bluuebunny/crossref_metadata_2025 huggingface dataset:
Achieving Organisational Benefits with Social Media Analytics
Authors: Bekmamedova Nargiza  , Shanks Graeme  , Carlsson Sven
Published: February 2025

Social media analytics (SMA) involves the analysis of vast amounts of social media data to provide insights to organisational decision-makers. Many organisations are investing in SMA but few describe themselves as effective adopters. In this paper, a framework for achieving benefits with social media analytics is presented, based on SMA motivations, the resource-based view (RBV) and dynamic capabilities theory. Concepts in the framework are clearly defined and two propositions are developed, based on relationships in the framework. Finally, we discuss implications of the framework for researchers and practitioners and suggest directions for future research.
Barriers of Using Social Media to Support Health-related Decisions: A Sociomaterial Perspective
Authors: Pousti Hamid  , Burstein Frada
Published: February 2025

In the recent years, there has been a strong trend of using social media by the patients, carers, and practitioners to support chronic care management decisions. Studies also show that social media have promising potentials in this area; however, the findings from our exploratory study suggested that there are yet many uncertainties and barriers perceived around the usefulness of using social media for healthcare decision making. The purpose of this study is to explore and unravel the barriers of using social media in the management of chronic disease. We argue that sociomaterial perspective provides a new way of understanding the relation between technology and human decision-making in a complex social phenomenon such as the management of chronic disease.
A Hierarchical Multi-Attribute Model for Bank Reputational Risk Assessment
Authors: Bohanec Marko  , Aprile Giorgio  , Costante Maria  , Foti Morena  , Trdin Nejc
Published: February 2025

A decision support model aimed at the assessment of reputational risks associated with bank operation is presented in this paper. The innovative aspect of the model is that it combines different types and sources of information: structured and unstructured, quantitative and qualitative, internal and external. Unstructured, qualitative and external aspects are represented by sentiment of news and blogs about bank counterpart organisations. The model is multi-attribute and hierarchical, and is composed of three modules: basic data processing, qualitative evaluation, aggregation; these are described in detail. This paper also presents a prototype implementation of the model, illustrates its application on real-life data, and reports on experts' opinion about the model and its use.
Positive Change: Connecting the Virtual and the Real
Authors: Wiederhold Brenda K.  , Riva Giuseppe
Published: February 2025

How do we lastingly change our lives for the better? There is not an easy answer to this question. However, due to the advances in psychology and neuroscience, now we have a better view of personal change, that is not limited to a specific viewpoint. In particular, the emergence of integrative and transdiagnostic accounts suggests that change is contextual, depending on the person, the issues, and the situation. More, personal change is a process, happening in discontinuous and nonlinear ways, following life transitions and traumatic events. In this process a key role can be played by technology: using the “Positive Technology” approach it is possible to use technology to manipulate the quality of experience, with the goal of increasing wellness, and generating strengths and resilience in individuals, organizations and society.
Simulated Job Interview Improves Skills for Adults with Serious Mental Illnesses
Authors: Humm Laura Boteler  , Olsen Dale  , Be Morris  , Fleming Michael  , Smith Matthew
Published: February 2025

Adults with serious mental illnesses (e.g., Autism Spectrum Disorder [ASD], schizophrenia, post-traumatic stress disorder [PTSD]) often have difficulties obtaining employment. The Job Interview Training System with Molly Porter, developed in collaboration with Yale and Northwestern Universities and vocational rehabilitation specialists with funding from The National Institutes of Health (R43/44MH080496), allows learners to practice job interviews on computers in a stress free environment. The system includes user-driven educational materials, an interactive job application, a practice simulation with a fictional interviewer (Molly Porter), and extensive feedback. SIMmersion's PeopleSIM™ technology allows each conversation with Molly to provide a unique interview experience, enabling users to gain confidence while building skills. The on-screen coach provides insight during the conversation, and a comprehensive after-action review provides learners with feedback on the entire interview. In a randomized control trial, the system was proven effective at improving participants' interview skills and confidence. Ninety-six (96) unemployed adults with ASD (n=26), schizophrenia/other (n=37) or PTSD (n=33) were recruited. Participants were randomized into control (n=32) and experimental (n=64) conditions. The control group was “wait-listed” to receive training, and the experimental group used the training system with Molly Porter. Both groups completed pre- and post-intervention role-play interviews and self-assessment questionnaires. Analyses of covariance showed that the simulation provided a highly significant training effect, with experimental group participants scoring better in the role-play interviews and self-assessing higher than control group participants. By increasing skills and confidence, this system may ultimately reduce the length of unemployment for adults with mental illnesses.
Effects of Simulation Fidelity on User Experience in Virtual Fear of Public Speaking Training – An Experimental Study
Authors: Poeschl Sandra  , Doering Nicola
Published: February 2025

