Int. J. Inf. Technol. Web Eng.最新文献

{"title":"On Using Multiple Disabilities Profiles to Adapt Multimedia Documents: A Novel Graph-Based Method","authors":"Asma Saighi, Zakaria Laboudi, P. Roose, Sébastien Laborie, N. Ghoualmi-Zine","doi":"10.4018/ijitwe.2020070103","DOIUrl":"https://doi.org/10.4018/ijitwe.2020070103","url":null,"abstract":"Currently, advanced technological hardware can offer mobile devices which fits in the hand with a capacity to consult documents at anytime and anywhere. Multiple user context constraints as well as mobile device capabilities may involve the adaptation of multimedia content. In this article, the authors propose a new graph-based method for adapting multimedia documents in complex situations. Each contextual situation could correspond to a physical handicap and therefore triggers an adaptation action using ontological reasoning. Consequently, when several contextual situations are identified, this leads to multiple disabilities and may give rise to inconsistency between triggered actions. Their method allows modeling relations between adaptation-actions to select the compatible triggerable ones. In order to evaluate the feasibility and the performance of their proposal, an experimental study has been made on some real scenarios. When tested and compared with some existing approaches, their proposal showed improvements according to various criteria.","PeriodicalId":222340,"journal":{"name":"Int. J. Inf. Technol. Web Eng.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122480658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IoT-Based Smart Home Process Management Using a Workflow Approach","authors":"Mohammed Eldjilali Ouldkablia, Kechar Bouabdellah, S. Bouzefrane","doi":"10.4018/ijitwe.2020040103","DOIUrl":"https://doi.org/10.4018/ijitwe.2020040103","url":null,"abstract":"ThenewconceptoftheInternetofThings(IoT)isbringingnewformsofknowledgeandapplications thatrelyonsmartobjectsabletosenseandprocessthecollecteddataonaremoteworkflowserverin theperspectivetogenerateautomateddecisions.Inthiscontext,oneofthemainproblemsishowto schedulethedataflowcirculatingbetweenobjects,andbetweenobjectsapplications.Thecooperation betweentheseobjectsisapromisingsolutiontomeetthischallenge.Businessprocessmanagement (BPM)isthemostadaptedwaytocarryoutdatamanagementthankstoworkflowprocesses.Tothis end,anewsemanticsoperatorwhichtheauthorscallagatewayforintelligentprocessschedulingof IoT(GIPSIT)isproposedasasemanticgatewayenablingthemanagementofdataflowscirculating between theconnectedobjectsof IoT.The researchersvalidate their approachbasedonGIPSIT operatorbyimplementingarealisticeHealthbased-scenarioinaSmartHome.Theobtainedfindings showedclearlytheimportanceofthisnewoperatorinthecontextofIoT. KEyWoRdS BPMN, Internet of Things, Packet Tracer, SmartHome, Workflow","PeriodicalId":222340,"journal":{"name":"Int. J. Inf. Technol. Web Eng.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122287234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"eHealth Adoption on Patients' Pre-Consultation Waiting Time: A Comparative Assessment of Two District Hospitals in Abuja, Nigeria","authors":"I. Ekong, O. Esan, E. Chukwu, Mohammed B. Kawu","doi":"10.4018/ijitwe.2020040105","DOIUrl":"https://doi.org/10.4018/ijitwe.2020040105","url":null,"abstract":"Evidence to support widespread adoption of digital health tools in hospitals is still lacking, and proof of their acceptance within the health system is largely missing. This study compared patient's pre-consultation waiting time (time spent at the pay-point, registration, and nursing-station prior to consultation) in two hospitals, one using paper based registration system and the other using an electronic (eHealth) registration system. Structured questionnaires were administered to both patients and health workers to determine and compare factors affecting care delivery wait times and how the use or non-use of eHealth in patient's registration process influence it. In addition, patient wait times were measured in both hospitals at these care points. Overall aggregate waiting time was observed to be longer in Maitama District Hospital (MDH) using the electronic hospital information system. This variance was found to be statistically significant as can be seen (t= 58.405, p=0.024). Inspite of this, wait times at registration and pay-point was significantly lower for MDH.","PeriodicalId":222340,"journal":{"name":"Int. J. Inf. Technol. Web Eng.","volume":"225 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116134219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Semantic Matching Strategy for Very Large Knowledge Bases Integration","authors":"A. M. Rinaldi, Cristiano Russo, K. Madani","doi":"10.4018/ijitwe.2020040101","DOIUrl":"https://doi.org/10.4018/ijitwe.2020040101","url":null,"abstract":"Over the last few decades, data has assumed a central role, becoming one of the most valuable items in society. The exponential increase of several dimensions of data, e.g. volume, velocity, variety, veracity, and value, has led the definition of novel methodologies and techniques to represent, manage, and analyse data. In this context, many efforts have been devoted in data reuse and integration processes based on the semantic web approach. According to this vision, people are encouraged to share their data using standard common formats to allow more accurate interconnection and integration processes. In this article, the authors propose an ontology matching framework using novel combinations of semantic matching techniques to find accurate mappings between formal ontologies schemas. Moreover, an upper-level ontology is used as a semantic bridge. An implementation of the proposed framework is able to retrieve, match, and align ontologies. The framework has been evaluated with the state-of-the-art ontologies in the domain of cultural heritage and its performances have been measured by means of standard measures.","PeriodicalId":222340,"journal":{"name":"Int. J. Inf. Technol. Web Eng.