SCHOOL REPORT

Report on the Quantum Information Access andRetrieval Theory Winter School
Emanuele Di Buccio
Department of Information Engineering, University of Padova, Italy
dibuccio@dei.unipd.it
Abstract
QUARTZ (Quantum Information Access and Retrieval Theory) is an Innovative Training
Network that aims to educate its Early Stage Researchers to adopt a novel theoretically andempirically motivated approach to Information Access and Retrieval based on the quantum
mechanical framework that gives up the notions of unimodal features and classical ranking
models disconnected from context. The present document reports on the QUARTZ WinterSchool, one of the activities of the QUARTZ training programme. The school was held at
the Department of Information Engineering of the University of Padova, Padova, Italy, fromFebruary 7 to February 14, 2018. This report describes the goal of the school framed within
the training activities of the QUARTZ project, how the school was structured in terms oflectures and activities devoted to the acquisition of transversal skills.

1

Introduction

QUARTZ (Quantum Information Access and Retrieval Theory) is an Innovative Training
Network (ITN) that aims to educate its Early Stage Researchers (ESRs) to adopt a novel
theoretically and empirically motivated approach to Information Access and Retrieval (IAR)
based on the quantum mechanical framework that gives up the notions of unimodal features and classical ranking models disconnected from context. [1] The objective of ITNs is
to “raise excellence and structure research and doctoral training in Europe, extending the
traditional academic research training setting, incorporating elements of Open Science andequipping researchers with the right combination of research-related and transferable competences.” [2] In ITNs, joint research training and/or doctoral programmes are implemented
by partnerships of actors from diﬀerent countries across Europe and beyond — examples ofactors are universities, research institutions, and businesses. The QUARTZ project involves
seven organizations: University of Padova (Italy), The Open University (UK), Universityof Bedfordshire (UK), Vrije Universiteit Brussel (Belgium), University of Copenhagen (Denmark), Brandenburg University of Technology Cottbus-Senftenberg (Germany), and Linnæus
University (Sweden). QUARTZ consists of thirteen individual ESR projects.
The QUARTZ training activities aim at helping the ESRs to achieve the best scientiﬁcand technological preparation in IAR and the quantum mechanical framework, international
relationships with leading research groups in Europe and outside Europe, transversal skills
useful to disseminate their own research work at the highest level possible, and to get a

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deep understanding of the strategic priority of “Open Science” [3]. The QUARTZ training
activities aim at complementing the doctoral schools oﬀered by the organizations.
The training programme of QUARTZ is organized in three main areas:• training through research (e.g. supervision, workshops)• training activities• transversal skill training
The Winter School1 was held at the Department of Information Engineering of the Universityof Padova (Italy) from February 7 to February 14, 2018; no activities were carried out during
the weekend (February 10-11). Besides ESRs, the school welcomed two external participants.
The QUARTZ Winter School was intended to train the ESRs in the multidisciplinary andintersectoral areas of QUARTZ including abstract vector spaces, probability, logic, machinelearning, audio-visual information processing, decision and cognition. Besides lectures onthese topics, the school included training activities devoted to the acquisition of transversal
skills, such as how to design a research video and practical hints on agile techniques forknowledge workers.
The ﬁrst QUARTZ Workshop was held in conjunction with the school, on the afternoon
of February 7. The goal of the workshop was to give the ESRs an environment for meetingthe senior researchers of the participating organizations and for presenting themselves to theother colleagues of the network. The workshop consisted of the ESR’s self-introduction.

2

Lectures

The QUARTZ Winter School included 15 invited lectures by speakers both from companies
and academia. A short description of the lectures is provided below.
• Introduction to Information Access and Retrieval by Massimo Melucci, University of Padova, Italy.
The lecture was focused on the introduction of the main IR concepts, IR models and
Evaluation. The lecture introduced the IR problem and fundamental concepts such as
information, data, query and relevance; the main concepts and components of an IR
system were also introduced (e.g. term, posting, index). The lecture covered diﬀerent retrieval models: boolean logic modelling, vector space-based models, probabilistic
models and statistical language models. The ﬁnal part of the lecture covered the topic
of Evaluation in IR.
• User Interaction and Modelling in Multimedia IR by Haiming Liu, Universityof Bedfordshire, United Kingdom.
This lecture started with the introduction of the problem of Multimedia Information
Retrieval (MIR), discussing peculiar issues that diﬀerentiate MIR from text-based IR.
It was then introduced how the users could be brought into the search loop, speciﬁcally
how to exploit user interactions and how to model the user. As regards the former, thelecture covered how forms of user interactions could be adopted to support retrieval
and to support design (e.g. user interfaces design). As regards the latter, frameworks
for user modelling such as the information foraging theory were introduced.
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http://www.quartz-itn.eu/training/winter-school

