International Semantic Web Conference

Last updated
International Semantic Web Conference
AbbreviationISWC
Discipline Semantic Web
Publication details
Publisher Springer-Verlag
History2002-
Frequencyannual
no

The International Semantic Web Conference (ISWC) is a series of academic conferences and the premier international forum for the Semantic Web, Linked Data and Knowledge Graph Community. [1] [2] [3] Here, scientists, industry specialists, and practitioners meet to discuss the future of practical, scalable, user-friendly, and game changing solutions. [4] Its proceedings are published in the Lecture Notes in Computer Science by Springer-Verlag.

The annual ISWC conference series was established in 2002 by the Semantic Web Science Association (SWSA) after the success of the Semantic Web Working Symposium, a three-day conference held at Stanford University in the summer of 2001. SWSA continues to oversee the ISWC conference and choose organizers for future ISWC instances based on bids.

Overview

ISWC conferences
ConferenceDatePlaceProceedingsAwardsNotes
ISWC 2024 11-15 November Flag of the United States.svg Baltimore, USA, USALNCS vol. tbd
ISWC 2023 6-10 November Flag of Greece.svg Athens, Greece, Greece LNCS vol. 14265, LNCS vol. 14266 Best Research Track Paper Award Genivika Mann, Alishiba Dsouza, Ran Yu and Elena Demidova. “Spatial Link Prediction with Spatial and Semantic Embeddings”. Best Research Track Student Paper Award Alishiba Dsouza, Ran Yu, Moritz Windoffer and Elena Demidova. Iterative Geographic Entity Alignment with Cross-Attention.
ISWC 2022 23-27 October Flag of the People's Republic of China.svg Hangzhou, China, China LNCS vol. 13489 Best Paper: Efficient Dependency Analysis for Rule-Based Ontologies. Larry González, Alex Ivliev, Markus Krötzsch, Stephan Mennicke
ISWC 2021 24-28 October Flag of the United States.svg Albany, New York, USA LNCS vol. 12922 Best Paper: Improving Inductive Link Prediction Using Hyper-Relational Facts. Mehdi Ali, Max Berrendorf, Mikhail Galkin, Veronika Thost, Tengfei Ma, Volker Tresp, Jens Lehmann
ISWC 2020 2-6 November Flag of Greece.svg Athens, Greece, Greece LNCS vol. 12506, LNCS vol. 12507 Best Paper: Ronald Denaux, Jose Manuel Gomez-Perez: Linked Credibility Reviews for Explainable Misinformation Detection [5]

Best Student Paper: Timo Homburg, Steffen Staab, Daniel Janke: GeoSPARQL+: Syntax, Semantics and System for Integrated Querying of Graph, Raster and Vector Data [6]

ISWC 2019 26–30 October Flag of New Zealand.svg Auckland, New Zealand, New Zealand LNCS vol. 11778, LNCS vol.11779 Best Paper: Julien Corman, Fernando Florenzano, Juan L. Reutter and Ognjen Savkovic: Validating SHACL constraints over a SPARQL endpoint [7]

Best Student Paper: Hernan Vargas, Carlos Buil Aranda, Aidan Hogan and Claudia López: RDF Explorer: A Visual Query Builder for Semantic Web Knowledge Graphs [8] Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Azzurra Ragone and Joseph Trotta: How to make latent factors interpretable by feeding Factorization machines with knowledge graphs [9]

ISWC 2018 08-12 October Flag of the United States.svg Monterey, California, USA LNCS vol.11136, LNCS vol.11137 Best Paper: Sumit Bhatia, Purusharth Dwivedi and Avneet Kaur: That’s interesting, tell me more! Finding descriptive support passages for explaining knowledge graph relationships [10]

Best Student Paper: Jaime Salas and Aidan Hogan: Canonicalisation of monotone SPARQL queries [11]

ISWC 2017 21–25 October Flag of Austria.svg Vienna, Austria LNCS vol.10587, LNCS vol.10588 Best Paper: Olaf Hartig, Ian Letter and Jorge Pérez: A Formal Framework for Comparing Linked Data Fragments [12]

