{"title":"LodLive, exploring the web of data","authors":"D. Camarda, S. Mazzini, Alessandro Antonuccio","doi":"10.1145/2362499.2362532","DOIUrl":"https://doi.org/10.1145/2362499.2362532","url":null,"abstract":"LodLive project, http://en.lodlive.it/, provides a demonstration of the use of Linked Data standard (RDF, SPARQL) to browse RDF resources. The application aims to spread linked data principles with a simple and friendly interface and reusable techniques. In this report we present an overview of the potential of LodLive, mentioning tools and methodologies that were used to create it.","PeriodicalId":275036,"journal":{"name":"International Conference on Semantic Systems","volume":"22 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134093746","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":"Ontology-driven mindmapping","authors":"P. Kremen, Pavel Micka, Miroslav Blasko, M. Smíd","doi":"10.1145/2362499.2362517","DOIUrl":"https://doi.org/10.1145/2362499.2362517","url":null,"abstract":"Mindmaps have been a popular means for intuitive and user-friendly conceptual modeling for several years. This paper proposes a mindmapping tool driven by semantic web ontologies that allows to assign meanings to the mindmap nodes and, even more importantly, guide the user through mindmap creation by proposing ontological concepts and roles relevant to each mindmap node. The tool is backed by OWL ontologies that allow to capture domain knowledge semantics precisely and rigorously. The tool is being developed as a part of the MONDIS project aimed at efficient knowledge management of immovable cultural heritage failures records. As such, the tool is currently used by civil engineering experts for collaborative authoring of structural damage records.","PeriodicalId":275036,"journal":{"name":"International Conference on Semantic Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133053624","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":"Graph-based ontology analysis in the linked open data","authors":"Lihua Zhao, R. Ichise","doi":"10.1145/2362499.2362508","DOIUrl":"https://doi.org/10.1145/2362499.2362508","url":null,"abstract":"The Linked Open Data (LOD) includes over 31 billion Resource Description Framework (RDF) triples interlinked by around 504 million SameAs links (as of September 2011). The data sets of the LOD use different ontologies to describe instances, that cause the ontology heterogeneity problem. Dealing with the heterogeneous ontologies is a challenging problem and it is time-consuming to manually learn big ontologies in the LOD. The heterogeneity of ontologies in the LOD can be reduced by automatically integrating related ontology classes and properties, which can be retrieved from interlinked instances. The interlinked instances can be represented as an undirected graph, from which we can discover the characteristics of instances and retrieve related ontology classes and properties that are important for linking instances. In this paper, we retrieve graph patterns from several linked data sets and perform ontology alignment methods on each graph pattern to identify related ontology classes and properties from the data sets. We successfully integrate various ontologies, analyze the characteristics of interlinked instances, and detect mistaken properties in the real data sets. Furthermore, our approach solves the ontology heterogeneity problem and helps Semantic Web application developers easily query on various data sets with the integrated ontology.","PeriodicalId":275036,"journal":{"name":"International Conference on Semantic Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127813290","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":"Personal image tagging: a game-based approach","authors":"Jakub Simko, M. Bieliková","doi":"10.1145/2362499.2362512","DOIUrl":"https://doi.org/10.1145/2362499.2362512","url":null,"abstract":"An effective search and organization of personal multimedia repositories demands very specific, owner-related metadata (e.g. person names, places, events). Only the resource owners and their social circles are able to provide these metadata, but are often not motivated to do so. To increase their motivation, we introduce a game-based personal image annotation framework. Today's crowd-based games with a purpose (GWAP) are able to harness human labor to acquire metadata for general domain multimedia resources. However, their deployment in such specific domain as one's personal multimedia is hindered by the issue of extremely small number of competent potential workers. Therefore, a traditional cross-worker agreement filtering of wrong answers cannot be effectively applied. In our approach (which is an extension of an existing image tagging game), we overcome this issue by inviting user to play for his own good i.e. annotate his own images while enjoying the game. This additional motivation causes an overall increase of quality of user-generated metadata and thus allows the use of less strict tag extraction algorithms for producing final set of tags. We show that our approach is able to yield valid image annotations, specific to the context of the resource owner. We also examine its performance with different types of annotated images and tags.","PeriodicalId":275036,"journal":{"name":"International Conference on Semantic Systems","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115551104","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":"Validation of music metadata via game with a purpose","authors":"Peter Dulacka, Jakub Simko, M. Bieliková","doi":"10.1145/2362499.2362526","DOIUrl":"https://doi.org/10.1145/2362499.2362526","url":null,"abstract":"Quantity of music metadata on the Web is sufficient, music recommendation and online repository systems are proof of it. However, it became a real challenge to keep quality of these metadata at reasonable level as the cost of manual validation is too high and current automatic approaches are inaccurate. In this paper we present a game with a purpose called City Lights -- a music metadata validation approach which lowers the cost of human computation and makes the validation fun. Our goal is to get rid of incorrect user-submitted music tags or tags not usable at global scale. We describe the game principles and evaluate the game results.","PeriodicalId":275036,"journal":{"name":"International Conference on Semantic Systems","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124545015","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":"First steps towards a context aware ontology-driven reporting system","authors":"Mika Cohen, Andreas Horndahl, Christian Mårtenson","doi":"10.1145/2362499.2362514","DOIUrl":"https://doi.org/10.1145/2362499.2362514","url":null,"abstract":"In spite of constant technological advances, the nature of today's military conflicts has increased the importance of intelligence gathering by human observers. To allow for efficient exploitation, the information collected needs to be structured. Traditional hand-held reporting systems solves this by assuming a fixed report structure; the reporter submits a report by filling in the various data fields in a predefined report schema.