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• Introduction to Machine Learning by Roi Blanco, Amazon – Core Machine Learning, Spain.
This lecture aimed at the introduction of the basic concepts of Machine Learning (ML)and of the role of ML in IR. The lecture started with the introduction of ML basics, themain components of ML algorithms and the main types of learning problems (supervised, semi-supervised, unsupervised, reinforcement learning). Several supervised ML
algorithms were brieﬂy introduced. Evaluation of ML algorithms and the problem ofgeneralization were then discussed. The last part of the lecture was focused on ML for
IR. Learning to Rank was introduced and diﬀerent classes of loss functions (point-wise,pair-wise, list-wise) used in IR were presented. The lectures ended with some recommendations for IR students when approaching ML techniques to address their researchquestions.
• Research in video. Main guidelines to communicate scientific results withvideo by Marco Toﬀanin, University of Padova, Italy.
The goal of this lecture was to provide the students with the basics on how to make avideo for research. The lecture introduced the three main steps that need to be carried out: pre-production (scriptwriting), production (shooting), and post-production(editing). As regards production, practical hints to avoid common mistakes were presented; examples were provided to show the eﬀect of diﬀerent choices in production. As
regards post-production multimedia principles were introduced. The ﬁnal part of thelecture covered also some issues related to copyright, provided some sources for creative
commons contents, and a list of software that could be used for the post-production
step.
• Introduction to Quantum Information and its applications by Giuseppe Vallone, University of Padova, Italy.
In this lecture an introduction to Quantum Information was provided. The lecture
started with the introduction of the basic concepts of Quantum Mechanics, e.g. thenotion of state, the superposition principle, measurement and no-cloning theorem, andthe uncertainty principle. The lectures then covered Quantum Key Distribution, protocols involving Entanglement (e.g. Quantum Teleportation) and Quantum Random
Number Generators.
• Empirical Foundations of Quantum Cognition by Zheng Wang, The Ohio State
University, United States.
Quantum theory provides a uniﬁed and powerful explanation for a wide variety ofparadoxes found in human cognition and decision research ranging from attitude, inference, causal reasoning, judgment and decision, to perception and memory. This lecture
reviewed applications of quantum cognition where classical models fail, including (1)conjunction/disjunction errors that violate rules of classical probability, (2) questionorder eﬀects that violate commutativity, (3) interference eﬀects that violate the lawof total probability, (4) context eﬀects that violate joint probabilities (including violations of Bell type inequalities), (5) asymmetric similarity judgments and violations of
Euclidean distance models. This lecture focused on this new theoretical and modelingapproach to a wide variety of empirical cognitive phenomena using a uniﬁed, common
set of theoretical principles.

