  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.

Computation and Language;Information Retrieval;Quantum Physics