dimensional complex Hilbert space H that models the data and demonstrates the relationship between overextension and interference. We view the interference effect as, not a logical fallacy on the conjunction, but a signal that out of the two constituent concepts, a new concept has emerged.