bluuebunny/crossref_metadata_2025 huggingface dataset:
Analytic Network Process Algorithm
Authors: Rokou Elena  , Kirytopoulos Konstantinos  , Voulgaridou Dimitra
Published: February 2025

The Analytical Network Process (ANP) is a multicriteria decision analysis method that has been widely used the last few years to support decision making. Primary aim of this paper is to expose in detail the mathematics of the method in order to explain the mechanics of its steps and provide an exact algorithm that will give the opportunity to easily understand and implement either the method itself or modified versions of it. The paper holds an holistic approach to the method, covering not only simple ANP models but also Hierarchies and BOCR models. The practical implication of this paper is that the algorithm provided may be used as a basis for the development of custom software programs and tools that will foster the further expanding of the method.
A multi-attribute analysis module for SABILOC – a DSS for Location Problems
Authors: Fernandes Sérgio  , Captivo M. Eugénia  , Clímaco João
Published: February 2025

In this paper, we present the new developments of the interactive Decision Support System (DSS) named SABILOC ([8], [1]). SABILOC is aimed at supporting decision-making concerning bicriteria location models in which the facilities to be located could have environmental impacts. The decision support is provided through two interactive phases. First, a combinatorial optimization procedure to obtain non-dominated solutions for bicriteria location problems is used. A Geographic Information System was embedded into the DSS ([7]) in order to obtain relevant data for the models concerned, especially those considering enviromental issues. In the second phase, a set of compromise alternatives can be analyzed in detail using a multi-attribute a posteriori analysis tool. This one stands for a simple interactive implementation of the conjunctive method making use of a radar chart as basis for the procedure.
Towards a Seamless Integration of Human and Machine Reasoning in Data-Intensive Collaborative Decision Making Settings: The Dicode Approach
Authors: Karacapilidis Nikos  , Tzagarakis Manolis
Published: February 2025

This paper presents an innovative approach to collaborative decision making that takes into account requirements imposed by the “data deluge” era. The proposed approach builds on the synergy of human and machine intelligence. It integrates a set of interoperable services that reduce the data-intensiveness and complexity overload at critical decision points to a manageable level. Its applicability in three real-world use cases is sketched.
Aggregation of individual preference models in collaborative decision making through disaggregation – aggregation approach with the RACES system
Authors: Spyridakos Athanasios
Published: February 2025

The synergistic operation of the RACES and MINORA systems is oriented to exploit disaggregation – aggregation approaches for collaborative decision making. The process is progressed through two paths. The first one concerns the a priori estimation of a total ranking by the utilization of collective voting functions (Borda, De Condorcet, Eigenvector, etc.). This ranking is further used by the UTA* method for the assessment of a collective additive value preference model. The second path is focused on the a posteriori assessment of a collective preference additive value model by the aggregation of the individuals ones which are assessed by the UTA* method. This methodological approach provides a flexible framework to investigate and discover the structures of Decision Makers' (DMs) preferences in collaborative decision making for small groups. This work presents the functions of the RACES and MINORA systems and examines the way with which individual preference models can be conformed to a composite one and how the collaborative decision making process can be supported through interactive feedbacks, so as to lead to a common accepted preference model, satisfying the individuality.
A Multi-Agent View of Distributed Collaborative Decision Support Systems
Authors: Adla Abdelkader  , Nachet Bakhta  , Ould-Mahraz Abdelkader
Published: February 2025

In this paper, we propose a Multi-agent view of distributed collaborative decision support systems in which a facilitator and group decision makers are supported by intelligent agents. It considers group participants as multiple agents concerned with the quality of the collective decision. We define a facilitator agent as that agent responsible for the overall decision making process. This includes managing the complex negotiation processes that are required among those participants collaborating on decision making. The agents in the system autonomously plan and pursue their actions and sub-goals to cooperate, coordinate and negotiate with others, and to respond flexibly and intelligently to dynamic and unpredictable situations. Specifically, agents were used to collect information and generate alternatives that would allow the user to focus on solutions that were found to be significant. The decision making process, applied to the fault diagnosis in an oil plant, relies on a cycle that includes recognition of the causes of a defect (diagnosis), plan actions to solve the incidences and, execution of the selected actions.
Using the general practice EMR for improving blood pressure medication adherence
Authors: Warren Jim  , Kennelly John  , Warren Debra  , Elley C. Raina  , Wai Kuinileti Chang  , Manukia Marilyn  , Davy Jennifer  , Mabotuwana Thusitha  , Robinson Elizabeth
Published: February 2025

