Information Systems最新文献_第4页

IF 3 2区计算机科学

Information Systems Pub Date : 2024-12-09 DOI: 10.1016/j.is.2024.102504

Avivit Levy , Dana Shapira

{"title":"Computation over APT compressed data","authors":"Avivit Levy , Dana Shapira","doi":"10.1016/j.is.2024.102504","DOIUrl":"10.1016/j.is.2024.102504","url":null,"abstract":"<div><div>The Arithmetic Progressions Tree (<span>APT</span>) is a data structure storing an encoding of a monotonic sequence <span><math><mi>L</mi></math></span> in <span><math><mrow><mo>[</mo><mn>1</mn><mo>.</mo><mo>.</mo><mi>n</mi><mo>]</mo></mrow></math></span>. Previous work on APTs focused on its theoretical and experimental compression guarantees. This paper is the first to consider computations over <span>APT</span> compressed data. In particular:</div><div>1. We show how to perform a search for any sub-sequence/a set of the monotone sequence <span><math><mi>L</mi></math></span> in time proportional to the query sub-sequence length/set size multiplied by the size of the <em><span>APT</span> compressed representation of</em> <span><math><mi>L</mi></math></span>.</div><div>2. We show how, given the <span>APT</span> compressed representation of the monotone sequence <span><math><mi>L</mi></math></span>, we can find a minimum run-length of <span><math><mi>L</mi></math></span> in constant time, a maximum run-length of <span><math><mi>L</mi></math></span> in <span><math><mrow><mi>O</mi><mrow><mo>(</mo><mo>log</mo><mi>n</mi><mo>)</mo></mrow></mrow></math></span> time, and all runs of <span><math><mi>L</mi></math></span> in constant time plus the output size.</div><div>3. We show how, given the <span>APT</span> compressed representation of the monotone sequence <span><math><mi>L</mi></math></span>, we can answer whether a consecutive periodic pattern <span><math><mi>P</mi></math></span> is represented by an <span>APT</span>-node in <span><math><mrow><mi>O</mi><mrow><mo>(</mo><mo>log</mo><mi>n</mi><mo>)</mo></mrow></mrow></math></span> time and report occurrences of <span><math><mi>P</mi></math></span> in <span><math><mi>L</mi></math></span> within the processing time of the output size.</div><div>4. In addition, we improve the <span>APT</span> construction algorithm time and space complexity.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"129 ","pages":"Article 102504"},"PeriodicalIF":3.0,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143164403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Open V2X Management Platform: An intelligent charging station management system

IF 3 2区计算机科学

Information Systems Pub Date : 2024-12-06 DOI: 10.1016/j.is.2024.102494

Christos Dalamagkas, V.D. Melissianos, George Papadakis, Angelos Georgakis, Vasileios-Martin Nikiforidis, Kostas Hrissagis-Chrysagis

{"title":"The Open V2X Management Platform: An intelligent charging station management system","authors":"Christos Dalamagkas, V.D. Melissianos, George Papadakis, Angelos Georgakis, Vasileios-Martin Nikiforidis, Kostas Hrissagis-Chrysagis","doi":"10.1016/j.is.2024.102494","DOIUrl":"10.1016/j.is.2024.102494","url":null,"abstract":"<div><div>We present an open-source web-based system, called Open V2X Management Platform (O-V2X-MP), which facilitates the management of charging points for electric vehicles with the goal of realizing Vehicle-to-Everything (V2X) scenarios. First, we describe its backend, which comprises several components connected through a microservices architecture leveraging Docker containers. Then, we elaborate on its frontend, which provides numerous functionalities for common users (i.e., EV drivers) and administrators. Finally, we demonstrate its data analytics capabilities, showing that O-V2X-MP can seamlessly integrate AI pipelines from the Python ecosystem. In particular, we examine two tasks of particular interest for charging point operators: (i) the clustering of EV drivers into profiles of predictable behavior, and (ii) the prediction of the overall daily load for each individual charging station. In our experiments, we use proprietary and public real-world data, verifying the high effectiveness achieved in both tasks.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"129 ","pages":"Article 102494"},"PeriodicalIF":3.0,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143164402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