Realistic models in virtual reality training applications are considered to positively influence presence and performance. The experimental study presented, analyzed the effect of simulation fidelity (static vs. animated audience) on presence as a prerequisite for performance in a prototype virtual fear of public speaking application with a sample of N = 40 academic non-phobic users. Contrary to the state of research, no influence was shown on virtual presence and perceived realism, but an animated audience led to significantly higher effects in anxiety during giving a talk. Although these findings could be explained by an application that might not have been realistic enough, they still question the role of presence as a mediating factor in virtual exposure applications.
A Course Exam Scheduling Approach based on Data Mining
Authors: Ivančević Vladimir  , Knežević Marko  , Luković Ivan
Published: February 2025

We propose an exam scheduling approach to deal with problems that may appear in some oral exams, such as the cases when student turnout is considerably above or below expectation. As opposed to similar approaches, we focus on predicting the number of students applying for an exam by performing data mining on student records. Our predictive model considers previous student scores, attendance records, and past exam attempts. We evaluate the prediction segment of this approach on a real-world data set containing university records for a pair of database-related courses.
An Online Transfer Learning RBF Neural Network for Cross Domain Data Classification
Authors: Tan Shing Chiang  , Lim Chee Peng  , Seera Manjeevan
Published: February 2025

In this paper, a Radial Basis Function Network (RBFN) trained with the Dynamic Decay Adjustment (DDA) algorithm (i.e., RBFNDDA) is deployed as an incremental learning model for tackling transfer learning problems. An online learning strategy is exploited to allow the RBFNDDA model to transfer knowledge from one domain and applied to classification tasks in a different yet related domain. An experimental study is carried out to evaluate the effectiveness of the online RBFNDDA model using a benchmark data set obtained from a public domain. The results are analyzed and compared with those from other methods. The outcomes positively reveal the potentials of the online RBFNDDA model in handling transfer learning tasks.
A Safety Verification for e-Business Model Based on Paraconsistent Annotated Logic Program bf-EVALPSN
Authors: Alasuutari Aapo  , Nakamatsu Kazumi  , Abe Jair Minoro
Published: February 2025

In this article we show a logic programming based method for modelling and verifying online shopping transactions using before-after Extended Vector Annotated Logic Program with Strong Negation created by Kazumi Nakamatsu. The verifying is done on-line and can be used not only to check for standard error flags and possible problems but also before-after relations between different processes, creating a double fail safe against errors and attacks on the software.
Identifying and Assessing Walking Ability Using an Accelerometer and a Support Vector Machine
Authors: Shibata Shin-ichi  , Beniya Tomoaki  , Tajima Takuya  , Abe Takehiko  , Kimura Haruhiko
Published: February 2025

In response to an aging society, four people will be supporting each people aged 65 or over in our country. Rehabilitation as functional training is becoming more and more crucial as well as medical treatment in medical and welfare institution. The recovery of locomotor function for gait disorder like a parkinsonian tremor has important effects for the quality of life for the elderly. It is necessary for the elderly to evaluate the condition of walking ability by objective estimate data. But the ability has been evaluated by the subjective judgment of the physical therapist in the medical practice. Therefore, this method falls short of accuracy and generality for evaluating the patient's walking state. We carried out experiment aimed at discriminating the walking ability by three-axis acceleration sensor and Support Vector Machine (SVM) in order to evaluate the ability in an objective way. As a result, we obtained an average identification rate of 86.5% with the Gaussian kernel when the frequency component of the normalized acceleration was used for the feature quantity.
Expansion of the Orthogonal Basis in Video Compression
Authors: Balonin Nikolay  , Sergeev Mikhail
Published: February 2025

This article discusses the procedure of image compression using the Hadamard-Mersenne, Hadamard-Fermat matrices and derived from them orthogonal M-matrices. At the stage of image spectral decomposition it is proposed to use the original two-tier symmetric orthogonal M-matrices order, equal to the Mersenne and Fermat primes, as well as the low frequency filters relevant to them.
Flipped Classroom – From Experiment to Practice
Authors: Rutkowski Jerzy
Published: February 2025

The paper discusses use of ICT in Engineering Education, an engineering course redevelopment from Traditional Classroom model to Self-Directed Learning with Flipped Classroom model. This model has been introduced at the Faculty of Automatic Control, Electronics & Computer Science in the academic year 2012/2013, in teaching the Electric Circuits Theory. After the first year of experimenting, this model has become fully operational, however it is still improved. The case study results are presented, some guidelines are proposed. The paper main objective is an attempt to prove that SDL works, that it is the ultimate way to go, regardless difficulties faced at the introductory stage, students' unreadiness to SDL first of all.
Usage of augmented reality technology in the training given to military technical personnel
Authors: Szczekala Marek  , Karczmarz Dariusz  , Mądrzycki Przemysław  , Perz-Osowska Małgorzata
Published: February 2025