Purpose. Analysis of practice electronic medical records (EMRs) demonstrated widespread antihypertensive medication adherence problems in a Pacific-led general practice serving a predominantly Pacific (majority Samoan) caseload in suburban New Zealand. Adherence was quantified in terms of medication possession ratio (MPR, percent of days covered by medication supply) from the practice's prescribing data. We studied the effectiveness of general practice staff follow-up guided by EMR data to improve medication adherence.
The Void in Hydro Ontology
Authors: Hahmann Torsten  , Brodaric Boyan
Published: February 2025

Voids are extremely important to water science, because their size and connectivity determines the storage and flow of water both above and below the ground surface. While previous formal theories about voids strictly consider holes hosted inside objects, we generalize voids to also include spaces between objects, and distinguish voids in macroscopic objects from those occurring microscopically in an object's matter. These notions are axiomatized in first-order logic as an extension of the DOLCE ontology, and are applied to key aspects of hydrology and hydrogeology, laying the groundwork for a foundational hydro ontology.
Towards Making Explicit the Ontological Commitment of a Database Schema on the Geological Domain
Authors: Rosa da Silva Alda Maria Ferreira  , Cavalcanti Maria Cláudia
Published: February 2025

Recently, the demand for data integration on the Geological domain has increased. Most approaches for database schema integration are strongly based on structure and syntax, and present limitations. Semantic resources, such as ontologies, have been used to reach better results for data integration. However, these approaches assume there are already local ontologies that represent the databases involved in the interoperation. Furthermore, the creation of an ontology based on the database logical schema is not an easy task. On the other hand, it had been proposed that the association of a top-level ontology to a database conceptual schema may lead to better interoperability results. The idea is to make explicit the ontological commitment of each representation, and thus facilitate their integration. This work presents a case study on the Geological domain, which aimed at making explicit the ontological commitment of a database conceptual schema, in order to further improve data interoperability. The main contribution of this work is that it covers the whole process. It starts from the database logical schema, applies a set of reverse engineering techniques to create a preliminary database conceptual schema, and then uses a top-level ontology as a way of making explicit its ontological commitment. A detailed description is provided on how each step was taken, serving as a roadmap for others that may need to go through a similar process on the geological domain or on other domains.
An Interactive Way of Learning About Cancer and Healthy Living in a Multicultural Setting (part one)?
Authors: Betancourt Juan  , Fuentes Lucía  , CÁceres Ana  , Rivas Silvia
Published: February 2025

Health education is essential not only for preventing illnesses but also for knowing how to act when disease comes. In countries where the education system is inefficient for most of the population and where health issues are often ignored or mistreated because of ignorance or well-intended but ineffective belief in nature's energy and magic, it is important that people have access to truthful information about health issues. Such access allows them to act adequate knowledge and also to learn ways to avoid illness by changing their daily habits into a “healthy way of living.” Approaching the young population is a way to achieve this objective. The program described here considers the education of both majority (indigenous) and minority (non indigenous) populations. It approaches the communication of information in such a way that it involves the participants in the “making” of the education. The participants actively interact with didactic material that allows them to experience “hands on” the issues about cancer and healthy living. It is intended to have a profound impact on the participant, so that he/she will remember the “education” not only as information but also as an experience. The program includes specific material for the indigenous population, which is based on their idiosyncrasy (corn plants) so that they can more easily understand the concepts. In Guatemala, UNOP (Unidad Nacional de Oncologia Pediatrica) is the only institution that provides a quality integral service for the majority of the entire children-with-cancer population. UNOP and the Psychology Department are interested in the development and implementation of education programs such as this where the participant not only learns but also experiences information about this disease and its prevention.
Development of the Nutrition4Kids Website
Authors: Williams Michelle S.
Published: February 2025

According to the 2009 National Vital Statistics Report, cancer is the second-leading cause of death in the United Sates. Researchers have determined that consuming a diet low in fruits, vegetables, and whole grains is a common risk factor associated with the risk of developing several types of cancer including stomach, colorectal, breast, and pancreatic. Currently, there are few websites devoted to increasing students' knowledge about the role of a healthy diet in cancer prevention. The Nutrition4Kids website is a unique health education tool that targets youth aged 10 to 14 years. The website content and design were based on the Health Belief Model, the Information-Motivation and Behavioral Skills Model, and the principles of health literacy. The information included on the website was based on recommendations from the American Institute for Cancer Research and the World Cancer Research Fund. The website contains nutrition information, recipes that emphasize the consumption of fruits, vegetables, and whole grains, and interactive games. The primary objectives of the Nutrition4Kids website are to 1) increase students' knowledge of how poor dietary habits can affect their health, 2) increase students' knowledge of healthy dietary habits that can reduce their risk for cancer, 3) increase students' ability to prepare healthy, well-balanced meals and snacks, 4) increase students' ability to discuss healthy eating with their family and friends, and 5) increase students' knowledge of nutrients that have healthful benefits.
An automatic approach for detecting early indicators of design anti-patterns
Authors: Puławski Łukasz
Published: February 2025