\u0000 In this paper, we consider how to make the report schema aware of the reporting context and also dynamically adapt to information requests posed by actors external to the reporting situation: when a reporter enters data which are relevant to an information request, but do not fully answer the request, the schema expands to include fields that supply the missing information. We consider in detail how to evaluate relevance and how to select the additional data fields to query for.\u0000 When deciding what additional data fields to query for, we take into account not merely what data is missing, but also the information capability of the reporter, i.e., what kind of data the reporter is in a position to supply in the context he or she is in; more technically, we assume that the information capabilities of reporters are formalized in a simple epistemic logic extension to the domain ontology that underlies the reporting system, and use reasoning to infer the appropriate additional data fields for which to query the reporter.","PeriodicalId":275036,"journal":{"name":"International Conference on Semantic Systems","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127437126","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":"Semantic mining on customer survey","authors":"Yang Yu, Jiangbo Dang","doi":"10.1145/2362499.2362510","DOIUrl":"https://doi.org/10.1145/2362499.2362510","url":null,"abstract":"Business intelligence aims to support better business decision-making. Customer survey is priceless asset for intelligent business decision-making. However, business analysts usually have to read hundreds of textual comments and tabular data in survey to manually dig out the necessary information to feed business intelligence models and tools. This paper introduces a business intelligence system to solve this problem by extensively utilizing Semantic Web technologies. Ontology based knowledge extraction is the key to extract interesting terms and understand the logic concept of them. All knowledge extracted forms a semantic knowledge base. Flexible user queries and intelligent analysis can be easily issued to the system over the semantic data store through standard protocol. Besides resolving problems in theory, we designed a flexible, intuitive user interaction interface to explain and present the analysis result for business analysts. Through the real usage of this system, it is validated that our system gives good solution for semantic mining on customer survey for business intelligence.","PeriodicalId":275036,"journal":{"name":"International Conference on Semantic Systems","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132825306","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}
T. D. Noia, R. Mirizzi, V. Ostuni, David Romito, M. Zanker
{"title":"Linked open data to support content-based recommender systems","authors":"T. D. Noia, R. Mirizzi, V. Ostuni, David Romito, M. Zanker","doi":"10.1145/2362499.2362501","DOIUrl":"https://doi.org/10.1145/2362499.2362501","url":null,"abstract":"The World Wide Web is moving from a Web of hyper-linked Documents to a Web of linked Data. Thanks to the Semantic Web spread and to the more recent Linked Open Data (LOD) initiative, a vast amount of RDF data have been published in freely accessible datasets. These datasets are connected with each other to form the so called Linked Open Data cloud. As of today, there are tons of RDF data available in the Web of Data, but only few applications really exploit their potential power. In this paper we show how these data can successfully be used to develop a recommender system (RS) that relies exclusively on the information encoded in the Web of Data. We implemented a content-based RS that leverages the data available within Linked Open Data datasets (in particular DBpedia, Freebase and LinkedMDB) in order to recommend movies to the end users. We extensively evaluated the approach and validated the effectiveness of the algorithms by experimentally measuring their accuracy with precision and recall metrics.","PeriodicalId":275036,"journal":{"name":"International Conference on Semantic Systems","volume":"06 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128274672","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":"terkait: semantic interactions with web content","authors":"Sebastian Germesin, Massimo Romanelli","doi":"10.1145/2362499.2362524","DOIUrl":"https://doi.org/10.1145/2362499.2362524","url":null,"abstract":"We present our ongoing development of an application, called terkait - that supports a user with related information while browsing the web. terkait analyses semantic objects that are either annotated directly in the content or retrieved by external services. The extracted entities are then preprocessed, filtered and finally presented to the user in a non-obtrusive user interface. The user can then choose to learn more about certain knowledge objects by browsing the related content that is presented alongside the particular entity. The architecture is implemented with clean and open APIs to allow different services to be used for both, the analyzing part as well as the querying for related content.","PeriodicalId":275036,"journal":{"name":"International Conference on Semantic Systems","volume":"207 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116109141","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 field application of LOD: LOD extraction from web and LOD search by sensor","authors":"Takahiro Kawamura, Akihiko Ohsuga","doi":"10.1145/2362499.2362530","DOIUrl":"https://doi.org/10.1145/2362499.2362530","url":null,"abstract":"Semantic search is intrinsically suited for information retrieval in field research, where keyword search is burdensome for users. Also, exploitation of mobile and facility sensors is now prevailing, but applications are still vague. Therefore, LOD can serve as an intermediary interpreting the semantics of the users and their environmental information obtained by the sensors and connecting it to the collective intelligence on the net. In this paper, to build ecosystem of LOD used in the field, we propose a mechanism of LOD content generation and its field application. Firstly, we introduce an Android application, which searches a plant fitting the environmental conditions obtained by the sensors from Plant LOD. Then, we show that our LOD generation mechanism builds the Plant LOD from the Web with an accuracy of 85 to 97%.","PeriodicalId":275036,"journal":{"name":"International Conference on Semantic Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128157954","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}
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