Practical experience gained by Air Force Institute of Technology team during usage of Augmented Reality application is presented in the paper. The aim of the research was to examine possibilities of using the augmented reality technology for training technical personnel, providing aid during technical maintenance procedures and diagnostics of complex technical systems. The prototype of application is presented which incorporates texts, signs, active virtual 2D and 3D objects, animated sequences and multimedia elements in the real world. The procedure of creating tasks and their structure, technological limitations as well as matters concerning markers detection and tracking is presented in the paper.
Smart Education as the Main Paradigm of Development of an Information Society
Authors: Tikhomirov Vladimir
Published: February 2025

The paper deals with the penetration of the smart concept into society with respect to education development. Emerging “smart” technologies have a great impact on students, course design, and knowledge communication, and these needs to be taken into account in the development of higher educational institution.
Context-based multi-model energy prediction algorithm using RLS estimation
Authors: Neves-Silva Rui  , Campos Ana Rita
Published: February 2025

The subject of this paper is developed in the scope of decision support to reduce energy consumption in industrial processes. It starts from the observation that context under production units are producing might have a strong influence on the specific energy consumption. In this line, this paper proposes an approach to model energy consumption taking the value of context variables in consideration. The approach is based on the estimation of multiple models, using RLS and valid in identified context regions, collecting the necessary knowledge to support future decision making processes. An example using experimental data from a cement factory is used to illustrate the proposed methodology.
Policy Recommendations for Open Access to Research Data in Europe – Stakeholder Values and Ecosystems
Authors: Sveinsdottir Thordis  , Wessels Bridgette A.  , Smallwood Rod  , Linde Peter  , Kala Vasso  , Tsoukala Victoria  , Sondervan Jeroen
Published: February 2025

RECODE will leverage existing networks, communities and projects to address challenges within the open access and data dissemination and preservation sector, and produce policy recommendations foropen access to research data based on existing good practice. The open access to research data sector includes several different networks, initiatives, projects and communities that are fragmented by discipline, geography, stakeholder category (publishers, academics, repositories, etc.) as well as other boundaries. Many of these organisations are already addressing key barriers to open access to research data, such as stakeholder fragmentation, technical and infrastructural issues, ethical and legal issues, and state and institutional policy fragmentation. However, these organisations are often working in isolation or with limited contact with one another. RECODE will provide a space for European stakeholders interested in open access to research data to work together to provide common solutions for these issues. RECODE will culminate in a series of over-arching policy recommendations for a policy framework tosupport open access to European research data targeted at different stakeholders and policy-makers. (http://www.recodeproject.eu).
How Can Libraries and Other Academic Institutions Engage in Making Data Open?
Authors: Linde Peter  , Wessels Bridgette A.  , Sveinsdottir Thordis  , Noorman Merel
Published: February 2025

In this paper we will address the questions of what and where the value of open access to research data might be and how libraries and related stakeholders can contribute to achieve the benefits of freely sharing data. In particular, the emphasis will be on how libraries need to acquire the competence for collaboration to train and encourage researchers and library staff to work with open data. The paper is based on the early results of the RECODE project, an EU FP7 project that addresses the drivers and barriers in developing open access to research data in Europe (http://www.recodeproject.eu).
EPISCIENCES – an overlay publication platform
Authors: Berthaud Christine  , Capelli Laurent  , Gustedt Jens  , Kirchner Claude  , Loiseau Kevin  , Magron Agnès  , Medves Maud  , Monteil Alain  , Riverieux Gaëlle  , Romary Laurent
Published: February 2025

This paper delineates the main characteristics of the Episciences platform, an environment for overlay peer-reviewing that complements existing publication repositories, designed by the Centre pour la Communication Scientifique directe (CCSDCCSD is a joint service unit between the CNRS, Inria and the University of Lyon
Comparison of Consumer Derived Evidence with an Omaha System Evidence-Based Practice Guideline for Community Dwelling Older Adults
Authors: Pruinelli Lisiane  , Fu Helen  , Monsen Karen A.  , Westra Bonnie L.
Published: February 2025

Consumer involvement in healthcare is critical to support continuity of care for consumers to manage their health while transitioning from one care setting to another. Validation of evidence-based practice (EBP) guideline by consumers is essential to achieving consumer health goals over time that is consistent with their needs and preferences. The purpose of this study was to compare an Omaha System EBP guideline for community dwelling older adults with consumer-derived evidence of their ongoing needs, resources, and strategies after home care discharge. All identified problems were relevant for all patients except for Neglect and Substance use. Ten additional problems were identified from the interviews, five of which affected at least 10% of the participants. Consumer derived evidence both validated and expanded EBP guidelines; thus further emphasizing the importance of consumer involvement in the delivery of home healthcare.
Development and Implementation of IT Require Focus on User Participation, Acceptance and Workflow
Authors: Sølling Ina Koldkjær  , Carøe Per  , Mathiesen Kirsten Siggaard
Published: February 2025