The paper presents a framework for automatic inferring knowledge about reasons for the appearance of anti-patterns in the program source code during its development. Experiments carried out on histories of development of few open-source java projects shown that we can efficiently detect temporal patterns, which are indicators of likely appearance of future anti-pattern. The approach presented in this paper uses expert knowledge (formal description of anti-patterns) to automatically produce extra knowledge (with machine learning algorithm) about the evolution of bad structures in the program source code. The research can be used to build scalable and adaptive tools, which warns development teams about the fact that system architecture is drifting in the wrong direction, before this is reported by typical static source code analysis tools.
Consistent GUI Arrangements by Analyzing Existing Windows
Authors: Shirogane Junko  , Shirai Seitaro  , Iwata Hajime  , Fukazawa Yoshiaki
Published: February 2025

To realize usability of software, consistency of GUI (Graphical User Interface) layouts is required. Consistency is realized by user interface guidelines, in many cases. However, there are many items in the guidelines, and it is difficult to apply all items to GUIs in terms of costs and schedule. In our method, we have proposed a method to realize consistency of GUIs. Concretely, source programs of developed GUIs are analyzed, and layout rules are extracted. Then, source programs of undeveloped GUIs are generated based on the extracted layout rules.
Mapping Rule Between Requirements Analysis Model and Web Framework Specific Design Model
Authors: Okuda Hirotaka  , Ogata Shinpei  , Matsuura Saeko
Published: February 2025

Model Driven Development is a promising approach to develop high quality software systems. We have proposed a method of model-driven requirements analysis using Unified Modeling Language (UML). The main feature of our method is to automatically generate a Web user interface prototype from UML requirements analysis model so that we can confirm validity of in-put/output data for each page and page transition on the system by directly operating the prototype. We have shown that the requirements analysis model has traceability to the final product by implementation experiment from the requirements analysis model. This paper proposes a mapping rule in which design information independent of each web application framework implementation is defined based on the requirements analysis model.
Detecting API Usage Patterns from Software Repositories Using Method Categorization
Authors: Akbar Rizky Januar  , Omori Takayuki  , Maruyama Katsuhisa
Published: February 2025

Developers often have difficulties using APIs. To aid developers in efficiently using APIs, API usage patterns can be extracted from source code stored in software repositories. Previous approaches have mined repositories to extract API usage patterns by simply applying a data mining technique to the collection of method invocations of API objects. However, respective roles of invoked methods within API objects are not considered in these approaches. This paper proposes an improved approach that extracts API usage patterns at a higher-level abstraction rather than mining the actual method invocations. Our approach embraces a multilevel sequential mining technique and uses categorization of method invocations to define their concept hierarchy. In the categorization, the method invocations are categorized based on their roles. The extracted API usage patterns represent recurring usages of API objects. Therefore, they are useful to recommend typical usages of APIs. The experimental results show that our approach is practical to discover patterns that reveal characteristics of usages.
Using Fuzzy Cognitive Maps for the Domain Knowledge Representation of an Adaptive e-Learning System
Authors: Chrysafi Adi Konstantina  , Virvou Maria
Published: February 2025

In this paper we describe a method for the knowledge representation of an e-learning adaptive system. A crucial factor for adaptive systems is to provide adaptive navigation support through the links that constitute the learning material. Therefore, the system should advice each individual learner which domain concepts to read, taking into account her/his progress and performance on other related domain concepts. As a result, the system should be informed about the knowledge dependencies that exist among the domain concepts of the learning material, as well as the strength on impact of each domain concept on others. Fuzzy Cognitive Maps (FCMs) seem to be an ideal way for representing graphically this kind of information. However, due to the fact that a FCM usually is complex and there is a difficulty in extracting information of them, we suggest transforming them to a two-dimensional matrix, in which knowledge dependencies are analysed clearly through its rows and columns.
An evaluation of a quality model for a high quality procurement specification
Authors: Nakakita Hideki  , Tsuda Kazuhiko  , Nakatani Takako
Published: February 2025

We have developed a quality model of an Information System Procurement Specifications (ISPSs). The model is called the ISPS-Q Model. Our aim is to improve the quality of ISPSs for the improvement of procurement operations. The government and/or municipal offices request comments on an ISPS from the public before they open the ISPS to companies. The public comments are referred to in an attempt to further improve the quality of the ISPS. In order to evaluate the efficiency of the ISPS-Q Model, we obtained the public comments and their target ISPS for analyzation. As a result, we could clarify that most of the public comments were written with ambiguous words and/or incomplete statements. Furthermore, we could no regard these ambiguous and/or incomplete comments as a means to improve the quality of the ISPS. In this regard, the ISPS-Q Model is essential to the improvement of the quality of ISPSs. The ISPS-Q Model was developed by adding fair and deleting modifiable to IEEE Std. 830-1998, since fair is a property that the government requires of every ISPS, and that the ISPSs would never be changed after their procurement. We applied the model to a real ISPS and evaluated the quality of the ISPS. We found 19 problematic statements in the ISPS. Multiple companies submitted 109 comments regarding the same ISPS. In this paper, we discuss the differences between our comments and the public comments made by the companies. After that, we define new quality characteristics and reconstruct the ISPS-Q Model. We will close this paper by showing the revised ISPS-Q Model.
Heuristically Accelerated Reinforcement Learning: Theoretical and Experimental Results
Authors: Bianchi Reinaldo A.C.  , Ribeiro Carlos H.C.  , Costa Anna H.R.
Published: February 2025