Best Student Paper: Stephan Baier, Volker Tresp and Yunpu Ma: Improving Visual Relationship Detection using Semantic Modeling of Scene Descriptions [13]

ISWC 2016 17-21 October Flag of Japan.svg Kobe, Japan LNCS vol.9981, LNCS vol.9982 Best Paper: Renzo Angles and Claudio Gutierrez: The multiset semantics of SPARQL patterns [14]

Linhong Zhu, Majid Ghasemi-Gol, Pedro Szekely, Aram Galstyan and Craig A. Knoblock: Unsupervised Entity Resolution on Multi-type Graphs [15]

Best Student Paper: Lei Zhang, Achim Rettinger, and Ji Zhang: A Probabilistic Model for Time-Aware Entity Recommendation [16]

ISWC 2015 11–15 October Flag of the United States.svg Bethlehem, Pennsylvania, USA LNCS vol.9366, LNCS vol.9367 Best Paper: L. Rietveld, W. Beek, and S. Schlobach: LOD Lab: Experiments at LOD Scale [17]

Best Student Paper: Y. Roussakis, I. Chrysakis, K. Stefanidis, G. Flouris, and Y. Starakas: A Flexible Framework for Understanding the Dynamics of Evolving RDF Datasets [18]

ISWC 2014 19–23 October Flag of Italy.svg Riva del Garda, Italy LNCS vol.8796, LNCS vol.8797 Best Paper: Ricardo Usbeck, Axel-Cyrille Ngonga Ngomo, Michael Röder, Daniel Gerber, Sandro Athaide Coelho, Sören Auer and Andreas Both: AGDISTIS - Graph-Based Disambiguation of Named Entities using Linked Data [19]

Best Student Paper: Juan F. Sequeda, Marcelo Arenas and Daniel P. Miranker: OBDA: Query Rewriting or Materialization? In Practice, Both! [20]

ISWC 2013 21–25 October Flag of Australia (converted).svg Sydney, Australia LNCS vol.8218, LNCS vol.8219 Best Paper: Carsten Lutz, Inanc Seylan, David Toman and Frank Wolter: The Combined Approach to OBDA: Taming Role Hierarchies using Filters. [21]

Best Student Paper: Jay Pujara, Hui Miao, Lise Getoor, William Cohen: Knowledge Graph Identification [22]

ISWC 2012 11–15 November Flag of the United States.svg Boston, USA LNCS vol. 7649, LNCS vol. 7650 Best Paper: Rahul Parundekar, Craig Knoblock and José Luis Ambite: Discovering Concept Coverings in Ontologies of Linked Data Sources [23]

Best Student Paper: Jean Christoph Jung and Carsten Lutz: Ontology-Based Access to Probabilistic Data with OWL QL [24]

ISWC 2011 23–27 October Flag of Germany.svg Bonn, Germany LNCS vol. 7031, LNCS vol. 7032 Best Paper: Mohamed Morsey, Jens Lehmann, Sören Auer and Axel-Cyrille Ngonga Ngomo: DBpedia SPARQL Benchmark Performance Assessment with Real Queries on Real Data [25]

Best Student Paper: Chiara Del Vescovo, Damian Gessler, Pavel Klinov, Bijan Parsia, Ulrike Sattler, Thomas Schneider and Andrew Winget: Decomposition and Modular Structure of BioPortal Ontologies [26]

ISWC 2010 7–11 November Flag of the People's Republic of China.svg Shanghai, China LNCS vol. 6496, LNCS vol. 6497 Best Paper: Shenghui Wang and Paul Groth: Measuring the dynamic bi-directional influence between content and social networks [27]

Best Student Paper: Heather S. Packer, Nicholas Gibbins and Nicholas R. Jennings: Forgetting Fragments from Evolving OWL Ontologies [28]

ISWC 2009 25–29 October Flag of the United States.svg Washington, DC, USA LNCS vol. 5823 Best Paper: Ugur Kuter and Jennifer Golbeck: Semantic Web Service Composition in Social Environments [29]