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134057646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Query Expansion Techniques and Content-Based Filtering for Personalizing Analysis in Big Data","authors":"Menaceur Sadek, M. Derdour, Abdelkrim Bouramoul","doi":"10.4018/ijitwe.2020040104","DOIUrl":"https://doi.org/10.4018/ijitwe.2020040104","url":null,"abstract":"The recent debates on personalizing analyses in a Big Data context are one of the most solicited challenges for business intelligence (BI) administrators. The high-volume, the high-variety, and the high-velocity of Big Data have produced difficulty in storing, processing, and analyzing data in traditional systems. These 3Vs (volume, velocity, and variety) created many new challenges and make them difficult to extract the specific needs of the users. In addition, the user may be faced with the problem of disorientation; he does not know what information really corresponds to his needs. The information personalization systems aim to overcome these problems of disorientation by using a user profile. The effectiveness of the personalization system in a Big Data context is to demonstrate by the relevance and accuracy of the content of the results obtained, according to the needs of the user and the context of the research. Nevertheless, most of the recent research focused on the relational data warehouse personalizing and ignored the integration of the user context into the analysis of OLAP cubes, which is the first concerned to execute the user's multidimensional queries. To deal with this, the authors propose in this article a dynamic personalizing approach in Big Data context using OLAP cubes, based on the Content-Based Filtering, and the Query Expansion techniques. The first step in the proposal consists of processing the user queries by an enrichment technique in order to integrate the user profile and his searching context to reduce the searching space in the OLAP cube, and use the expansion technique to extend the scope of the analysis in the OLAP cube. The retrieved results are: “as relevant as possible” compared to the user's initial request. Afterward, they use information filtering techniques such as content-based filtering to personalize the analysis in the reduced data cube according to the term frequency and cosine similarity. Finally, they present a case study and experiences results to evaluate and validate their approach.","PeriodicalId":222340,"journal":{"name":"Int. J. Inf. Technol. Web Eng.","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115572715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dealing with Precise and Imprecise Temporal Data in Crisp Ontology","authors":"F. Ghorbel, F. Hamdi, Elisabeth Métais","doi":"10.4018/IJITWE.2020040102","DOIUrl":"https://doi.org/10.4018/IJITWE.2020040102","url":null,"abstract":"This article proposes a crisp-based approach for representing and reasoning about concepts evolving in time and of their properties in terms of qualitative relations (e.g., “before”) in addition to quantitative ones, time intervals and points. It is not only suitable to handle precise time intervals and points, but also imprecise ones. It extends the 4D-fluents approach with crisp components to represent handed data. It also extends the Allen's interval algebra. This extension allows reasoning about imprecise time intervals. Compared to related work, it is based on crisp set theory. These relations preserve many properties of the original algebra. Their definitions are adapted to allow relating a time interval and a time point, and two time points. All relations can be used for temporal reasoning by means of transitivity tables. Finally, it proposes a crisp ontology that based on the extended Allen's algebra instantiates the 4D-fluents-based representation.","PeriodicalId":222340,"journal":{"name":"Int. J. Inf. Technol. Web Eng.