Since finding control policies using Reinforcement Learning (RL) can be very time consuming, in recent years several authors have investigated how to speed up RL algorithms by making improved action selections based on heuristics. In this work we present new theoretical results – convergence and a superior limit for value estimation errors – for the class that encompasses all heuristics-based algorithms, called Heuristically Accelerated Reinforcement Learning. We also expand this new class by proposing three new algorithms, the Heuristically Accelerated Q(λ), SARSA(λ) and TD(λ), the first algorithms that uses both heuristics and eligibility traces. Empirical evaluations were conducted in traditional control problems and results show that using heuristics significantly enhances the performance of the learning process.
A Protocol Based on a Game-Theoretic Dilemma to Prevent Malicious Coalitions in Reputation Systems
Authors: Bonnet Grégory
Published: February 2025

In decentralized and open systems, a large number of agents interact and make collective decisions in order to share resources. As those systems are open, the presence of malicious agents needs to be considered. A way to deal with such agents in a decentralized fashion is to use reputation systems. But, as reputation systems are based on the aggregation of local trust between the agents, they are vulnerable to malicious coalitions, particularly to self-promotion based on false identities. In this paper, we propose a game-theoretic approach to prevent such manipulations. Its main feature is that honest agents use in turn a false-name manipulation to fool malicious agents and to drive them into a dilemma. We show that the best response to that dilemma in terms of mixed strategy equilibrium leads the malicious agents to give up most of their manipulations.
Computational Creativity: The Final Frontier?
Authors: Colton Simon  , Wiggins Geraint A.
Published: February 2025

Notions relating to computational systems exhibiting creative behaviours have been explored since the very early days of computer science, and the field of Computational Creativity research has formed in the last dozen years to scientifically explore the potential of such systems. We describe this field via a working definition; a brief history of seminal work; an exploration of the main issues, technologies and ideas; and a look towards future directions. As a society, we are jealous of our creativity: creative people and their contributions to cultural progression are highly valued. Moreover, creative behaviour in people draws on a full set of intelligent abilities, so simulating such behaviour represents a serious technical challenge for Artificial Intelligence research. As such, we believe it is fair to characterise Computational Creativity as a frontier for AI research beyond all others—maybe, even, the final frontier.
Decision-making with Sugeno integrals: DMU vs. MCDM
Authors: Couceiro Miguel  , Dubois Didier  , Prade Henri  , Waldhauser Tamás
Published: February 2025

This paper clarifies the connection between multiple criteria decision-making and decision under uncertainty in a qualitative setting relying on a finite value scale. While their mathematical formulations are very similar, the underlying assumptions differ and the latter problem turns out to be a special case of the former. Sugeno integrals are very general aggregation operations that can represent preference relations between uncertain acts or between multifactorial alternatives where attributes share the same totally ordered domain. This paper proposes a generalized form of the Sugeno integral that can cope with attributes which have distinct domains via the use of qualitative utility functions. In the case of decision under uncertainty, this model corresponds to state-dependent preferences on act consequences. Axiomatizations of the corresponding preference functionals are proposed in the cases where uncertainty is represented by possibility measures, by necessity measures, and by general monotonic set-functions, respectively. This is achieved by weakening previously proposed axiom systems for Sugeno integrals.
Case-based Planning for Problems with Real-valued Fluents: Kernel Functions for Effective Plan Retrieval
Authors: Gerevini Alfonso E.  , Saetti Alessandro  , Serina Ivan
Published: February 2025

Case-based planning (CBP) re-uses existing plans as a starting point to solve new planning problems. In this work, we address CBP for planning in PDDL domains with real-valued fluents, that are essential to model real-world problems involving continuous resources. Specifically, we propose some new heuristic techniques for retrieving a plan from a library of existing plans that is promising for a new given planning problem, i.e., that can be efficiently adapted to solve the new problem. The effectiveness of these techniques, which derive much of their power from the use of the numerical information in the planning problem specification and in the library plans, is then evaluated by an experimental analysis.
Comparator selection for RPC with many labels
Authors: Hiard Samuel  , Geurts Pierre  , Wehenkel Louis
Published: February 2025