The study “Online Care” follows a municipal project “Online Welfare” where a nurse's presence in the citizen's own home was replaced by online communication. The paper is based on a citizen's perspective and seeks to develop meaningful workflow for the benefit of citizens with medical problems. The study examines five citizens' opinions on whether online communication in a meaningful way supports the citizens in what they associate with a good life. In addition, relatives and the citizen's nurse were interviewed individually concerning the same issues as the citizens. The study has been approved by the Danish System of Ethics in Science and is conducted in collaboration with Aalborg University, Aalborg Municipality and DanAge, (NGO). The municipality's goal of efficiency and financial savings regarding “Online Welfare” was not honored due to insufficient network infrastructure and technical problems. An adoption barrier was that the municipality did not determine the efforts and the goal of the project, who could benefit from participating and the requirements of the professionals and the organization including ethical considerations.It was difficult to find citizens who were willing to participate. Citizens, who were included in the study accepted and adopted the technology however, “Online Welfare” could not replace the care they used to receive. Therefore, the offer was perceived as an “appendix” which tended to meaninglessness by some of the citizens.The nurses' perception of nursing care and their limited IT skills was a barrier to acceptance, adoption and development of technology opportunities in nursing. The citizens' disability, the screen appearance, and the technology setup meant that the citizens perceived poor usability of the equipment. The study showed a change in workflow, as the cooperation between the citizen and the professional developed. New roles occurred for the professionals.The citizens had many ideas concerning the development of the technology and the study recommends that users are involved in the development and implementation of welfare technology and telemedicine. The relatively small sample size of the study shows findings that must be clarified by further research.
The Computerized OMAHA System in Microsoft Office Excel
Authors: Lai Xiaobin  , Wong Frances K. Y.  , Zhang Peiqiang  , Leung Carenx W. Y.  , Lee Lai H.  , Wong Jessica S. Y.  , Lo Yim F.  , Ching Shirley S. Y.
Published: February 2025

The OMAHA System was adopted as the documentation system in an interventional study. To systematically record client care and facilitate data analysis, two Office Excel files were developed. The first Excel file (File A) was designed to record problems, care procedure, and outcomes for individual clients according to the OMAHA System. It was used by the intervention nurses in the study. The second Excel file (File B) was the summary of all clients that had been automatically extracted from File A. Data in File B can be analyzed directly in Excel or imported in PASW for further analysis. Both files have four parts to record basic information and the three parts of the OMAHA System. The computerized OMAHA System simplified the documentation procedure and facilitated the management and analysis of data.
The Relationship of Learning Motivation, Achievement and Satisfaction for Nurses Learning Simple Excel VBA Information Systems Programming
Authors: Lee Ying Li  , Chien Tsai Feng  , Kuo Ming Chuan  , Chang Polun
Published: February 2025

This study aims to understand the relationship between participating nurses' motivation, achievement and satisfaction before and after they learned to program in Excel Visual Basic for Applications (Excel VBA). We held a workshop to train nurses in developing simple Excel VBA information systems to support their clinical or administrative practices. Before and after the workshop, the participants were evaluated on their knowledge of Excel VBA, and a questionnaire was given to survey their learning motivation and satisfaction. Statistics softwares Winsteps and SPSS were used for data analysis. Results show that the participants are more knowledgeable about VBA as well as more motivated in learning VBA after the workshop. Participants were highly satisfied with the overall arrangement of the workshop and instructors, but didn't have enough confidence in promoting the application of Excel VBA themselves. In addition, we were unable to predict the participants' achievement by their demographic characteristics or pre-test motivation level.
Rapid EHR Development and Implementation Using Web and Cloud-Based Architecture in a Large Home Health and Hospice Organization
Authors: Weaver Charlotte A.  , Teenier Pamela
Published: February 2025

Health care organizations have long been limited to a small number of major vendors in their selection of an electronic health record (EHR) system in the national and international marketplace. These major EHR vendors have in common base systems that are decades old, are built in antiquated programming languages, use outdated server architecture, and are based on inflexible data models [1,2]. The option to upgrade their technology to keep pace with the power of new web-based architecture, programming tools and cloud servers is not easily undertaken due to large client bases, development costs and risk [3]. This paper presents the decade-long efforts of a large national provider of home health and hospice care to select an EHR product, failing that to build their own and failing that initiative to go back into the market in 2012. The decade time delay had allowed new technologies and more nimble vendors to enter the market. Partnering with a new start-up company doing web and cloud based architecture for the home health and hospice market, made it possible to build, test and implement an operational and point of care system in 264 home health locations across 40 states and three time zones in the United States. This option of “starting over” with the new web and cloud technologies may be posing a next generation of new EHR vendors that retells the Blackberry replacement by iPhone story in healthcare.
Access to Internet in Rural and Remote Canada
Authors: Currie Leanne M.  , Ronquillo Charlene  , Dick Tania
Published: February 2025