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Vol. 52 No. 2 December 2018• Theoretical Foundations of Quantum Cognition by Jerome Busemeyer, Indiana
University, United States.
Quantum cognition is a rapidly growing new approach to building computational modelsof cognition and decision. The cognitive revolution in the 1960s was based on classicalcomputational logic; the connectionist and neural network movements in the 1970s
were based on classical dynamical systems; the current Bayesian cognition movement
is based on classical probability theory. These classical assumptions remain at theheart of all these theories, and they are so commonly and widely applied that we takethem for granted. However, what are the critical but hidden assumptions upon which
all traditional theories rely? In this lecture, it was reviewed how quantum theory
provides a fundamentally diﬀerent approach to logic, reasoning, probabilistic inference,and dynamical systems in cognition and decision research. For example, quantum
logic does not follow the distributive axiom of Boolean logic; quantum probabilities do
not obey the disjunctive axiom of Kolmogorov probability; quantum reasoning does notobey the principle of monotonic reasoning. It turns out that humans do not always obey
these classical restrictions either and a lot of puzzling human behaviors are consistent
with predictions based on quantum models. This lecture provided an exposition of thebasic assumptions of classical versus quantum theories. These basic assumptions were
examined, side-by-side, in a parallel and elementary manner.
• Introduction to Information Retrieval and Quantum Mechanics by Massimo
Melucci, University of Padova, Italy.
This lecture introduced Quantum Theory IR Models and Frameworks. The lecture
started by explaining how Quantum Theory inspired IR, Quantum Probability, thenotions of superposition, interference and incompatibility and how these notions are
related to some IR concepts and issues. The Quantum Probability Ranking principle was then introduced. The lecture then covered how the mathematical constructof vector space basis can be used to model context and how the generalized view ofprobability rooted in the quantum mechanical framework can be adopted to computethe probability of context. The last part of the lecture discussed retrieval as a problem
of context detection, speciﬁcally using quantum detection theory.
• Quantum Logic by Ingo Schmitt, Brandenburg University of Technology CottbusSenftenberg, Germany.
This lecture provided an introduction to quantum logic. The talk started with a motivating example. After recalling some mathematical constructs like poset and latticetheory it was shown, that all projectors together with their operations intersection
and convex hull of union form a speciﬁc lattice which is the basic of quantum logic.
Quantum logic is diﬀerent from Boolean algebra. Next, the negation was introduced.
Important properties of the logic were identiﬁed and consequences in practical use were
derived. It was shown that the projector lattice contains subsets of projectors whichobey Boolean algebra laws. Finally, a weighting scheme of operands of logical operations
was introduced.
• Natural Language Processing and Computational Linguistics by Toine Bogers,
Aalborg University Copenhagen, Denmark.
This lecture provided the students with an introduction to Natural Language Processing(NLP) as well as a more detailed look at two speciﬁc applications of NLP: vector

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Vol. 52 No. 2 December 2018semantics and text classiﬁcation. A deﬁnition of NLP was provided along with an
introduction of the levels of linguistic analysis and the main sources for complexity of
NLP. Then NLP applications and a generic architecture shared by most NLP tools were
presented. The second part of the lecture was focused on vector semantics, providing thestudents with an introduction to distributional semantics, to the problem of measuring
word similarity and to evaluation. The last part of the lecture was focused on Text
Classiﬁcation, particularly on the Nave Bayes classiﬁcation method, on the evaluationof text classiﬁers, and on practical issues that should be addressed when working withclassiﬁers.
• Design and Evaluation of Machine Learning based Information Retrieval
Systems by Emanuele Di Buccio, University of Padova, Italy.
The lecture started with a brief review on the use of Machine Learning technologies
to train a ranking model. The lecture was focused on two uses: how to automaticallytune free parameters of IR models, if any, and approaches to learn how to optimallycombine features. A brief review of ad-hoc IR and a concise introduction to evaluation
campaigns, test collections, and eﬀectiveness measures were provided. Ranking functions with free parameters (e.g. BM25) were then introduced. The lecture then focusedon the problem of the optimization of free parameters, the motivations for optimizing
ranking functions, a methodology to perform optimization and possible strategies toﬁnd the most eﬀective parameter setting. The problem of optimization of parameters
was then discussed with regard to other IR tasks, e.g. relevance feedback. Some open
source software libraries were brieﬂy presented. The ﬁnal part of the lecture was focused on Learning to Rank (LtR), speciﬁcally on a methodology for LtR and on theevaluation of LtR algorithms; some available test collections (e.g. LETOR datasets)
and open source software libraries were presented.
• Polyrepresentation in a Quantum-inspired Information Retrieval Framework by Ingo Frommholz, University of Bedfordshire, United Kingdom.
A recent development in information access and retrieval is the utilisation of the theory of quantum mechanics as an expressive integrated framework to capture a user’s
context and interaction with the system. In this lecture it was brieﬂy introduced thefundamentals behind the proposed quantum-theoretical information access and retrieval
framework. It was discussed how information needs and relevance can be expressed in
the proposed interactive framework, neatly combining geometry and (quantum) probability theory. A further well-established cognitive principle in information retrieval
is polyrepresentation (or multiple evidence). Polyrepresentation states that the relevance of a document with respect to diﬀerent representations determines its overall
relevance. It was discussed how this principle can be integrated into the proposed
quantum-inspired framework.
• From Cognition to Computer Science I: Quantum Models of Cognition by
Sandro Sozzo, University of Leicester, United Kingdom.
Traditional approaches to cognitive psychology model human judgment and decisionmaking using set-theoretical structures. However, accumulating empirical ﬁndings reveal that these structures are generally unable to model concrete human decisions,which makes problematical the interpretation of several cognitive phenomena in termsof classical logic and probability, and massively inﬂuences the development of applied
disciplines, such as linguistics and artiﬁcial intelligence. Meanwhile, growing research