VOOL: A modular insight-based framework for vocalizing OLAP sessions

IF 3 2区计算机科学

Information Systems Pub Date : 2024-12-02 DOI: 10.1016/j.is.2024.102496

Matteo Francia, Enrico Gallinucci, Matteo Golfarelli, Stefano Rizzi

{"title":"VOOL: A modular insight-based framework for vocalizing OLAP sessions","authors":"Matteo Francia, Enrico Gallinucci, Matteo Golfarelli, Stefano Rizzi","doi":"10.1016/j.is.2024.102496","DOIUrl":"10.1016/j.is.2024.102496","url":null,"abstract":"<div><div>OLAP streamlines the exploration of multidimensional data cubes by allowing decision-makers to build sessions of analytical queries via a “point-and-click” interaction. However, new scenarios are appearing in which alternative forms of user-system communication, based for instance on natural language, are necessary. To cope with these scenarios, we present VOOL, an extensible framework for the vocalization of the results of OLAP sessions. To avoid flooding the user with long and tedious descriptions, we choose to vocalize only selected insights automatically extracted from query results. Insights are quantitative and rich-in-semantics characterizations of the results of an OLAP query, and they also take into account the user’s intentions as expressed by OLAP operators. Firstly, they are extracted using statistics and machine learning algorithms; then an optimization algorithm is applied to select the most relevant insights respecting a limit on the overall duration of vocalization. Finally, the selected insights are sorted into a comprehensive description that is vocalized to the user. After describing and formalizing our approach, we evaluate it from the points of view of efficiency, effectiveness, and operativity, also by comparing it with LLM-based applications.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"129 ","pages":"Article 102496"},"PeriodicalIF":3.0,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143164401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Discovering partially ordered workflow models 发现部分有序的工作流模型

IF 3 2区计算机科学

Information Systems Pub Date : 2024-11-25 DOI: 10.1016/j.is.2024.102493

Humam Kourani , Sebastiaan J. van Zelst , Daniel Schuster , Wil M.P. van der Aalst

{"title":"Discovering partially ordered workflow models","authors":"Humam Kourani , Sebastiaan J. van Zelst , Daniel Schuster , Wil M.P. van der Aalst","doi":"10.1016/j.is.2024.102493","DOIUrl":"10.1016/j.is.2024.102493","url":null,"abstract":"<div><div>In many real-world scenarios, processes naturally define partial orders over their constituent tasks. Partially ordered representations can be exploited in process discovery as they facilitate modeling such processes. The Partially Ordered Workflow Language (POWL) extends partially ordered representations with control-flow operators to support modeling common process constructs such as choice and loop structures. POWL integrates the hierarchical nature of process trees with the flexibility of partially ordered representations, opening up significant opportunities in process discovery. This paper presents and compares various approaches for the automated discovery of POWL models. We investigate the effects of applying varying validity criteria to partial orders, and we propose methods for incorporating frequency information to improve the quality of the discovered models. Additionally, we propose alternative visualizations for POWL models, offering different approaches that may be useful in various contexts. The discovery approaches are evaluated using various real-life data sets, demonstrating the ability of POWL models to capture complex process structures.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"128 ","pages":"Article 102493"},"PeriodicalIF":3.0,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Learning policies for resource allocation in business processes 学习业务流程中资源分配的策略

IF 3 2区计算机科学

Information Systems Pub Date : 2024-11-22 DOI: 10.1016/j.is.2024.102492

Jeroen Middelhuis , Riccardo Lo Bianco , Eliran Sherzer , Zaharah Bukhsh , Ivo Adan , Remco Dijkman

{"title":"Learning policies for resource allocation in business processes","authors":"Jeroen Middelhuis , Riccardo Lo Bianco , Eliran Sherzer , Zaharah Bukhsh , Ivo Adan , Remco Dijkman","doi":"10.1016/j.is.2024.102492","DOIUrl":"10.1016/j.is.2024.102492","url":null,"abstract":"<div><div>Efficient allocation of resources to activities is pivotal in executing business processes but remains challenging. While resource allocation methodologies are well-established in domains like manufacturing, their application within business process management remains limited. Existing methods often do not scale well to large processes with numerous activities or optimize across multiple cases. This paper aims to address this gap by proposing two learning-based methods for resource allocation in business processes to minimize the average cycle time of cases. The first method leverages Deep Reinforcement Learning (DRL) to learn policies by allocating resources to activities. The second method is a score-based value function approximation approach, which learns the weights of a set of curated features to prioritize resource assignments. We evaluated the proposed approaches on six distinct business processes with archetypal process flows, referred to as scenarios, and three realistically sized business processes, referred to as composite business processes, which are a combination of the scenarios. We benchmarked our methods against traditional heuristics and existing resource allocation methods. The results show that our methods learn adaptive resource allocation policies that outperform or are competitive with the benchmarks in five out of six scenarios. The DRL approach outperforms all benchmarks in all three composite business processes and finds a policy that is, on average, 12.7% better than the best-performing benchmark.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"128 ","pages":"Article 102492"},"PeriodicalIF":3.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

STracker: A framework for identifying sentiment changes in customer feedbacks STracker：识别客户反馈中情感变化的框架