Canada is the second largest landmass country in the world, but has one of the lowest population densities. As of 2011, approximately 19% of the Canadian population lives in rural, or remote communities. The purpose of this study was to examine differences in rural and urban access to the Internet and device use in Canada, and to explore differences in access to broadband between Aboriginal and non-Aboriginal communities in Canada. In general rural-dwellers had lower levels of Internet access and despite efforts to increase access to high speed Internet, Aboriginal communities in some regions have limited access. Future research should explore computer and health literacy in the context of rural and remote communities in Canada.
Dynamic and Accretive Composition of Patient Engagement Instruments for Personalized Plan Generation
Authors: Hsueh Pei-Yun S.  , Zhu Xinxin  , Deng Vincent  , Ramarishnan Sreeram  , Ball Marion
Published: February 2025

Patient engagement is important to help patients become more informed and active in managing their health. Effective patient engagement demands short, yet valid instruments for measuring self-efficacy in various care dimensions. However, the static instruments are often too lengthy to be effective for assessment purposes. Furthermore, these tests could neither account for the dynamicity of measurements over time, nor differentiate care dimensions that are more critical to certain sub-populations. To remedy these disadvantages, we devise a dynamic instrument composition approach that can model the measurement of patient self-efficacy over time and iteratively select critical care dimensions and appropriate assessment questions based on dynamic user categorization. The dynamically composed instruments are expected to guide patients through self-management reinforcement cycles within or across care dimensions, while tightly integrated into clinical workflow and standard care processes.
An Optimal Iterative Algorithm for Extracting MUCs in a Black-box Constraint Network
Authors: Laborie Philippe
Published: February 2025

We present a non-intrusive iterative algorithm for extracting Minimal Unsatisfiable Cores in black-box constraint networks. The problem can be generalized as the one of finding a minimal subset satisfying an upward-closed property P. If performance is measured as the number of infeasibility property checks, we show that the proposed algorithm, ADEL, is optimal both for small and for large MUCs and that it consistently outperforms existing approaches in between those two extremal cases.
Faustian Dynamics in Sarkar's Social Cycle
Authors: Obraztsova Svetlana  , Rabinovich Zinovi  , Madunts Alexandra
Published: February 2025

Recently Bai and Lagunoff [1] have studied the question of Faustian Dynamics (FD) of policy and political power using a formal game theoretic framework. Specifically, they studied the conflict between implementing a (personally) optimal policy and maintaining political power. However, these works assumed that the policy makers come from the same population that empowers them. In contrast, in this paper we study a society that has a political class, hence policy makers are detached from the general population. Specifically, we study a society where members of the political class compete via pre-election propaganda campaigns – a competition form characteristic to modern democracies. We assume that the society is characterised by an inherent cyclical Faustian dynamics, such as the Sarkar Cycle, and concentrate on the strategic behaviour of the political class members. We show that their propaganda over time tends to become extreme (single issue oriented). In addition, the equilibrium behaviour of the political class members precludes them from adopting a persistent agenda. Rather, to optimise their political gain over time, they must lack any permanent agenda or views.
STIT is dangerously undecidable
Authors: Schwarzentruber François  , Semmling Caroline
Published: February 2025

STIT is a potential logical framework to capture responsibility, counterfactual emotions and norms, which are main ingredients for specifying behaviors of virtual agents. We identify here a new fragment and its satisfiability problem is NP-complete and in Σ3when the number of agents is unbounded. We also identify a slightly more expressive fragment which is undecidable.
Semantical Information Graph Model toward Fast Information Valuation in Large Teamwork
Authors: Zhang Yulin  , Xu Yang  , Hu Haixiao  , Liu Xianggen
Published: February 2025

Sharing information is critical to large teamwork for cooperative decision making in dynamic and partially observable environments. To be effective, other than building a full information coverage, agents should valuate how a potential receiver could be benefited with a piece of given information. In this paper, we propose a fast valuation model with complex network based graph modeling and analysis, which help to indicate the information importance to a given information base. Similar to vague information valuation by humans, the key is that important information always significantly changes their complex information graph with its incorporation. Therefore, we calculate the semantic based value of this new information in a graph model and build a local graph evaluation algorithm to estimate information graph evolution, instead of performing expensive complete graph search. Although the decision may be not precise, similar to human communication, it is good enough to disseminate valuable information around the team.
The Piano Music Companion
Authors: Arzt Andreas  , Böck Sebastian  , Flossmann Sebastian  , Frostel Harald  , Gasser Martin  , Liem Cynthia C.S.  , Widmer Gerhard
Published: February 2025

We present a system that we call ‘The Piano Music Companion’ and that is able to follow and understand (at least to some extent) a live piano performance. Within a few seconds this system can identify the piece that is being played, and the position within the piece. It then tracks the progress of the performer over time via a robust score following algorithm. The companion is useful in multiple ways, e.g., it can be used for piece identification, music visualisation, during piano rehearsal and for automatic page turning.
VMAP: A Visual Schema Mapping Tool
Authors: Chertes Florin  , Feinerer Ingo
Published: February 2025

