Journal of Web Semantics最新文献

{"title":"Time-aware evidence ranking for fact-checking","authors":"Liesbeth Allein ,&nbsp;Isabelle Augenstein ,&nbsp;Marie-Francine Moens","doi":"10.1016/j.websem.2021.100663","DOIUrl":"10.1016/j.websem.2021.100663","url":null,"abstract":"<div><p>Truth can vary over time. Fact-checking decisions on claim veracity should therefore take into account temporal information of both the claim and supporting or refuting evidence. In this work, we investigate the hypothesis that the timestamp of a Web page is crucial to how it should be ranked for a given claim. We delineate four temporal ranking methods that constrain evidence ranking differently and simulate hypothesis-specific evidence rankings given the evidence timestamps as gold standard. Evidence ranking in three fact-checking models is ultimately optimized using a learning-to-rank loss function. Our study reveals that time-aware evidence ranking not only surpasses relevance assumptions based purely on semantic similarity or position in a search results list, but also improves veracity predictions of time-sensitive claims in particular.</p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S157082682100038X/pdfft?md5=b9db24722ada9dc060b0028d53c7640b&pid=1-s2.0-S157082682100038X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87992041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Optimizing a tableau reasoner and its implementation in Prolog","authors":"Riccardo Zese ,&nbsp;Giuseppe Cota","doi":"10.1016/j.websem.2021.100677","DOIUrl":"https://doi.org/10.1016/j.websem.2021.100677","url":null,"abstract":"<div><p><span>One of the foremost reasoning services for knowledge bases is finding all the justifications for a query. This is useful for debugging purpose and for coping with uncertainty. Among </span>Description Logics<span><span> (DLs) reasoners, the tableau algorithm is one of the most used. However, in order to collect the justifications, the reasoners must manage the non-determinism of the </span>tableau method. For these reasons, a Prolog implementation can facilitate the management of such non-determinism.</span></p><p>The TRILL framework contains three probabilistic reasoners written in Prolog: TRILL, TRILL^<em>P</em><span> and TORNADO. Since they are all part of the same framework, the choice about which to use can be done easily via the framework settings. Each one of them uses different approaches for probabilistic inference and handles different DLs flavors. Our previous work showed that they can sometimes achieve better results than state-of-the-art (non-)probabilistic reasoners.</span></p><p>In this paper we present two optimizations that improve the performances of the TRILL reasoners. The first one consists into identifying the fragment of the KB that allows to perform inference without losing the completeness. The second one modifies which tableau rule to apply and their order of application, in order to reduce the number of operations. Experimental results show the effectiveness of the introduced optimizations.</p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138090273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards the next generation of the LinkedGeoData project using virtual knowledge graphs","authors":"Linfang Ding ,&nbsp;Guohui Xiao ,&nbsp;Albulen Pano ,&nbsp;Claus Stadler ,&nbsp;Diego Calvanese","doi":"10.1016/j.websem.2021.100662","DOIUrl":"10.1016/j.websem.2021.100662","url":null,"abstract":"<div><p>With the advancement of Semantic Technologies, large geospatial data sources have been increasingly published as Linked data on the Web. The <em>LinkedGeoData</em> project is one of the most prominent such projects to create a large knowledge graph from <em>OpenStreetMap</em> (OSM) with global coverage and interlinking of other data sources. In this paper, we report on the ongoing effort of exposing the relational database in LinkedGeoData as a SPARQL endpoint using <em>Virtual Knowledge Graph</em> (VKG) technology. Specifically, we present two realizations of VKGs, using the two systems Sparqlify and Ontop. In order to improve compliance with the OGC GeoSPARQL standard, we have implemented GeoSPARQL support in Ontop v4. Moreover, we have evaluated the VKG-powered LinkedGeoData in the test areas of Italy and Germany. Our experiments demonstrate that such system supports complex GeoSPARQL queries, which confirms that query answering in the VKG approach is efficient.</p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1570826821000378/pdfft?md5=4faeffc9e304792fcc147abfd1e837e1&pid=1-s2.0-S1570826821000378-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89708603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Design, Application and Evaluation of PROV-SwProcess: A PROV extension Data Model for Software Development Processes","authors":"Gabriella Castro Barbosa Costa ,&nbsp;Claudia Werner ,&nbsp;Regina Braga ,&nbsp;Eldânae Nogueira Teixeira ,&nbsp;Victor Ströele ,&nbsp;Marco Antônio Pereira Araújo ,&nbsp;Marcos Alexandre Miguel","doi":"10.1016/j.websem.2021.100676","DOIUrl":"10.1016/j.websem.2021.100676","url":null,"abstract":"<div><p>The literature defines data provenance<span> as the description of the origins of a piece of data and the process by which it arrived in a database. It helps to audit and understand data history and bring transparency to the process. Provenance has been successfully used in scientific computing, chemical