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indicates that quantum theory provides the conceptual and mathematical framework
to deal with these classically problematical situations in cognition. In this lecture, it
was ﬁrstly introduced the combination problem of concept theory, that is, the problem
of coherently representing the combination of two (or more) concepts in terms of therepresentation of the component concepts. Then, it was shown that classical modelling
approaches lead to paradoxical conclusions, illustrated, e.g., by over-/under-extension
eﬀects in membership judgments, Guppy eﬀects and borderline contradictions. It wasthen presented a quantum-theoretic framework for conceptual categorization which allows to faithfully represent diﬀerent sets of data on conjunctions, disjunctions andnegations of two concepts, explaining, at the same time, the observed deviations fromclassicality in terms of genuine quantum eﬀects. It was shown how the quantumtheoretic framework can be successfully applied to more complex cognitive situations,like conjunctive and disjunctive fallacies, and disjunction eﬀects. It was then put forward an explanatory hypothesis on human reasoning, which enables us to reconcile awhole set of cognitive phenomena under a unitary, rather than fragmented, framework.
• From Cognition to Computer Science II: A Quantum Model of the World
Wide Web by Massimiliano Sassoli de Bianchi, Brussels Free University, Belgium.
In this lecture it was shown that the approach oﬀers a fundamental strategy for modelingthe meaning associated with collections of documental entities, taking the World Wide
Web as a paradigmatic example. In doing so, it was emphasized the importance ofdistinguishing the Web, made of printed documents, from a more abstract meaning
entity, called the Quantum Web, where the former is considered to be the collectionof traces that can be left by the latter, in speciﬁc measurements, similarly to how
a non-spatial quantum entity like an electron can leave localized traces of impact on
a detection screen. The double-slit experiment was extensively used to illustrate therationale of the proposed model, which is guided by how physicists constructed quantum
theory to describe the behavior of the microscopic entities. It was emphasized that thesuperposition principle and the associated interference eﬀects are not suﬃcient to model
all experimental probabilistic data, like those obtained by counting the relative numberof documents containing certain words and co-occurrences of words. For this, additionaleﬀects, like context eﬀects, must also be taken into consideration.
• Agile for knowledge workers: practical hints by Marco Dussin and Ivano Masiero,Independent Consultants, Italy.
This lecture consisted in two activities: the Marshmallow Design Challenge2 and theDot Game3 . These two activities are a useful tool to present and to foster discussion
on some concepts related design and productivity. The ﬁrst activity was originallyproposed by Peter Skillman and was designed in order to show the importance of learning by doing and of addressing a problem with multiple iterations building successive
prototypes to ﬁx. The Dot Game is a real-time simulation of an assembly line where
three types of actors are involved: some workers, a tester, and a client. The gameallows typical behavioral patterns of work group to be shown and some concepts to beunderstood by means of a direct involvement in the simulation – e.g. how people infront of a bottleneck are causing problems when adding more work, or that much workin progress adds waste and makes it harder to detect and ﬁx problems. The activities
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https://www.youtube.com/watch?v=H0_yKBitO8M
https://www.netobjectives.com/system/files/DotGame_vas11_0.pdf

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were followed by a discussion among the participants and lead by the lecturers, whose
objective was to make explicit some issues that emerge when working in groups andthat should be addressed in order to increase both the productivity and the quality of
the work.