Schema mapping languages are a key technique for data engineers to perform data exchange and integration in the context of the semantic web. Visual schema mapping languages provide an extra benefit as they help to visually describe the flow of data between various sources and destinations in the Internet. We present a tool called VMAP for implementing visual schema mappings. Its focus is on standardization and modularity.
ATL* With Truly Perfect Recall: Expressivity and Validities
Authors: Bulling Nils  , Jamroga Wojciech  , Popovici Matei
Published: February 2025

In alternating-time temporal logic ATL*, agents with perfect recall assign choices to sequences of states, i.e., to possible finite histories of the game. However, when a nested strategic modality is interpreted, the new strategy does not take into account the previous sequence of events. It is as if agents collect their observations in the nested game again from scratch, thus effectively forgetting what they observed before. Intuitively, it does not fit the assumption of agents having perfect recall of the past.
Improving pattern discovery relevancy by deriving constraints from expert models
Authors: Flouvat Frédéric  , Sanhes Jérémy  , Pasquier Claude  , Selmaoui-Folcher Nazha  , Boulicaut Jean-François
Published: February 2025

To support knowledge discovery from data, many pattern mining techniques have been proposed. One of the bottlenecks for their dissemination is the number of computed patterns that appear to be either trivial or uninteresting with respect to available knowledge. Integration of domain knowledge in constraint-based data mining is limited. Relevant patterns still miss because methods partly fail in assessing their subjective interestingness. However, in practice, we often have in the literature mathematical models defined by experts based on their domain knowledge. We propose here to exploit such models to derive constraints that can be used during the data mining phase to improve both pattern relevancy and computational efficiency. Even though the approach is generic, it is illustrated on pattern set discovery from real data for studying soil erosion.
Detecting the Reputation Polarity of Microblog Posts
Authors: Gârbacea Cristina  , Tsagkias Manos  , de Rijke Maarten
Published: February 2025

We address the task of detecting the reputation polarity of social media updates, that is, deciding whether the content of an update has positive or negative implications for the reputation of a given entity. Typical approaches to this task include sentiment lexicons and linguistic features. However, they fall short in the social media domain because of its unedited and noisy nature, and, more importantly, because reputation polarity is not only encoded in sentiment-bearing words but it is also embedded in other word usage. To this end, automatic methods for extracting discriminative features for reputation polarity detection can play a role. We propose a data-driven, supervised approach for extracting textual features, which we use to train a reputation polarity classifier. Experiments on the RepLab 2013 collection show that our model outperforms the state-of-the-art method based on sentiment analysis by 20% accuracy.
Past, Present, and Future: An Optimal Online Algorithm for Single-Player GDL-II Games
Authors: Geißer Florian  , Keller Thomas  , Mattmüller Robert
Published: February 2025

In General Game Playing, a player receives the rules of an unknown game and attempts to maximize his expected reward. Since 2011, the GDL-II rule language extension allows the formulation of nondeterministic and partially observable games. In this paper, we present an algorithm for such games, with a focus on the single-player case. Conceptually, at each stage, the proposed NORNS algorithm distinguishes between the past, present and future steps of the game. More specifically, a belief state tree is used to simulate a potential past that leads to a present that is consistent with received observations. Unlike other related methods, our method is asymptotically optimal. Moreover, augmenting the belief state tree with iteratively improved probabilities speeds up the process over time significantly.
Extending Acyclicity Notions for Existential Rules
Authors: Baget Jean-François  , Garreau Fabien  , Mugnier Marie-Laure  , Rocher Swan
Published: February 2025

Existential rules have been proposed for representing ontological knowledge, specifically in the context of Ontology-Based Query Answering. Entailment with existential rules is undecidable. We focus in this paper on conditions that ensure the termination of a breadth-first forward chaining algorithm known as the chase. First, we propose a new tool that allows to extend existing acyclicity conditions ensuring chase termination, while keeping good complexity properties. Second, we consider the extension to existential rules with nonmonotonic negation under stable model semantics and further extend acyclicity results obtained in the positive case.
LTL
Authors: Li Jianwen  , Zhang Lijun  , Pu Geguang  , Vardi Moshe Y.  , He Jifeng
Published: February 2025

We consider here Linear Temporal Logic (LTL) formulas interpreted over finite traces. We denote this logic by LTLf. The existing approach for LTLfsatisfiability checking is based on a reduction to standard LTL satisfiability checking. We describe here a novel direct approach to LTLfsatisfiability checking, where we take advantage of the difference in the semantics between LTL and LTLf. While LTL satisfiability checking requires finding a fair cycle in an appropriate transition system, here we need to search only for a finite trace. This enables us to introduce specialized heuristics, where we also exploit recent progress in Boolean SAT solving. We have implemented our approach in a prototype tool and experiments show that our approach outperforms existing approaches.
Verifying the Precision of Diagnostic Algorithms
Authors: Su Xingyu  , Grastien Alban
Published: February 2025

