Lemonia Giantsiou, Alex Simov, Nikos Loutas, Vassilios Peristeras, K. Tarabanis
{"title":"The WSMO-PA Service Editor","authors":"Lemonia Giantsiou, Alex Simov, Nikos Loutas, Vassilios Peristeras, K. Tarabanis","doi":"10.1109/ICSC.2008.22","DOIUrl":"https://doi.org/10.1109/ICSC.2008.22","url":null,"abstract":"Semantic Web Service (SWS) editors did not support until now the expression of domain specific semantics. On the other hand, the adoption of SWSs in different domains, i.e. eGovernment, eBusiness, has created the need for enhancing SWS descriptions with domain specific semantics. Therefore, models and tools that allow this integration have to be developed. The WSMO-PA Service Editor is an effort made towards this direction. It provides a friendly user interface which facilitates the creation of semantically-enhanced descriptions for Public Administration (PA) services. To do so, the WSMO-PA Service Editor combines the GEA PA Service Model, the WSMO Framework and the WSMO-PA specification.","PeriodicalId":102805,"journal":{"name":"2008 IEEE International Conference on Semantic Computing","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126744075","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":"Mobile Mashups: Thoughts, Directions, and Challenges","authors":"E. M. Maximilien","doi":"10.1109/ICSC.2008.100","DOIUrl":"https://doi.org/10.1109/ICSC.2008.100","url":null,"abstract":"The twin mainstream computing shifts of mobility and programable Web are fundamentally impacting how humans interact, socialize, and accessinformation. Never before has computing been so disruptive and important in our daily activities. With such profound change looming what are the challengeswe still face and the challenges that we will increasingly have to deal with to make these coming changes as smooth and useful as possible?","PeriodicalId":102805,"journal":{"name":"2008 IEEE International Conference on Semantic Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129562466","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":"Discovering Entities Relationships on the Web","authors":"Wei Yu, Junpeng Chen, Guoying Yu","doi":"10.1109/ICSC.2008.16","DOIUrl":"https://doi.org/10.1109/ICSC.2008.16","url":null,"abstract":"Mining entities relationships on the Web is a crucial problem for many data analysis work. We propose a new method to discover the relationships between two entities on the Web and designed an entities relationships miner prototype ERM, where the relationships can be mined in different granularities and the related Web pages containing the connections between two entities are returned in ranked order. Our experimental results show that ERM provides an efficient yet effective way for the user to discover the entities relationships on the Web.","PeriodicalId":102805,"journal":{"name":"2008 IEEE International Conference on Semantic Computing","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124956783","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}
Miriam Fernández, V. López, M. Sabou, V. Uren, D. Vallet, E. Motta, P. Castells
{"title":"Semantic Search Meets the Web","authors":"Miriam Fernández, V. López, M. Sabou, V. Uren, D. Vallet, E. Motta, P. Castells","doi":"10.1109/ICSC.2008.52","DOIUrl":"https://doi.org/10.1109/ICSC.2008.52","url":null,"abstract":"While semantic search technologies have been proven to work well in specific domains, they still have to confront two main challenges to scale up to the Web in its entirety. In this work we address this issue with a novel semantic search system that a) provides the user with the capability to query Semantic Web information using natural language, by means of an ontology-based Question Answering (QA) system [14] and b) complements the specific answers retrieved during the QA process with a ranked list of documents from the Web [3]. Our results show that ontology-based semantic search capabilities can be used to complement and enhance keyword search technologies.","PeriodicalId":102805,"journal":{"name":"2008 IEEE International Conference on Semantic Computing","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133460812","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}
M. Hartmann, Torsten Zesch, M. Mühlhäuser, Iryna Gurevych
