Journal of Web Semantics最新文献_第7页

A multiplatform reasoning engine for the Semantic Web of Everything 万物语义网的多平台推理引擎

IF 2.5 3区计算机科学

Journal of Web Semantics Pub Date : 2022-07-01 DOI: 10.1016/j.websem.2022.100709

Michele Ruta, Floriano Scioscia, Ivano Bilenchi, Filippo Gramegna, Giuseppe Loseto, Saverio Ieva, Agnese Pinto

引用次数: 6

A hybrid E-learning recommendation integrating adaptive profiling and sentiment analysis 集成自适应分析和情感分析的混合电子学习推荐

IF 2.5 3区计算机科学

Journal of Web Semantics Pub Date : 2022-04-01 DOI: 10.1016/j.websem.2021.100700

Hadi Ezaldeen , Rachita Misra , Sukant Kishoro Bisoy , Rawaa Alatrash , Rojalina Priyadarshini

{"title":"A hybrid E-learning recommendation integrating adaptive profiling and sentiment analysis","authors":"Hadi Ezaldeen , Rachita Misra , Sukant Kishoro Bisoy , Rawaa Alatrash , Rojalina Priyadarshini","doi":"10.1016/j.websem.2021.100700","DOIUrl":"10.1016/j.websem.2021.100700","url":null,"abstract":"<div><p><span>This research proposes a novel framework named Enhanced e-Learning Hybrid Recommender System (ELHRS) that provides an appropriate e-content with the highest predicted ratings corresponding to the learner’s particular needs. To accomplish this, a new model is developed to deduce the Semantic Learner Profile automatically. It adaptively associates the learning patterns and rules depending on the learner’s behavior and the semantic relations computed in the semantic matrix that mutually links e-learning materials and terms. Here, a semantic-based approach for term expansion is introduced using DBpedia and WordNet ontologies. Further, various </span>sentiment analysis<span><span> models are proposed and incorporated as a part of the recommender system<span><span> to predict ratings of e-learning resources from posted text reviews utilizing fine-grained sentiment classification on five discrete classes. Qualitative Natural Language Processing (NLP) methods with tailored-made </span>Convolutional Neural Network (CNN) are developed and evaluated on our customized dataset collected for a specific domain and a public dataset. Two improved </span></span>language models are introduced depending on Skip-Gram (S-G) and Continuous Bag of Words (CBOW) techniques. In addition, a robust language model based on hybridization of these couple of methods is developed to derive better vocabulary representation, yielding better accuracy 89.1% for the CNN-Three-Channel-Concatenation model. The suggested recommendation methodology depends on the learner’s preferences, other similar learners’ experience and background, deriving their opinions from the reviews towards the best learning resources. This assists the learners in finding the desired e-content at the proper time.</span></p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82902142","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}

引用次数: 19

An empirical study of representing adjectives over knowledge bases: Approach, lexicon and application 形容词知识库表示的实证研究:方法、词汇和应用

IF 2.5 3区计算机科学

Journal of Web Semantics Pub Date : 2022-04-01 DOI: 10.1016/j.websem.2021.100681

Jiwei Ding, Wei Hu, Xin Yu, Yuzhong Qu

{"title":"An empirical study of representing adjectives over knowledge bases: Approach, lexicon and application","authors":"Jiwei Ding, Wei Hu, Xin Yu, Yuzhong Qu","doi":"10.1016/j.websem.2021.100681","DOIUrl":"10.1016/j.websem.2021.100681","url":null,"abstract":"<div><p>Adjectives are common in natural language, and their usage and semantics have been studied broadly. In recent years, with the rapid growth of knowledge bases (KBs), many knowledge-based question answering (KBQA) systems are developed to answer users’ natural language questions over KBs. A fundamental task of such systems is to transform natural language questions into structural queries, e.g., SPARQL queries. Thus, such systems require knowledge about how natural language expressions are represented in KBs, including adjectives. In this paper, we specifically address the problem of representing adjectives over KBs. We propose a novel approach, called Adj2SP, to represent adjectives as SPARQL query patterns. Adj2SP contains a statistic-based approach and a neural network-based approach, both of them can effectively reduce the search space for adjective representations and overcome the lexical gap between input adjectives and their target representations. Two adjective representation datasets are built for evaluation, with adjectives used in QALD and Yahoo! Answers, as well as their representations over DBpedia. Experimental results show that Adj2SP can generate representations of high quality and significantly outperform several alternative approaches in F1-score. Furthermore, we publish Lark, a lexicon for adjective representations over KBs. Current KBQA systems show an improvement of over 24% in F1-score by integrating Adj2SP.</p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73837177","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}

引用次数: 0

A study of the quality of Wikidata 维基数据质量的研究

IF 2.5 3区计算机科学

Journal of Web Semantics Pub Date : 2022-04-01 DOI: 10.1016/j.websem.2021.100679

Kartik Shenoy , Filip Ilievski , Daniel Garijo , Daniel Schwabe , Pedro Szekely

引用次数: 35

A framework for differentially-private knowledge graph embeddings 差分私有知识图嵌入框架

IF 2.5 3区计算机科学

Journal of Web Semantics Pub Date : 2022-04-01 DOI: 10.1016/j.websem.2021.100696

Xiaolin Han , Daniele Dell’Aglio , Tobias Grubenmann , Reynold Cheng , Abraham Bernstein