The Ranking by Pairwise Comparison algorithm (RPC) is a well established label ranking method. However, its complexity is of O(N2)in the number N of labels. We present algorithms for selecting, before model construction, a subset of comparators of size O(N), to reduce computational complexity without loss in accuracy.
Characterization of Positive and Negative Information in Comparative Preference Representation
Authors: Kaci Souhila
Published: February 2025

In the last decade, AI researchers have pointed out the existence of two types of information: positive information and negative information. This distinction has also been asserted in cognitive psychology. Distinguishing between these two types of information may be useful in both knowledge and preference representation. In the first case, one distinguishes between situations which are not impossible because they are not ruled out by the available knowledge, and what is possible for sure. In the second case, one distinguishes between what is not rejected and what is really desired. Besides it has been shown that possibility theory is a convenient tool to model and distinguish between these two types of information. Knowledge/Preference representation languages have also been extended to cope with this particular kind of information. Nevertheless despite solid theoretical advances in this topic, the crucial question of “which reading (negative or positive) one should have” remains a real bottleneck. In this paper, we focus on comparative statements. We present a set of postulates describing different situations one may encounter. Then we provide a representation theorem describing which sets of postulates are satisfied by which kind of information (negative or positive) and conversely. One can then decide which reading to apply depending on which postulates she privileges.
A New Approach to the Snake-In-The-Box Problem
Authors: Kinny David
Published: February 2025

The “Snake-In-The-Box” problem, first described more than 50 years ago, is a hard combinatorial search problem whose solutions have many practical applications. Until recently, techniques based on Evolutionary Computation have been considered the state-of-the-art for solving this deterministic maximization problem, and held most significant records. This paper reviews the problem and prior solution techniques, then presents a new technique, based on Monte-Carlo Tree Search, which finds significantly better solutions than prior techniques, is considerably faster, and requires no tuning.
Reconciling OWL and Non-monotonic Rules for the Semantic Web
Authors: Knorr Matthias  , Hitzler Pascal  , Maier Frederick
Published: February 2025

We propose a description logic extending SROIQ (the description logic underlying OWL 2 DL) and at the same time encompassing some of the most prominent monotonic and nonmonotonic rule languages, in particular Datalog extended with the answer set semantics. Our proposal could be considered a substantial contribution towards fulfilling the quest for a unifying logic for the Semantic Web. As a case in point, two non-monotonic extensions of description logics considered to be of distinct expressiveness until now are covered in our proposal. In contrast to earlier such proposals, our language has the “look and feel” of a description logic and avoids hybrid or first-order syntaxes.
Inconsistency Handling in Datalog+/− Ontologies
Authors: Lukasiewicz Thomas  , Vanina Martinez Maria  , Simari Gerardo I.
Published: February 2025

The advent of the Semantic Web has made the problem of inconsistency management especially relevant. Datalog+/− is a family of ontology languages that is in particular useful for representing and reasoning over lightweight ontologies in the Semantic Web. In this paper, we study different semantics for query answering in inconsistent Datalog+/− ontologies. We develop a general framework for inconsistency management in Datalog+/− ontologies based on incision functions from belief revision, in which we can characterize several query answering semantics as special cases: (i) consistent answers, originally developed for relational databases and recently adopted for some classes of description logics (DLs), (ii) intersection semantics, a sound approximation of consistent answers, and (iii) lazy consistent answers, a novel alternative semantics that offers a good compromise between quality of answers and computation time. We also provide complexity results for query answering under the different semantics, including data tractability results.
Improving Video Activity Recognition using Object Recognition and Text Mining
Authors: Motwani Tanvi S.  , Mooney Raymond J.
Published: February 2025

Recognizing activities in real-world videos is a challenging AI problem. We present a novel combination of standard activity classification, object recognition, and text mining to learn effective activity recognizers without ever explicitly labeling training videos. We cluster verbs used to describe videos to automatically discover classes of activities and produce a labeled training set. This labeled data is then used to train an activity classifier based on spatio-temporal features. Next, text mining is employed to learn the correlations between these verbs and related objects. This knowledge is then used together with the outputs of an off-the-shelf object recognizer and the trained activity classifier to produce an improved activity recognizer. Experiments on a corpus of YouTube videos demonstrate the effectiveness of the overall approach.
Exploiting Expert Knowledge in Factored POMDPs
Authors: Müller Felix  , Späth Christian  , Geier Thomas  , Biundo Susanne
Published: February 2025