industries, and health sciences, considering that these areas require a comprehensive traceability mechanism. Meanwhile, companies have been collecting and storing more data from their systems and processes. This work investigates if the use of provenance models and techniques can support software processes execution analysis and data-driven decision-making, considering the increasing availability of process data provided by companies. PROV-SwProcess, a software development process provenance modeling proposal, was developed and evaluated by process and provenance experts. Our proposal is an extension of the W3C recommended standard model PROV, aiming to capture and store the most relevant information about software development process provenance data. The results suggest that the model’s suitability improves and assists process managers in the software process analysis and supports data-driven decision-making.</span></p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77723070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SemML: Facilitating development of ML models for condition monitoring with semantics","authors":"Baifan Zhou ,&nbsp;Yulia Svetashova ,&nbsp;Andre Gusmao ,&nbsp;Ahmet Soylu ,&nbsp;Gong Cheng ,&nbsp;Ralf Mikut ,&nbsp;Arild Waaler ,&nbsp;Evgeny Kharlamov","doi":"10.1016/j.websem.2021.100664","DOIUrl":"10.1016/j.websem.2021.100664","url":null,"abstract":"<div><p>Monitoring of the state, performance, quality of operations and other parameters of equipment and production processes, which is typically referred to as condition monitoring, is an important common practice in many industries including manufacturing, oil and gas, chemical and process industry. In the age of Industry 4.0, where the aim is a deep degree of production automation, unprecedented amounts of data are generated by equipment and processes, and this enables adoption of Machine Learning (ML) approaches for condition monitoring. Development of such ML models is challenging. On the one hand, it requires collaborative work of experts from different areas, including data scientists, engineers, process experts, and managers with asymmetric backgrounds. On the other hand, there is high variety and diversity of data relevant for condition monitoring. Both factors hampers ML modelling for condition monitoring. In this work, we address these challenges by empowering ML-based condition monitoring with semantic technologies. To this end we propose a software system SemML that allows to reuse and generalise ML pipelines for conditions monitoring by relying on semantics. In particular, SemML has several novel components and relies on ontologies and ontology templates for ML task negotiation and for data and ML feature annotation. SemML also allows to instantiate parametrised ML pipelines by semantic annotation of industrial data. With SemML, users do not need to dive into data and ML scripts when new datasets of a studied application scenario arrive. They only need to annotate data and then ML models will be constructed through the combination of semantic reasoning and ML modules. We demonstrate the benefits of SemML on a Bosch use-case of electric resistance welding with very promising results.</p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1570826821000391/pdfft?md5=13aa3514aea684bfe3a850fdc768a1e0&pid=1-s2.0-S1570826821000391-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89704076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Negative statements considered useful","authors":"Hiba Arnaout ,&nbsp;Simon Razniewski ,&nbsp;Gerhard Weikum ,&nbsp;Jeff Z. Pan","doi":"10.1016/j.websem.2021.100661","DOIUrl":"10.1016/j.websem.2021.100661","url":null,"abstract":"<div><p>Knowledge bases (KBs) about notable entities and their properties are an important asset in applications such as search, question answering and dialog. All popular KBs capture virtually only positive statements, and abstain from taking any stance on statements not stored in the KB. This paper makes the case for explicitly stating salient statements that do <em>not</em><span> hold. Negative statements are useful to overcome limitations of question answering systems that are mainly geared for positive questions; they can also contribute to informative summaries of entities. Due to the abundance of such invalid statements, any effort to compile them needs to address ranking by saliency. We present a statistical inference method for compiling and ranking negative statements, based on expectations from positive statements of related entities in peer groups. Experimental results, with a variety of datasets, show that the method can effectively discover notable negative statements, and extrinsic studies underline their usefulness for entity summarization. Datasets and code are released as resources for further research.