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A Recommendation Algorithm Based on Automatic Meta-path Generation and Relationship Aggregation
No full textPart 4: Recommendation and Social ComputingInternational audienceKnowledge Graph (KG) contains rich semantic information and supports knowledge reasoning. In recent years, introducing KG as auxiliary information into the recommender system has become one common measure for improving recommendation quality. The unified graph, which is constructed from the KG and user-item matrix in recommender systems, contains meta-paths formed by single-hop/continuous multi-hop connectivity relationships, and these meta-paths can assist modeling of user preferences. The quality of manually designed meta-paths is prone to the type and number of human-defined meta-paths. Moreover, the process of defining meta-paths is time-consuming and labor-intensive, and inadequate sufficient considerations in design will have an adverse impact on the quality of recommendations. We propose a self-supervised meta-path generation approach that does not rely on domain knowledge to select valuable path information from the unified graph and can deliver high-quality recommendations and reduce noises. Previous studies on meta-paths mainly focused on the neighbor information of nodes and ignored the edges that represents relationships between nodes. We develop a meta-path-based relational path-aware strategy to discover the relational information included within the meta-path. To make the use of the global structure in the unified graph and the information within the local scope in the user-item bipartite graph and KG, a two-level relationship aggregator to fully aggregate the fine-grained semantic information and multi-hop semantic associations is also proposed. We conducted experiments on two public datasets, MovieLens and Book-Crossing to verify the effectiveness of the proposed algorithm. The experimental results show that the recommendation algorithm outperforms the baseline models in terms of AUC, Recall@K, and F1 in most cases
Information Technology in Disaster Risk Reduction: 8th IFIP WG 5.15 International Conference, ITDRR 2023Tokyo, Japan, December 4–6, 2023
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Electronic Government: 23rd IFIP WG 8.5 International Conference, EGOV 2024, Ghent-Leuven, Belgium, September 3–5, 2024, Proceedings
No full textInternational audienceBook Front Matter of LNCS 1484
From the Evolution of Public Data Ecosystems to the Evolving Horizons of the Forward-Looking Intelligent Public Data Ecosystem Empowered by Emerging Technologies
No full textPart 6: Emerging TopicsInternational audiencePublic Data Ecosystems (PDEs) represent complex socio-technical systems crucial for optimizing data use in the public sector and outside it. Recognizing their multifaceted nature, previous research proposed a six-generation Evolutionary Model of Public Data Ecosystems (EMPDE). Designed as a result of a systematic literature review on the topic spanning three decades, this model, while theoretically robust, necessitates empirical validation to enhance its practical applicability. This study addresses this gap by validating the theoretical model through a real-life examination in five European countries - Latvia, Serbia, Czech Republic, Spain, and Poland. This empirical validation provides insights into PDEs dynamics and variations of implementations across contexts, particularly focusing on the 6th generation of forward-looking PDE generation named “Intelligent Public Data Generation” which represents a paradigm shift driven by emerging technologies such as cloud computing, Artificial Intelligence (AI), Natural Language Processing tools, Generative AI, and Large Language Models with potential to contribute to both automation and augmentation of business processes within these ecosystems. By transcending their traditional status as a mere component, evolving into both an actor and a stakeholder simultaneously, these technologies catalyse innovation and progress, enhancing PDE management strategies to align with societal, regulatory, and technical imperatives in the digital era
Prototyping Cross-Reality Escape Rooms
No full textPart 1: Full Research PapersInternational audienceWith more and more applications exploring the possibilities of AR and VR, some applications do not stay inside one reality but operate cross-reality. We propose the concept of a cross-reality escape room, where one player is in the real world interacting with real objects and one player is in a virtual world. They have to work together to solve a series of puzzles to complete the game. The actions one player does on their side can directly affect the other player’s world. Besides the concept of cross-reality escape rooms, we also provide an end-user editor to create such games. The editor aims to enable non-technical users, like designers for conventional escape rooms, to create their own cross-reality escape room, including creating and positioning objects and integrating and configuring a logic flow that drives the application. This allows virtual objects to be configured as well as real-life objects.To evaluate the concept and editor, twelve participants in groups of two first played a demo escape room and used the editor to create part of a room themselves. They were asked to give quantitative and qualitative feedback for both parts. With a score of 55.17 out of possible 63 on the Game User Experience Satisfaction Scale (GUESS)-18, we can say, that players like the demo room, we created. Combined with results from open feedback sessions, the players liked the concept, and that cross-reality adds value to the concept of escape rooms. However, there is still potential to improve. For the editor, we received mixed results, that depend heavily on the individual users. During semi-structured interviews, we could also create a list of improvements for future versions