Decision support in real-world applications is often challenging because one has to deal with large and only partially observable domains. In case of full observability, large deterministic domains are successfully tackled by making use of expert knowledge and employing methods like Hierarchical Task Network (HTN) planning. In this paper, we present an approach that transfers the advantages of HTN planning to partially observable domains. Experimental results for two implemented algorithmsUCTA* search, show that our approach significantly speeds up the generation of high-quality policies: the policies generated by our approach consistently outperform policies generated by Symbolic Perseus and can be computed in less than 10% of its runtime on average.
ExpExpExplosion: Uniform Interpolation in General EL Terminologies
Authors: Nikitina Nadeschda  , Rudolph Sebastian
Published: February 2025

Although EL is a popular logic used in large existing knowledge bases, to the best of our knowledge no procedure has yet been proposed that computes uniform EL interpolants of general EL terminologies. Up to now, also the bounds on the size of uniform EL interpolants remain unknown. In this paper, we propose an approach based on proof theory and the theory of formal tree languages to computing a finite uniform interpolant for a general EL terminology if it exists. Further, we show that, if such a finite uniform EL interpolant exists, then there exists one that is at most triple exponential in the size of the original TBox, and that, in the worst-case, no shorter interpolants exist, thereby establishing the triple exponential tight bounds on their size.
Optimizations for the Boolean Approach to Computing Minimal Hitting Sets
Authors: Pill Ingo  , Quaritsch Thomas
Published: February 2025

The Boolean approach to computing minimal hitting sets proposed by Lin and Jiang is known to offer very attractive general performance, but also has its issues, specifically with a cardinality-restricted search. In this paper we propose optimizations regarding the refinement rules, also offering a revised decision strategy as well as optimized termination criteria that exploit cardinality bounds. Our experiments including artificial and real-world samples for the bounded and unbounded case show the potential of our work, where we could achieve speed-ups of up to two orders of magnitude.
Solving Raven's IQ-tests: An AI and Cognitive Modeling Approach
Authors: Ragni Marco  , Neubert Stefanie
Published: February 2025

Human reasoners have an impressive ability to solve analogical reasoning problems and they still outperform computational systems. Analogical reasoning is relevant in dealing with intelligence tests. There are two kinds of approaches: to solve IQ-test problems in a way similar to humans (i.e., a cognitive approach) or to solve these problems optimally (i.e., the AI approach). Most systems can be associated with one of these approaches. Detailed systems solving geometrical intelligence tests, explaining cognitive operations based on working memory and producing precise predictions and results such as error rates and response times have not been developed so far. We present a system implemented in the cognitive architecture ACT-R, able to solve analogously developed problems of Raven's Standard and Advanced Progressive Matrices. The model solves 66 of the 72 tested problems of both tests. The model's predicted error rates correlate to human performance with r = .8 for the Advanced Progressive Matrices and r = .7 for all problems together.
Best Reply Dynamics for Scoring Rules
Authors: Reyhani Reyhaneh  , Wilson Mark C.
Published: February 2025

We consider best-reply dynamics for voting games in which all players are strategic and no coalitions are formed. We study the class of scoring rules, show convergence of a suitably restricted version for the plurality and veto rules, and failure of convergence for other rules including k-approval and Borda. In particular, for 3 candidates convergence fails for all rules other than plurality and veto. We give a unified proof for the convergence of these two rules. Our proofs in the case of plurality improve the known bound on convergence, and the other convergence results are new.
Deciding Membership in a Class of Polyhedra
Authors: Ruggieri Salvatore
Published: February 2025

Parameterized linear systems allow for modelling and reasoning over classes of polyhedra. Collections of squares, rectangles, polytopes, and so on can readily be defined by means of linear systems with parameters in constant terms. In this paper, we consider the membership problem of deciding whether a given polyhedron belongs to the class defined by a parameterized linear system. As an example, we are interested in questions such as: “does a given polytope belong to the class of hypercubes?” We show that the membership problem is NP-complete, even when restricting to the 2-dimensional plane. Despite the negative result, the constructive proof allows us to devise a concise decision procedure using constraint logic programming over the reals, namely CLP(R), which searches for a characterization of all instances of a parameterized system that are equivalent to a given polyhedron.
A Stubborn Set Algorithm for Optimal Planning
Authors: Alkhazraji Yusra  , Wehrle Martin  , Mattmüller Robert  , Helmert Malte
Published: February 2025

We adapt a partial order reduction technique based on stubborn sets, originally proposed for detecting dead ends in Petri Nets, to the setting of optimal planning. We demonstrate that stubborn sets can provide significant state space reductions on standard planning benchmarks, outperforming the expansion core method.
Ontology Driven Decision Support Systems for Medical Diagnosis
Authors: Donfack Guefack Valéry  , Bertaud Gounot Valérie  , Duvauferrier Régis  , Bourde Annabel  , Morelli John  , Lasbleiz Jérémy
Published: February 2025