Diagnosis of discrete event systems requires to decide whether the system model allows for certain types of executions to take place. Because this problem is hard, incomplete yet faster algorithms may be needed. This however can lead to a loss of precision. This paper presents a method to decide whether precision is maintained by such incomplete algorithms. To this end we define the Simulation, which is a modification of the model that simulates how the algorithm works. We then use the twin plant method to decide whether diagnosability is maintained despite the imprecision of the diagnostic algorithm. We illustrate the benefits of this approach on two diagnostic algorithms, namely Independent-Windows Algorithms and Chronicle-based Diagnosis.
Mixing Materialization and Query Rewriting for Existential Rules
Authors: Thomazo Michaël  , Rudolph Sebastian
Published: February 2025

Ontology-Based Data Access (OBDA) is a recent paradigm aiming at enhancing data access by taking ontological knowledge into account. When using existential rules as ontological language, query answering is an undecidable problem, whence numerous decidable classes of ontologies have been defined, ranging from classes with very good computational complexities (AC0 in data complexity) to classes with much larger expressivity. However, actually implementable algorithms have been proposed only for very restricted classes (typically those coinciding with lightweight description logics). The aim of this paper is to show how to deal with more expressive ontologies by proposing an algorithm that performs both materialization and rewriting and is applicable for a significant generalization of lightweight description logics. To this end, we first modify an existing algorithm previously proposed for a very generic class of rules, namely greedy bounded treewidth sets of rules. We then exhibit a special case, called pattern oblivious rule sets, which significantly generalizes the ℰℒℋdrdescription logic, which underlies the OWL 2 EL ontology standard, while keeping the beneficial worst-case computational complexity. We last define a subclass of pattern oblivious rules that is recognizable in polynomial time.
Computing Skypattern Cubes
Authors: Ugarte Willy  , Boizumault Patrice  , Loudni Samir  , Crémilleux Bruno
Published: February 2025

We introduce skypattern cubes and propose an efficient bottom-up approach to compute them. Our approach relies on derivation rules collecting skypatterns of a parent node from its child nodes without any dominance test. Non-derivable skypatterns are computed on the fly thanks to Dynamic CSP. The bottom-up principle enables to provide a concise representation of the cube based on skypattern equivalence classes without any supplementary effort. Experiments show the effectiveness of our proposal.
Social Computing in JaCaMo
Authors: Baldoni Matteo  , Baroglio Cristina  , Capuzzimati Federico
Published: February 2025

Social Computing (SC) requires agents to reason seamlessly both on their social relationships and on their goals, beliefs. We claim the need to explicitly represent the social state and social relationships as resources, available to agents. We built a framework, based on JaCaMo, where this vision is realized and SC is implemented through social commitments and commitment protocols.
A First Comparison of Abstract Argumentation Reasoning-Tools
Authors: Bistarelli Stefano  , Rossi Fabio  , Santini Francesco
Published: February 2025

We compare three different implementations of reasoning tools dedicated to Abstract Argumentation Frameworks. These systems are ASPARTIX, ConArg2, and Dung-O-Matic. They have been tested over three different random graph-models, corresponding to the Erdös-Rényi model, Kleinberg small-world model, and scale-free Barabasi model.
Practical Defeasible Reasoning for Description Logics
Authors: Moodley Kody  , Meyer Thomas  , Sattler Uli
Published: February 2025

The preferential approach to nonmonotonic reasoning was consolidated in depth by Krause, Lehmann and Magidor (KLM) for propositional logic in the early 90's. In recent years, there have been efforts to extend their framework to Description Logics (DLs) and a solid (though preliminary) theoretical foundation has already been established towards this aim. Despite this foundation, the generalisation of the propositional framework to DLs is not yet complete and there are multiple proposals for entailment in this context with no formal system for deciding between these. In addition, there are virtually no existing preferential reasoning implementations to speak of for DL-based ontologies. The goals of this PhD are: to place the preferential approach in context w.r.t. the alternative nonmonotonic reasoning proposals, to provide a complete generalisation of the preferential framework of KLM to the DL ALC, provide a formal understanding of the relationships between the multiple proposals for entailment in this context, and finally, to develop an accompanying defeasible reasoning system for DL-based ontologies with performance that is suitable for use in existing ontology development settings.
Electronic Tourist Guides: User-friendly Editing of Automatically Planned Routes
Authors: Schaller Richard
Published: February 2025

Sightseeing tourists on a city trip can be supported by an electronic tourist guide. More advanced systems generate personalized routes taking into account user preferences and traveling distances between sights. Recommenders can be used in order to estimate user's interest in the available sights. Typically recommendations are then fed into a planning algorithm that tries to determine a subset of sights and a suitable order. The aim being to include the most interesting sites for the user and possibly as many interesting sights as possible within a given set of constraints. Additional constraints can be considered such as a sight being a must-see for the user or opening hours of sights. At some point the generated route is shown to the user. If the user is not satisfied with the route he may want to change it. In most systems modifying the constraints or user preferences and then regenerating a completely new route is the only option to accomplish this task. More fine-grained control over route modifications is in typically unavailable.
HiPOP: Hierarchical Partial-Order Planning
Authors: Bechon Patrick  , Barbier Magali  , Infantes Guillaume  , Lesire Charles  , Vidal Vincent
Published: February 2025