{"title":"Using Similarity Measures for Context-Aware User Interfaces","authors":"M. Hartmann, Torsten Zesch, M. Mühlhäuser, Iryna Gurevych","doi":"10.1109/icsc.2008.94","DOIUrl":"https://doi.org/10.1109/icsc.2008.94","url":null,"abstract":"Context-aware user interfaces facilitate the user interaction by suggesting or prefilling data derived from the userpsilas current context. This raises the problem of mapping context information to input elements in the user interface. We address this problem for web applications by (i) automatically extracting a textual representation of their input elements, and by (ii) mapping context information to them using these textual representations. In this paper, we present an approach for the representation extraction task that outperforms existing ones, and we explore the potential of similarity measures for the context mapping task.","PeriodicalId":102805,"journal":{"name":"2008 IEEE International Conference on Semantic Computing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114882630","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}
D. Fensel, F. V. Harmelen, Bosse Andersson, P. Brennan, H. Cunningham, Emanuele Della Valle, F. Fischer, Zhisheng Huang, A. Kiryakov, T. Lee, L. Schooler, Volker Tresp, S. Wesner, M. Witbrock, N. Zhong
{"title":"Towards LarKC: A Platform for Web-Scale Reasoning","authors":"D. Fensel, F. V. Harmelen, Bosse Andersson, P. Brennan, H. Cunningham, Emanuele Della Valle, F. Fischer, Zhisheng Huang, A. Kiryakov, T. Lee, L. Schooler, Volker Tresp, S. Wesner, M. Witbrock, N. Zhong","doi":"10.1109/ICSC.2008.41","DOIUrl":"https://doi.org/10.1109/ICSC.2008.41","url":null,"abstract":"Current semantic Web reasoning systems do not scale to the requirements of their hottest applications, such as analyzing data from millions of mobile devices, dealing with terabytes of scientific data, and content management in enterprises with thousands of knowledge workers. In this paper, we present our plan of building the large knowledge collider, a platform for massive distributed incomplete reasoning that will remove these scalability barriers. This is achieved by (i) enriching the current logic-based semantic Web reasoning methods, (ii) employing cognitively inspired approaches and techniques, and (iii) building a distributed reasoning platform and realizing it both on a high-performance computing cluster and via \"computing at home\". In this paper, we will discuss how the technologies of LarKC would move beyond the state-of-the-art of Web scale reasoning.","PeriodicalId":102805,"journal":{"name":"2008 IEEE International Conference on Semantic Computing","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127309487","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":"Efficient Selection and Integration of Data Sources for Answering Semantic Web Queries","authors":"A. Qasem, Dimitre A. Dimitrov, J. Heflin","doi":"10.1109/ICSC.2008.31","DOIUrl":"https://doi.org/10.1109/ICSC.2008.31","url":null,"abstract":"In this work we adapt an efficient information integration algorithm to identify the minimal set of potentially relevant Semantic Web data sources for a given query. The vast majority of these sources are files written in RDF or OWL format, and must be processed in their entirety. Our adaptation includes enhancing the algorithm with taxonomic reasoning, defining and using a mapping language for the purpose of aligning heterogeneous Semantic Web ontologies, and introducing a concept of source relevance to reduce the number of sources that we need to consider for a given query. After the source selection process, we load the selected sources into a Semantic Web reasoner to get a sound and complete answer to the query. We have conducted an experiment using synthetic ontologies and data sources which demonstrates that our system performs well over a wide range of queries. A typical response time for a substantial work load of 50 domain ontologies, 80 map ontologies and 500 data sources is less than 2 seconds. Furthermore,our system returned correct answers to 200 randomly generated queries in several workload configurations. We have also compared our adaptation with a basic implementation of the original information integration algorithm that does not do any taxonomic reasoning. In the most complex configuration with 50 domain ontologies, 100 map ontologies and 1000 data sources our system returns complete answers to all the queries whereas the basic implementation returns complete answers to only 28% of the queries.","PeriodicalId":102805,"journal":{"name":"2008 IEEE International Conference on Semantic Computing","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127758257","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}