3

Team Building Activity

The team building activity was designed in order to encourage the collaboration between thestudents by carrying out a small project. The task assigned to the students was to design aworkshop related to the main topic of the QUARTZ project: Quantum Information Accessand Retrieval Theory. The students were divided in three groups (the number of componentsof each group ranged from three to four); group members were selected in order to avoid thepresence of students from the same organization in the same group. The task was presented
to the students on the afternoon of February 8. When describing the task (design a workshop
on quantum information access and retrieval) no speciﬁc guidelines were provided. The main
reason for this choice was not to bias the students towards speciﬁc solutions, thus allowing
them to propose solutions other than the mini-conference format. The only “requirement”
was to design a workshop fostering high interaction among participants. Each group worked
in a separated room in order to minimize the interaction among groups during the activity.
Each group was asked to produce internal minutes at the end of each team building session.
The main issue that emerged in the ﬁrst session dedicated to the team building activity
was to deﬁne a more focused topic for the workshop: Quantum Information Access andRetrieval was perceived as too broad. An approach shared by the diﬀerent groups was to startfrom their own expertise and the topic of their ESR project in order to identify crucial issues
to be addressed or a shared interdisciplinary approach involving the quantum mechanicalframework. When designing the team building activity, a too broad topic was selected on
purpose in order to stimulate the discussion among the ESRs on the issues perceived as
crucial in Quantum IAR Theory.
The team building activity was also carried out in the last of time-slot on Friday 9 andin the morning of February 14. On February 14 the groups were asked to produce a shortpresentation to discuss their proposal in front of the other groups and the school participants.
There were three very diﬀerent proposals. The ﬁrst group reported on a proposal for a
Quantum IAR framework combining poly-representation, ontologies and multi-modal information retrieval. They worked on a paper proposal; working on a paper was a way to deﬁnea more speciﬁc topic on which a workshop could be focused. The second group proposed aworkshop on Quantum Inspired Neural Networks for IR. They presented related works on thesubject, discussed several open issues, and proposed a workshop based on a tutorial format;
the last part of the proposed workshop included a hand on session to implement Quantum
Inspired Neural Networks IR models. The third group proposed a workshop in the “miniconference format”, providing a complete proposal in terms of topics of interest, submission
format, and keynote speakers; each member of the group was assigned to a speciﬁc role in
the organization of the workshop.
After each presentation, there was a brief discussion on the proposal and suggestions were
provided by the other participants.
The main objective of the activity was to give to the ESRs the opportunity to startworking on a project or on a topic together, to provide them with a ﬁrst venue to discuss

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research questions that they perceive as crucial for the QUARTZ project and Quantum
IAR Theory in general. The proposals, the general discussion, and the ﬁnal atmosphere ofcollaboration suggested that the activity fostered interactions in the intended direction.

4

Conclusions

The QUARTZ Winter School was intended to train the ESRs in the multidisciplinary andintersectoral areas relevant to the QUARTZ project, which include abstract vector spaces,
probability, logic, machine learning, audio-visual information processing, decision and cognition. This objective was successfully achieved through the high-quality lectures given byinvited speakers both from companies and academia. Moreover, the school beneﬁted fromthe level of interaction of the ESRs, that actively participated to the lectures. One of theobjectives of the school was to provide the ESRs with a venue to discuss both with seniorresearchers and their peers research questions that they perceive as crucial. The active participation of the ESRs during the lectures, the interaction and the collaboration among ESRs
during the transversal skills training activities and the work they carried out during the teambuild activity suggest that this objective was successfully achieved.

5

Acknowledgements

We would like to thank all lecturers and participants to QUARTZ Winter School who madethe school a success through their valuable contributions. Special thanks go to the Department of Information Engineering of the University of Padova for hosting the school and forthe logistic support.
The activities were carried out as part of a project that has received funding fromthe European Union’s Horizon 2020 research and innovation programme under the Marie
Sklodowska-Curie grant agreement No 721321.

References[1] Quantum Information Access and Retrieval Theory (QUARTZ) Innovative Training Network. http://www.quartz-itn.eu/. Accessed: 2018-10-31.
[2] Innovative Training Networks.
http://ec.europa.eu/research/participants/
portal/desktop/en/opportunities/h2020/topics/msca-itn-2018.html. Accessed:
2018-10-31.
[3] Goals of research and innovation policy.
https://ec.europa.eu/info/
research-and-innovation/strategy/goals-research-and-innovation-policy_
en#openscienc. Accessed: 2018-10-31.

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