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125627749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generating Summaries Through Unigram and Bigram: Text Summarization","authors":"Nesreen Alsharman, I. Pivkina","doi":"10.4018/ijitwe.2020010105","DOIUrl":"https://doi.org/10.4018/ijitwe.2020010105","url":null,"abstract":"This article describes a new method for generating extractive summaries directly via unigram and bigram extraction techniques. The methodology uses the selective part of speech tagging to extract significant unigrams and bigrams from a set of sentences. Extracted unigrams and bigrams along with other features are used to build a final summary. A new selective rule-based part of speech tagging system is developed that concentrates on the most important parts of speech for summarizations: noun, verb, and adjective. Other parts of speech such as prepositions, articles, adverbs, etc., play a lesser role in determining the meaning of sentences; therefore, they are not considered when choosing significant unigrams and bigrams. The proposed method is tested on two problem domains: citations and opinosis data sets. Results show that the proposed method performs better than Text-Rank, LexRank, and Edmundson summarization methods. The proposed method is general enough to summarize texts from any domain.","PeriodicalId":222340,"journal":{"name":"Int. J. Inf. Technol. Web Eng.","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121391482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Intelligent System for Predicting a User Access to a Web Based E-Learning System Using Web Mining","authors":"V. Sathiyamoorthi","doi":"10.4018/ijitwe.2020010106","DOIUrl":"https://doi.org/10.4018/ijitwe.2020010106","url":null,"abstract":"In this Internet era, with ever-increasing interactions among participants, the size of the data is increasing so rapidly such that the information available to us in the near future is going to be unpredictable. Modeling and visualizing such data are one of the challenging tasks in the data analytics field. Therefore, business intelligence is the way in which a company can use data to improve business and operational efficiency whereas data analytics involves improving ways of making intelligence out of that data before acting on it. Thus, the proposed work focuses on prevailing challenges in data analytics and its application on social media like Facebook, Twitter, blogs, e-commerce, e-service and so on. Among all of the possible interactions, e-commerce, e-education, and e-services have been identified as important domains for analytics techniques. So, it focuses on machine learning technique in improving practice and research in such e-X domains. Empirical analysis is done to show the performance of proposed system using real-time datasets.","PeriodicalId":222340,"journal":{"name":"Int. J. Inf. Technol. Web Eng.","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115150924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Query Optimization in Crowd-Sourcing Using Multi-Objective Ant Lion Optimizer","authors":"Deepak Kumar, D. Mehrotra, Rohit Bansal","doi":"10.4018/IJITWE.2019100103","DOIUrl":"https://doi.org/10.4018/IJITWE.2019100103","url":null,"abstract":"Nowadays, query optimization is a biggest concern for crowd-sourcing systems, which are developed for relieving the user burden of dealing with the crowd. Initially, a user needs to submit a structured query language (SQL) based query and the system takes the responsibility of query compiling, generating an execution plan, and evaluating the crowd-sourcing market place. The input queries have several alternative execution plans and the difference in crowd-sourcing cost between the worst and best plans. In relational database systems, query optimization is essential for crowd-sourcing systems, which provides declarative query interfaces. Here, a multi-objective query optimization approach using an ant-lion optimizer was employed for declarative crowd-sourcing systems. It generates a query plan for developing a better balance between the latency and cost. The experimental outcome of the proposed methodology was validated on UCI automobile and Amazon Mechanical Turk (AMT) datasets. The proposed methodology saves 30%-40% of cost in crowd-sourcing query optimization compared to the existing methods.","PeriodicalId":222340,"journal":{"name":"Int. J. Inf. Technol. Web Eng.","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133186600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Enhanced and Efficient Multi-View Clustering Trust Inference Approach by GA Model","authors":"M. Ravichandran, M. SubramanianK., R. Jothikumar","doi":"10.4018/IJITWE.2019100104","DOIUrl":"https://doi.org/10.4018/IJITWE.2019100104","url":null,"abstract":"Multi-view affinity propagation (MAP) methods are widely accepted techniques, measure the within-view clustering and clustering consistency. These suffer from similarity and correlation between clusters. The trust and similarity measured was introduced as a new approach to overcome the problem. But these approaches suffer from low accuracy and coverage due to avoidance of implicit trust. So, a framework called multi-view clustering based on gray affinity (MVC-GA) created by integrating both similarity and implicit trust. Similarity between two clusters is obtained by applying the Pearson Correlation Coefficient-based similarity. It utilizes the collaborative filter-based trust evaluation for each clustered view in terms of the similarity based on the gray affinity nn algorithm. Classification of incomplete occurrences is addressed based on GA Function. Experiments on the benchmark data sets have been performed to validate the proposed framework. It is shown that MVC-GA can improve the multi-view clustering accuracy and coverage.","PeriodicalId":222340,"journal":{"name":"Int. J. Inf. Technol. Web Eng.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114358970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}