</span></p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89778494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intelligent software web agents: A gap analysis","authors":"Sabrina Kirrane","doi":"10.1016/j.websem.2021.100659","DOIUrl":"10.1016/j.websem.2021.100659","url":null,"abstract":"<div><p>Semantic web technologies have shown their effectiveness, especially when it comes to knowledge representation, reasoning, and data integration. However, the original semantic web vision, whereby machine readable web data could be automatically actioned upon by intelligent software web agents, has yet to be realised. In order to better understand the existing technological opportunities and challenges, in this paper we examine the status quo in terms of intelligent software web agents, guided by research with respect to requirements and architectural components, coming from the agents community. We use the identified requirements to both further elaborate on the semantic web agent motivating use case scenario, and to summarise different perspectives on the requirements from the semantic web agent literature. We subsequently propose a hybrid semantic web agent architecture, and use the various components and subcomponents in order to provide a focused discussion in relation to existing semantic web standards and community activities. Finally, we highlight open research opportunities and challenges and take a broader perspective of the research by discussing the potential for intelligent software web agents as an enabling technology for emerging domains, such as digital assistants, cloud computing, and the internet of things.</p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1570826821000342/pdfft?md5=5e359d8b7b907172f9f83e621c1e421a&pid=1-s2.0-S1570826821000342-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88079819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"HeadlineStanceChecker: Exploiting summarization to detect headline disinformation","authors":"Robiert Sepúlveda-Torres,&nbsp;Marta Vicente,&nbsp;Estela Saquete,&nbsp;Elena Lloret,&nbsp;Manuel Palomar","doi":"10.1016/j.websem.2021.100660","DOIUrl":"10.1016/j.websem.2021.100660","url":null,"abstract":"<div><p>The headline of a news article is designed to succinctly summarize its content, providing the reader with a clear understanding of the news item. Unfortunately, in the post-truth era, headlines are more focused on attracting the reader’s attention for ideological or commercial reasons, thus leading to mis- or disinformation through false or distorted headlines. One way of combating this, although a challenging task, is by determining the relation between the headline and the body text to establish the stance. Hence, to contribute to the detection of mis- and disinformation, this paper proposes an approach (<em>HeadlineStanceChecker</em>) that determines the stance of a headline with respect to the body text to which it is associated. The novelty rests on the use of a two-stage classification architecture that uses summarization techniques to shape the input for both classifiers instead of directly passing the full news body text, thereby reducing the amount of information to be processed while keeping important information. Specifically, summarization is done through Positional Language Models leveraging on semantic resources to identify salient information in the body text that is then compared to its corresponding headline. The results obtained show that our approach achieves 94.31% accuracy for the overall classification and the best FNC-1 relative score compared with the state of the art. It is especially remarkable that the system, which uses only the relevant information provided by the automatic summaries instead of the whole text, is able to classify the different stance categories with very competitive results, especially in the <em>discuss</em> stance between the headline and the news body text. It can be concluded that using automatic extractive summaries as input of our approach together with the two-stage architecture is an appropriate solution to the problem.</p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1570826821000354/pdfft?md5=2e9f623b6b4a0278d46a5df6af6c5671&pid=1-s2.0-S1570826821000354-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75634742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Optimizing a tableau reasoner and its implementation in Prolog","authors":"Riccardo Zese, Giuseppe Cota","doi":"10.2139/ssrn.3945445","DOIUrl":"https://doi.org/10.2139/ssrn.3945445","url":null,"abstract":"","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86499553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Crossing the chasm between ontology engineering and application development: A survey","authors":"Paola Espinoza-Arias ,&nbsp;Daniel Garijo ,&nbsp;Oscar Corcho","doi":"10.1016/j.websem.2021.100655","DOIUrl":"10.1016/j.websem.2021.100655","url":null,"abstract":"<div><p>The adoption of Knowledge Graphs (KGs) by public and private organizations to integrate and publish data has increased in recent years. Ontologies play a crucial role in providing the structure for KGs, but are usually disregarded when designing Application Programming Interfaces (APIs) to enable browsing KGs in a developer-friendly manner. In this paper we provide a systematic review of the state of the art on existing approaches to ease access to ontology-based KG data by application developers. We propose two comparison frameworks to understand specifications, technologies and tools responsible for providing APIs for KGs. Our results reveal several limitations on existing API-based specifications, technologies and tools for KG consumption, which outline exciting research challenges including automatic API generation, API resource path prediction, ontology-based API versioning, and API validation and testing.</p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.websem.2021.100655","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87299102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}