This paper describes a new planner, HiPOP (Hierarchical Partial-Order Planner), which is domain-configurable and uses POP techniques to create hierarchical time-flexible plans. HiPOP takes as inputs a description of a domain, a problem, and some optional user-defined search-control knowledge. This additional knowledge takes the form of a set of abstract actions with optional methods to achieve them. HiPOP uses this knowledge to enrich the output by providing a hierarchical time-flexible partial-order plan that follows the given methods. We show in this paper how to use this additional knowledge in a POP algorithm and provide results on a domain with a strong hierarchy of actions. We compare our approach with other temporal planners on this domain.
A Logic of Part and Whole for Buffered Geometries
Authors: Du Heshan  , Alechina Natasha
Published: February 2025

We propose a new qualitative spatial logic for reasoning about part-whole relations between geometries (sets of points) represented in different geospatial datasets, in particular crowd-sourced datasets. Since geometries in crowd-sourced data can be less inaccurate or precise, we buffer geometries by a margin of error or level of tolerance σ, and define part-whole relation for buffered geometries. The relations between geometries considered in the logic are: buffered part of (BPT), Near and Far. We provide a sound and complete axiomatisation of the logic with respect to metric models and show that its satisfiability problem is NP-complete.
Electronic Dental Record (EDR) Use in Saudi Arabia: An Exploratory Study
Authors: Almaiman Ahmad  , Bahkali Salwa  , Bahkali Ahlam  , Almaiman Sarah  , Elmetwally Ashraf  , Househ Mowafa
Published: February 2025

The purpose of this exploratory study is to provide an overview of the electronic dental records (EDR) systems used at National Guard Health Affair (NGHA) hospitals in the Kingdom of Saudi Arabia (KSA). Different sources of data were collected between February 18 and March 16, 2014. Sources of data included interviews with key informants. Key informants interviews included one 30 minute interview with an information technology specialist working at NGHA; seven 30–40 minute interview with dentists working in both the NGHA hospital and affiliated NGHA Primary Healthcare Clinics (PHCs). Two dental ward clerks were interviewed for 30 minutes and two dental directors were interviewed for 1 hour each. Four main themes emerged as a result of the analysis of the data. The main themes that emerged centered on staff satisfaction and workload, incomplete information, missing files, and adoption of EDRs. There were several challenges identified with the use of EDRs in Saudi Arabia. The challenges related to resistance to use the EDRs by clinical staff; lack of computer skills by clinical staff; usability of the systems; lack of interest in using EDRs; and lack of a clear management change strategy. Moving forward, these issues should be addressed so that more EDRs are implemented in all healthcare institutions in Saudi Arabia.
Merging Personalized and Participatory Medicine: Interpretation of Individual Genomes
Authors: Koutsoukis Alexander J.  , Lopez-Campos Guillermo H.  , Martin-Sanchez Fernando
Published: February 2025

Interpretation-only providers are becoming increasingly prominent in the field of Direct-To-Consumer genomics. We examined the information obtained from two different providers (Interpretome and Promethease) when analysing the same personal genome. We found large discrepancies between the results from these services for the list of SNPs included in the analysis, but a high level of concordance in their interpretation when the SNPs were coincident.
Predicting Ageing: On the Mathematical Modelization of Ageing Muscle Tissue
Authors: Musesti Alessandro  , Giusteri Giulio G.  , Marzocchi Alfredo
Published: February 2025

The ageing of biological tissues can be accelerated by many factors, mainly of physiological and nutritional nature. In the case of skeletal muscle tissue, one of the main consequences of ageing is a progressive loss of muscle mass and a worsening of the quality of muscle tissue, termed “sarcopenia”. The correlation between the deterioration of muscle tissue and what we usually refer to as the “lifestyle”, although being the subject of several studies, up to now has been considered only from a clinical and a statistical viewpoint. However, the construction of a sound mathematical model of the muscle tissue, accounting for the changes due to ageing, can provide a more refined quantitative tool. Such a tool could determine in an improved way the variations of some measurable physiological parameters, such as the mass and the electrical impedance of the tissue, caused by the variation of other controllable factors, such as diet, physical activity, pharmacological treatments, air pollution exposure. A specific mathematical model, once implemented on a computer, makes it possible to perform “virtual” experiments, facilitating the search for a suitable treatment of sarcopenia. Moreover, test situations can be studied which would not be reproducible in vivo, such as drug overdoses, extreme nutritional deficiencies, environmental overexposure to harmful substances, and so on.