Multiple myeloma (MM) is a malignant disorder characterized by the monoclonal proliferation of B cell derived plasma cells in the bone marrow. The diagnosis depends on the identification of abnormal monoclonal marrow plasma cells, monoclonal protein in the serum or urine, evidence of end-organ damage, and a clinical picture consistent with MM. The distinction between MM stages— monoclonal gammopathy of undetermined significance or indolent myeloma—is critical in guiding therapy. This paper describes how to produce ontology-driven semiological rules base (SRB) and a consultation form to aid in the diagnosis of plasma cells diseases. We have extracted the MM sub-ontology from the NCI Thesaurus. Using Protégé 3.4.2 and owl1, criteria in the literature for the diagnosis and staging of MM have been added to the ontology. All quantitative parameters have been transformed to a qualitative format. A formal description of MM variants and stages has been given. The obtained ontology has been checked by a reasoner and instantiated to obtain a SRB. The form created has been tested and evaluated utilizing 63 clinical medical reports. The likelihood for a disease being the correct diagnosis is determined by computing a ratio. The resulting tool is relevant for MM diagnosis and staging.
Semantic Enrichment of Medical Forms – Semi-Automated Coding of ODM-Elements via Web Services
Authors: Breil Bernhard  , Watermann Andreas  , Haas Peter  , Dziuballe Philipp  , Dugas Martin
Published: February 2025

Semantic interoperability is an unsolved problem which occurs while working with medical forms from different information systems or institutions. Standards like ODM or CDA assure structural homogenization but in order to compare elements from different data models it is necessary to use semantic concepts and codes on an item level of those structures. We developed and implemented a web-based tool which enables a domain expert to perform semi-automated coding of ODM-files. For each item it is possible to inquire web services which result in unique concept codes without leaving the context of the document. Although it was not feasible to perform a totally automated coding we have implemented a dialog based method to perform an efficient coding of all data elements in the context of the whole document. The proportion of codable items was comparable to results from previous studies.
The Reproducibility of CLIF, a Method for Clinical Quality Indicator Formalisation
Authors: Dentler Kathrin  , Cornet Ronald  , Ten Teije Annette  , Tytgat Kristien  , Klinkenbijl Jean  , De Keizer Nicolette
Published: February 2025

In order to be able to automatically calculate clinical quality indicators, we have proposed CLIF, a stepwise method for clinical quality indicator formalisation. Quality indicators are used for external accountability and hospital comparison. As clinical quality indicators are computed in a decentralised manner by the hospitals themselves, reproducibility of the formalisation method is essential to ensure the comparability of calculated values. Thus, we performed a case study to investigate the reproducibility of CLIF. Eight participants formalised the same sample quality indicator with the help of a web-based indicator-authoring tool that facilitates the application of CLIF. We analysed the results per step and concluded that the method itself leads to reproducible results. To further improve reproducibility, ambiguities in the indicator text must be clarified and trained experts are needed to encode clinical concepts and to specify the relations between concepts.
Promoting Generic Medication prescribing by Order Interface Redesign: Small change, Large impact
Authors: Malhotra Sameer  , Ancker Jessica S.  , Gossey J. Travis  , Cole Curtis L.  , Kaushal Rainu  , Cheriff Adam D
Published: February 2025

Prescription drugs are a significant component of the ever increasing health care costs. We describe the effects on generic medication prescribing behavior achieved through redesign of the order entry interface of our institutions ambulatory electronic health record. The redesign involved custom programming that automatically substituted brand medications with their generic equivalents and only allowed continuation with the brand medication if the clinician made an extra mouse click selecting “dispense as written”. We conducted a before-after retrospective study around the time of the redesign and witnessed a net 36.9% percentage increase in the number of generic medications prescribed.
Pharmaceutical Validation of Medication Orders Using an OWL Ontology and Business Rules
Authors: Chniti Amina  , Boussadi Abdelali  , Degoulet Patrice  , Albert Patrick  , Charlet Jean
Published: February 2025

In this paper we present an application of pharmaceutical validation of medication based on an OWL ontology and business rules or more specifically clinical decision rules. This application has been developed based on a prototype that enables business users to author, execute and manage their Business Rules over OWL Ontology. This prototype is based on the Business Rule Management System (BRMS) IBM WebSphere ILOG JRules.
Probabilistic Graphical Models for Effective Connectivity Extraction in the Brain Using fMRI Data
Authors: Ali Safari Mohammad  , Mohammadbeigi Majid
Published: February 2025

