Silvia Likavec

Propagating User Interests in Ontology-Based User Model

In this paper we address the problem of propagating user interests in ontology-based user models. Our ontology-based user model (OBUM) is devised as an overlay over the domain ontology. Using ontologies as the basis of the user profile allows the initial user behavior to be matched with existing concepts in the domain ontology. Such ontological approach to user profiling has been proven successful in addressing the cold-start problem in recommender systems, since it allows for propagation from a small number of initial concepts to other related domain concepts by exploiting the ontological structure of the domain. The main contribution of the paper is the novel algorithm for propagation of user interests which takes into account i) the ontological structure of the domain and, in particular, the level at which each domain item is found in the ontology; ii) the type of feedback provided by the user, and iii) the amount of past feedback provided for a certain domain object.

Behavioural inverse limit λ-models

We construct two inverse limit λ-models which completely characterise sets of terms with similar computational behaviours: the sets of normalising, head normalising, weak head normalising λ-terms, those corresponding to the persistent versions of these notions, and the sets of closable, closable normalising, and closable head normalising λ-terms. More precisely, for each of these sets of terms there is a corresponding element in at least one of the two models such that a term belongs to the set if and only if its interpretation (in a suitable environment) is greater than or equal to that element. We use the finitary logical description of the models, obtained by defining suitable intersection type assignment systems, to prove this.

Strong normalization of the dual classical sequent calculus

We investigate some syntactic properties of Wadler’s dual calculus, a term calculus which corresponds to classical sequent logic in the same way that Parigot’s λμ calculus corresponds to classical natural deduction. Our main result is strong normalization theorem for reduction in the dual calculus; we also prove some confluence results for the typed and untyped versions of the system.

Interacting with social networks of intelligent things and people in the world of gastronomy

This article introduces a framework for creating rich augmented environments based on a social web of intelligent things and people. We target outdoor environments, aiming to transform a region into a smart environment that can share its cultural heritage with people, promoting itself and its special qualities. Using the applications developed in the framework, people can interact with things, listen to the stories that these things tell them, and make their own contributions. The things are intelligent in the sense that they aggregate information provided by users and behave in a socially active way. They can autonomously establish social relationships on the basis of their properties and their interaction with users. Hence when a user gets in touch with a thing, she is also introduced to its social network consisting of other things and of users; she can navigate this network to discover and explore the world around the thing itself. Thus the system supports serendipitous navigation in a network of things and people that evolves according to the behavior of users. An innovative interaction model was defined that allows users to interact with objects in a natural, playful way using smartphones without the need for a specially created infrastructure. The framework was instantiated into a suite of applications called WantEat, in which objects from the domain of tourism and gastronomy (such as cheese wheels or bottles of wine) are taken as testimonials of the cultural roots of a region. WantEat includes an application that allows the definition and registration of things, a mobile application that allows users to interact with things, and an application that supports stakeholders in getting feedback about the things that they have registered in the system. WantEat was developed and tested in a real-world context which involved a region and gastronomy-related items from it (such as products, shops, restaurants, and recipes), through an early evaluation with stakeholders and a final evaluation with hundreds of users.

Semantic similarity in heterogeneous ontologies

Recent extensive usage of ontologies as knowledge bases that enable rigorous representation and reasoning over heterogenous data poses certain challenges in their construction and maintenance. Many of these ontologies are incomplete, containing many dense sub-ontologies. A need arises for a measure that would help calculate the similarity between the concepts in these kinds of ontologies. In this work, we introduce a new similarity measure for ontological concepts that takes these issues into account. It is based on conceptual specificity, which measures how much a certain concept is relevant in a given context, and on conceptual distance, which introduces different edge lengths in the ontology graph. We also address the problem of computing similarity between concepts in the presence of implicit classes in ontologies. The evaluation of our approach shows an improvement over Leacock and Chodorows distance based measure. Finally, we provide two application domains which can benefit when this similarity measure is used.

Property-based interest propagation in ontology-based user model

We present an approach for propagation of user interests in ontology-based user models taking into account the properties declared for the concepts in the ontology. Starting from initial user feedback on an object, we calculate user interest in this particular object and its properties and further propagate user interest to other objects in the ontology, similar or related to the initial object. The similarity and relatedness of objects depends on the number of properties they have in common and their corresponding values. The approach we propose can support finer recommendation modalities, considering the user interest in the objects, as well as in singular properties of objects in the recommendation process. We tested our approach for interest propagation with a real adaptive application and obtained an improvement with respect to IS-A-propagation of interest values.

Characterising Strongly Normalising Intuitionistic Terms

This paper gives a characterisation, via intersection types, of the strongly normalising proof-terms of an intuitionistic sequent calculus where LJ easily embeds. The soundness of the typing system is reduced to that of a well known typing system with intersection types for the ordinary λ-calculus. The completeness of the typing system is obtained from subject expansion at root position. Next we use our result to analyze the characterisation of strong normalisability for three classes of intuitionistic terms: ordinary λ-terms, ΛJ-terms λ-terms with generalised application, and λx-terms λ-terms with explicit substitution. We explain via our system why the type systems in the natural deduction format for ΛJ and λx known from the literature contain extra, exceptional rules for typing generalised application or substitution; and we show a new characterisation of the β-strongly normalising λ-terms, as a corollary to a PSN-result, relating the λ-calculus and the intuitionistic sequent calculus. Finally, we obtain variants of our characterisation by restricting the set of assignable types to sub-classes of intersection types, notably strict types. In addition, the known characterisation of the β-strongly normalising λ-terms in terms of assignment of strict types follows as an easy corollary of our results.

Intersection types for the resource control lambda calculi

We propose intersection type assignment systems for two resource control term calculi: the lambda calculus and the sequent lambda calculus with explicit operators for weakening and contraction. These resource control calculi, λ® and λ®Gtz, respectively, capture the computational content of intuitionistic natural deduction and intuitionistic sequent logic with explicit structural rules. Our main contribution is the characterisation of strong normalisation of reductions in both calculi. We first prove that typability implies strong normalisation in λ® by adapting the reducibility method. Then we prove that typability implies strong normalisation in λ®Gtz by using a combination of well-orders and a suitable embedding of λ®Gtz-terms into λ®-terms which preserves types and enables the simulation of all its reductions by the operational semantics of the λ®-calculus. Finally, we prove that strong normalisation implies typability in both systems using head subject expansion.

Safe and Flexible Objects with Subtyping

We design a calculus where objects are created by instantiating classes, as well as mixins. Mixin-instantiated objects are “incomplete objects”, that can be completed in an object-based fashion. The combination of class-based features with object-based ones offers some flexible programming solutions. The fact that all objects are created from fully-typed constructs is a guarantee of controlled (therefore reasonably safe) behavior. Furthermore, the calculus is endowed with width subtyping on complete objects, which provides enhanced flexibility while avoiding possible conflicts between method names.

A Core Calculus of Higher-Order Mixins and Classes

This work presents an object-oriented calculus based on higher-order mixin construction via mixin composition, where some software engineering requirements are modelled in a formal setting allowing to prove the absence of message-not-understood run-time errors. Mixin composition is shown to be a valuable language feature enabling a cleaner object-oriented design and development. In what we believe being quite a general framework, we give directions for designing a programming language equipped with higher-order mixins, although our study is not based on any already existing object-oriented language.