End-User Development of Oracle APEX Low-Code Applications Using Large Language Models
No full textPart 5: DemosInternational audienceThe natural-language understanding, code generation, and reasoning abilities of Large Language Model (LLMs) have the potential to speed up development times, especially when combined with Low-Code Development Platform (LCDPs). They could also enable end-users to make small to medium-sized changes themselves, while experienced developers can focus on the more complicated development tasks. This paper demos a prototype implementation of this concept. It enables end-users to edit Oracle Application Express (APEX) low-code applications using natural language in a chat-like user interface (UI) powered by the GPT-4 Turbo LLM. We also evaluate this prototype in a qualitative user study with APEX customers from the industry and find that they generally like both the concept and the prototype. The main problem that the study uncovered is a lack of a common vocabulary between the LLM and the users. Participants suggest to solve this by integrating support features like a glossary and an element type and name inspector into the prototype
Coordination Models and Languages: 26th IFIP WG 6.1 International Conference, COORDINATION 2024, Held as Part of the 19th International Federated Conference on Distributed Computing Techniques, DisCoTec 2024Groningen, The Netherlands, June 17–21, 2024
No full textInternational audienceThis book constitutes the refereed proceedings of the 26th IFIP WG 6.1 International Conference on Coordination Models and Language, COORDINATION 2024, held in Groningen, The Netherlands, in June 2024, as part of the 19th International Federated Conference on Distributed Computing Techniques, DisCoTec 2024.The 8 full papers, 7 tool papers, 1 short paper and 1 survey paper included in this book were carefully reviewed and selected from 28 submissions. This conference provides a well-established forum for the growing community of researchers interested in models, languages, architectures, and implementation techniques for coordination
A Probabilistic Choreography Language for PRISM
No full textPart 1: Regular PapersInternational audienceWe present a choreographic framework for modelling and analysing concurrent probabilistic systems based on the PRISM model-checker. This is achieved through the development of a choreography language, which is a specification language that allows to describe the desired interactions within a concurrent system from a global viewpoint. Employing choreographies provides a clear and comprehensive view of system interactions, enabling the discernment of process flow and detection of potential errors, thus ensuring accurate execution and enhancing system reliability. We equip our language with a probabilistic semantics and then define a formal encoding into the PRISM language and discuss its correctness. Properties of programs written in our choreographic language can be model-checked by the PRISM model-checker via their translation into the PRISM language. Finally, we implement a compiler for our language and demonstrate its practical applicability via examples drawn from the use cases featured in the PRISM website
Binary Opinion Models of Influence and Opinion Dynamics in Social Networks
No full textPart 1: Invited PapersInternational audienceThe process of influence and opinion dynamics is predominant in many kinds of real-life situations involving agents’ interactions. This phenomenon is extensively analyzed in different fields and with the help of various methods and tools. Network analysis is particularly suitable for the study of influence and opinion formation. The aim of this paper is to provide an overview of selected results on models of influence and opinion dynamics in social networks with non-strategic updating of binary opinions. We start with presenting some results on the relation between a static binary opinion model of influence with influence indices, follower and influence functions, and a framework of simple games called command games. Then, we focus on binary opinion dynamics with non-strategic agents embedded in a social network. In this overview, a special attention is paid to models based on aggregation functions which can be seen as a generalization of the threshold model. In particular, we present some of the main results of the convergence analysis concerning anonymous social influence, conformism and anti-conformism in social networks. Also the phenomenon of diffusion in large networks with the diffusion mechanism represented by an aggregation function is briefly presented. Finally, we conclude this overview paper by indicating some possible directions for future research on the discrete opinion dynamics in social networks
Challenging the Future with Lean: 9th IFIP WG 5.7 European Lean Educator Conference, ELEC 2023, 's-Hertogenbosch, The Netherlands, October 24-26, 2023, Proceedings
No full textInternational audienceBook Front Matter of AICT 68