In this study using Bayesian network method to learn the structure of effective connectivity among brain regions involved in a functional MRI. The approach is exploratory in the sense that it does not require a priori model as in the earlier approaches, such as the Structural Equation Modeling or Dynamic Causal Modeling, which can only affirm or refute the connectivity of a previously known anatomical model or a hypothesized model. The conditional probabilities that render the interactions among brain regions in Bayesian networks represent the connectivity in the complete statistical sense. This method is applicable even when the number of regions involved in the cognitive network is large or unknown. In this study, we demonstrated the present approach using synthetic data and fMRI data collected in attention to motion in the visual system task.
The issue of building generative terminologies for automatic medical data aggregation
Authors: Belhadj Ihssen  , Nobecourt Jêrome  , Despres Sylvie  , Jacquelinet Christian
Published: February 2025

This work addresses the problem of medical terminologies building. Starting from a set of elementary knowledge, a multi-hierarchical terminology is generated according to formal principles that are based on explicit classificatory points of view. The experimentation has been carried out on kidney diseases. Hierarchical conceptual structures are generated starting from Conceptual Graph based definition of kidney disease, a hierarchy of defining types and a set of organizing rules. The generated hierarchy includes new potential disease concepts with different level of likeliness. This “ready to use” generated multi-hierarchical terminology can be used for coding, includes new potential terms for the future and, due to the formalization of classificatory principles, offers improved opportunities of diseases instances aggregation. These features are looking very promising in the context of epidemiological observation tools (registries, long term cohort studies). They offer mean to meet two critical requirements: the statistical continuity in data analysis and the sustainable management of the underlying terminological system.
The use of linked registries to assess long-term mortality of ICU patients
Authors: Brinkman Sylvia  , De Jonge Evert  , Abu-Hanna Ameen  , De Lange Dylan W.  , De Keizer Nicolette F.
Published: February 2025

Clinical registries are frequently used to monitor and analyze the quality of health care by assessing the in-hospital mortality. However, long-term mortality is often ignored as it is rarely recorded in such clinical registries. In this study linkage of a clinical registry and administrative database is used to assess the longterm mortality of a large ICU sample. Information about long-term mortality may be used to inform patients about their prognosis, to get insight in factors that influence long-term mortality, and to adjust admission policy to the ICU. This study showed that the observed mortality in the total ICU population at 3, 6, and 12 months after ICU admission was 20.3%, 22.9%, and 26.6% respectively. Medical and urgent surgery patients showed a higher long-term mortality risk and planned surgery patients showed a lower long-term mortality risk compared to the other ICU patients. In this study we have focused on the general ICU population, though linkage of clinical and administrative databases can also be used to perform analyses in specific diagnostic ICU populations or for non-ICU patients. In this study 71.4% of the clinical records could be linked with the administrative database. Future studies should focus on improving linkage of different registries.
Proposal of Diagnostic Process Model for Computer Based Diagnosis
Authors: Matsumura Yasushi  , Takeda Toshihiro  , Manabe Shiro  , Saito Hirokazu  , Teramoto Kei  , Kuwata Shigeki  , Mihara Naoki
Published: February 2025

We aim at making a diagnosis support system that can be put to practical use. We proposed a diagnostic process model based on simple knowledge which can be gleaned from textbooks. We defined clinical finding (CF) as a general concept for patient's symptom or findings etc., whose value is expressed by Boolean. We call the combination of several CFs a “CF pattern”, and a set of CF patterns with concomitant diseases “case base”. We consider diagnosis as a process of searching an instance from the case base whose CF pattern is concomitant with that of a patient. The diseases which have the same CF pattern are candidates for diagnosis. Then we select a CF which is present in part of the candidates and check whether it is present or absent in the patient in order to narrow down the candidates. Because the case base does not exist in reality, the probability of CF pattern is calculated by the product of CF occurrence rate assuming that occurrence of CF is independent. Therefore the knowledge required for diagnosis is frequency of disease under sex and age group and CF-disease relation (CF and its occurrence rate in the disease). By processing these two types of knowledge, diagnosis can be made.
Patient safety-oriented usability testing: a pilot study
Authors: Marcilly Romaric  , Bernonville Stephanie  , Riccioli Costanza  , Beuscart-Zephir Marie-Catherine
Published: February 2025

This paper focuses on the prevention of technology induced errors in Health Information Technology (HIT) applications through usability tests in which patient safety-oriented usability goals have been included. A case study presents the evaluation of a web-based medication-related Clinical Decision Support System (CDSS). Systematically defining beforehand usability goals according to the potential use errors is an objective and replicable approach to identify the strengths and weaknesses of an application in terms of patient safety.
Interoperability Design of Personal Health Information Import Service
Authors: Tuomainen Mika  , Mykkänen Juha
Published: February 2025

Availability of personal health information for individual use from professional patient records is an important success factor for personal health information management (PHIM) solutions such as personal health records. In this paper we focus on this crucial part of personal wellbeing information management splutions and report the interoperability design of personal information import service. Key requirements as well as design factors for interfaces between PHRs and EPRs are discussed. Open standards, low implementation threshold and the acknowledgement of local market and conventions are emphasized in the design.