IF 3 2区计算机科学

Information Systems Pub Date : 2024-11-20 DOI: 10.1016/j.is.2024.102491

Petri Puustinen, Maria Stratigi, Kostas Stefanidis

引用次数: 0

Two-level massive string dictionaries 两级海量字符串词典

IF 3 2区计算机科学

Information Systems Pub Date : 2024-11-08 DOI: 10.1016/j.is.2024.102490

Paolo Ferragina, Mariagiovanna Rotundo, Giorgio Vinciguerra

{"title":"Two-level massive string dictionaries","authors":"Paolo Ferragina, Mariagiovanna Rotundo, Giorgio Vinciguerra","doi":"10.1016/j.is.2024.102490","DOIUrl":"10.1016/j.is.2024.102490","url":null,"abstract":"<div><div>We study the problem of engineering space–time efficient data structures that support membership and rank queries on <em>very</em> large static dictionaries of strings.</div><div>Our solution is based on a very simple approach that decouples string storage and string indexing by means of a block-wise compression of the sorted dictionary strings (to be stored in external memory) and a succinct implementation of a Patricia trie (to be stored in internal memory) built on the first string of each block. On top of this, we design an in-memory cache that, given a sample of the query workload, augments the Patricia trie with additional information to reduce the number of I/Os of future queries.</div><div>Our experimental evaluation on two new datasets, which are at least one order of magnitude larger than the ones used in the literature, shows that (i) the state-of-the-art compressed string dictionaries, compared to Patricia tries, do not provide significant benefits when used in a large-scale indexing setting, and (ii) our two-level approach enables the indexing and storage of 3.5 billion strings taking 273 GB in just less than 200 MB of internal memory and 83 GB of compressed disk space, while still guaranteeing comparable or faster query performance than those offered by array-based solutions used in modern storage systems, such as RocksDB, thus possibly influencing their future design.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"128 ","pages":"Article 102490"},"PeriodicalIF":3.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142660695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A generative and discriminative model for diversity-promoting recommendation 促进多样性推荐的生成和判别模型

IF 3 2区计算机科学

Information Systems Pub Date : 2024-11-06 DOI: 10.1016/j.is.2024.102488

Yuli Liu

{"title":"A generative and discriminative model for diversity-promoting recommendation","authors":"Yuli Liu","doi":"10.1016/j.is.2024.102488","DOIUrl":"10.1016/j.is.2024.102488","url":null,"abstract":"<div><div>Diversity-promoting recommender systems with the goal of recommending diverse and relevant results to users, have received significant attention. However, current studies often face a trade-off: they either recommend highly accurate but homogeneous items or boost diversity at the cost of relevance, making it challenging for users to find truly satisfying recommendations that meet both their obvious and potential needs. To overcome this competitive trade-off, we introduce a unified framework that simultaneously leverages a discriminative model and a generative model. This approach allows us to adjust the focus of learning dynamically. Specifically, our framework uses Variational Graph Auto-Encoders to enhance the diversity of recommendations, while Graph Convolution Networks are employed to ensure high accuracy in predicting user preferences. This dual focus enables our system to deliver recommendations that are both diverse and closely aligned with user interests. Inspired by the quality <em>vs.</em> diversity decomposition of Determinantal Point Process (DPP) kernel, we design the DPP likelihood-based loss function as the joint modeling loss. Extensive experiments on three real-world datasets, demonstrating that the unified framework goes beyond quality-diversity trade-off, <em>i.e.</em>, instead of sacrificing accuracy for promoting diversity, the joint modeling actually boosts both metrics.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"128 ","pages":"Article 102488"},"PeriodicalIF":3.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142660690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Soundness unknotted: An efficient soundness checking algorithm for arbitrary cyclic process models by loosening loops 不打结的健全性：通过松散循环对任意循环过程模型进行高效健全性检查的算法

IF 3 2区计算机科学

Information Systems Pub Date : 2024-10-23 DOI: 10.1016/j.is.2024.102476

Thomas M. Prinz , Yongsun Choi , N. Long Ha

引用次数: 0

The composition diagram of a complex process: Enhancing understanding of hierarchical business processes 复杂流程的组成图：加强对分层业务流程的理解

IF 3 2区计算机科学

Information Systems Pub Date : 2024-10-21 DOI: 10.1016/j.is.2024.102489

Pavol Jurik , Peter Schmidt , Martin Misut , Ivan Brezina , Marian Reiff

{"title":"The composition diagram of a complex process: Enhancing understanding of hierarchical business processes","authors":"Pavol Jurik , Peter Schmidt , Martin Misut , Ivan Brezina , Marian Reiff","doi":"10.1016/j.is.2024.102489","DOIUrl":"10.1016/j.is.2024.102489","url":null,"abstract":"<div><div>The article presents the Composition Diagram of a Complex Process (CDCP), a new diagramming method for modelling business processes with complex vertical structures. This Method addresses the limitations of traditional modelling techniques such as BPMN, Activity Diagrams (AD), and Event-Driven Process Chains (EPC).</div><div>The experiment was carried out on 277 students from different study programs and grades to determine the effectiveness of the methods. The main objective was to evaluate the usability and effectiveness of CDCP compared to established methods, focusing on two primary tasks: interpretation and diagram creation. The participant's performance was evaluated based on the objective results of the tasks and the subjective feedback of the questionnaire. The results indicate that CDCP was the effective method for the reading and drawing tasks, outperforming BPMN and EPC in terms of understanding and ease of use. Statistical analysis of variance showed that while the year of the study did not significantly affect performance, the study program and Method used had a significant effect. These findings highlight the potential of CDCP as a more accessible and intuitive business process modelling tool, even for users with minimal prior experience.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"128 ","pages":"Article 102489"},"PeriodicalIF":3.0,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0