引用次数: 8

The Smart Musical Instruments Ontology 智能乐器本体

IF 2.5 3区计算机科学

Journal of Web Semantics Pub Date : 2022-04-01 DOI: 10.1016/j.websem.2021.100687

Luca Turchet , Paolo Bouquet , Andrea Molinari , György Fazekas

{"title":"The Smart Musical Instruments Ontology","authors":"Luca Turchet , Paolo Bouquet , Andrea Molinari , György Fazekas","doi":"10.1016/j.websem.2021.100687","DOIUrl":"10.1016/j.websem.2021.100687","url":null,"abstract":"<div><p>The Smart Musical Instruments (SMIs) are an emerging category of musical instruments that belongs to the wider class of Musical Things within the Internet of Musical Things paradigm. SMIs encompass sensors, actuators, embedded intelligence, and wireless connectivity to local networks and to the Internet. Interoperability represents a key issue within this domain, where heterogeneous SMIs are envisioned to exchange information between each other and a plethora of Musical Things. This paper proposes an ontology for the representation of the knowledge related to SMIs, with the aim of facilitating interoperability between SMIs as well as with other Musical Things interacting with them. There was no previous comprehensive data model for the SMIs domain, however the new ontology relates to existing ontologies, including the SOSA Ontology for the representation of sensors and actuators, the Audio Effects Ontology dealing with the description of digital audio effects, and the IoMusT Ontology for the representation Musical Things and IoMusT ecosystems. This paper documents the design of the ontology and its evaluation with respect to specific requirements gathered from an extensive literature review, which was based on scenarios involving SMIs stakeholders, such as performers and studio producers. The SMI Ontology can be accessed at: <span>https://w3id.org/smi#</span><svg><path></path></svg>.</p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75247656","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}

引用次数: 11

A reference architecture for social robots 社交机器人的参考体系结构

IF 2.5 3区计算机科学

Journal of Web Semantics Pub Date : 2022-04-01 DOI: 10.1016/j.websem.2021.100683

Luigi Asprino , Paolo Ciancarini , Andrea Giovanni Nuzzolese , Valentina Presutti , Alessandro Russo

{"title":"A reference architecture for social robots","authors":"Luigi Asprino , Paolo Ciancarini , Andrea Giovanni Nuzzolese , Valentina Presutti , Alessandro Russo","doi":"10.1016/j.websem.2021.100683","DOIUrl":"10.1016/j.websem.2021.100683","url":null,"abstract":"<div><p><span>Social robotics poses tough challenges to software designers who are required to take care of difficult architectural drivers like acceptability, trust of robots as well as to guarantee that robots establish a personalized interaction with their users. Moreover, in this context recurrent<span><span> software design issues such as ensuring interoperability, improving </span>reusability<span> and customizability of software components also arise. Designing and implementing social robotic software architectures is a time-intensive activity requiring multi-disciplinary expertise: this makes it difficult to rapidly develop, customize, and personalize robotic solutions. These challenges may be mitigated at design time by choosing certain architectural styles, implementing specific architectural patterns and using particular technologies. Leveraging on our experience in the MARIO project, in this paper we propose a series of principles that social robots may benefit from. These principles lay also the foundations for the design of a reference software architecture for social robots. The goal of this work is twofold: </span></span></span><em>(i)</em> Establishing a reference architecture whose components are unambiguously characterized by an ontology thus allowing to easily reuse them in order to implement and personalize social robots; <em>(ii)</em><span> Introducing a series of standardized software components for social robots architecture (mostly relying on ontologies and semantic technologies) to enhance interoperability, to improve explainability, and to favor rapid prototyping.</span></p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84635634","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}

引用次数: 3

NLIRE: A Natural Language Inference method for Relation Extraction 关系抽取的自然语言推理方法

IF 2.5 3区计算机科学

Journal of Web Semantics Pub Date : 2022-04-01 DOI: 10.1016/j.websem.2021.100686

Wenfei Hu , Lu Liu , Yupeng Sun , Yu Wu , Zhicheng Liu , Ruixin Zhang , Tao Peng

{"title":"NLIRE: A Natural Language Inference method for Relation Extraction","authors":"Wenfei Hu , Lu Liu , Yupeng Sun , Yu Wu , Zhicheng Liu , Ruixin Zhang , Tao Peng","doi":"10.1016/j.websem.2021.100686","DOIUrl":"10.1016/j.websem.2021.100686","url":null,"abstract":"<div><p>Relation extraction task aims at detecting the semantic relation between a pair of entities in a given target sentence. However, previous methods lack the description of the relation definition, thus needing to model the implication of relations during training. To tackle this issue, we propose a natural language inference method for relation extraction. Given a premise and a hypothesis, the natural language inference task refers to predicting whether the facts in the premise necessarily imply the facts in the hypothesis. Specifically, for each relation type, we construct a relation description. These relation descriptions are the definition of relation, containing prior knowledge that helps model understand the meaning of relation. The given target sentence is viewed as the premise, and these descriptions are viewed as the hypotheses. Then model infers whether these hypotheses can be concluded from the premise. Based on the inference results, our model selects the relation corresponding to the most confident hypothesis as the prediction. Substantial experiments on SemEval2010 Task8 dataset demonstrate that the proposed method achieves state-of-the-art performance.</p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81620919","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}

引用次数: 3

A multiplatform energy-aware OWL reasoner benchmarking framework 一个多平台能量感知OWL推理基准测试框架

IF 2.5 3区计算机科学

Journal of Web Semantics Pub Date : 2022-04-01 DOI: 10.1016/j.websem.2021.100694

Floriano Scioscia, Ivano Bilenchi, Michele Ruta, Filippo Gramegna, Davide Loconte

引用次数: 3

Skeleton parsing for complex question answering over knowledge bases 基于知识库的复杂问题回答的骨架解析

IF 2.5 3区计算机科学

Journal of Web Semantics Pub Date : 2022-04-01 DOI: 10.1016/j.websem.2021.100698

Yawei Sun , Pengwei Li , Gong Cheng , Yuzhong Qu

引用次数: 6