Best Student Paper: Vicky Papavassiliou, Giorgos Flouris, Irini Fundulaki, Dimitris Kotzinos, and Vassilis Christophides: On Detecting High-Level Changes in RDF/S KBs [30]

ISWC 2008 26-30, October Flag of Germany.svg Karlsruhe, Germany LNCS vol. 5318 Best Paper: Matthew Horridge, Bijan Parsia and Ulrike Sattler: Laconic and Precise Justifications in OWL [31]
ISWC 2007 11–15 November Flag of South Korea.svg Busan, South Korea LNCS vol. 4825 Best Paper: Dimitris Zeginis, Yannis Tzitzikas, and Vassilis Christophides: On the Foundations of Computing Deltas between RDF models [32]

Best Student Paper: Sean Falconer and Margaret-Anne Storey: A cognitive support framework for ontology mapping [33]

Held together with ASWC 2007.
ISWC 2006 Archived 2011-01-05 at the Wayback Machine 5–9 November Flag of the United States.svg Athens, Georgia, USA LNCS vol. 4273 Best Paper: Marcelo Arenas, Jorge Perez and Claudio Gutierrez: Semantics and Complexity of SPARQL [34]
ISWC 2005 Archived 2010-12-21 at the Wayback Machine 6–10 November Flag of Ireland.svg Galway, Ireland LNCS vol. 3729 Best Paper: Peter Mika: Ontologies are us: A unified model of social networks and semantics [35]
ISWC 2004 7–11 November Flag of Japan.svg Hiroshima, Japan LNCS vol. 3298 Best Paper: Y. Guo, Z. Pan, and J. Heflin: An Evaluation of Knowledge Base Systems for Large OWL Datasets [36]
ISWC 2003 20–23 October Flag of the United States.svg Sanibel Island, USA LNCS vol. 2870 Best Paper: Aimilia Magkanaraki, Val Tannen, Vassilis Christophides, Dimitris Plexousakis: Viewing the Semantic Web through RVL Lenses [37]
ISWC 2002 9–12 June Flag of Italy.svg Sardinia, Italy LNCS vol. 2342 Best Paper: Peter F. Patel-Schneider, Jérôme Siméon: Building the Semantic Web on XML [38]

Related Research Articles

<span class="mw-page-title-main">Semantic Web</span> Extension of the Web to facilitate data exchange

The Semantic Web, sometimes known as Web 3.0, is an extension of the World Wide Web through standards set by the World Wide Web Consortium (W3C). The goal of the Semantic Web is to make Internet data machine-readable.

In information science, an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the concepts, data, or entities that pertain to one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of terms and relational expressions that represent the entities in that subject area. The field which studies ontologies so conceived is sometimes referred to as applied ontology.

The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies. Ontologies are a formal way to describe taxonomies and classification networks, essentially defining the structure of knowledge for various domains: the nouns representing classes of objects and the verbs representing relations between the objects.

An annotation is extra information associated with a particular point in a document or other piece of information. It can be a note that includes a comment or explanation. Annotations are sometimes presented in the margin of book pages. For annotations of different digital media, see web annotation and text annotation.

Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between items is based on the likeness of their meaning or semantic content as opposed to lexicographical similarity. These are mathematical tools used to estimate the strength of the semantic relationship between units of language, concepts or instances, through a numerical description obtained according to the comparison of information supporting their meaning or describing their nature. The term semantic similarity is often confused with semantic relatedness. Semantic relatedness includes any relation between two terms, while semantic similarity only includes "is a" relations. For example, "car" is similar to "bus", but is also related to "road" and "driving".

Patrick John Hayes FAAAI is a British computer scientist who lives and works in the United States. As of March 2006, he is a senior research scientist at the Institute for Human and Machine Cognition in Pensacola, Florida.

An RDF query language is a computer language, specifically a query language for databases, able to retrieve and manipulate data stored in Resource Description Framework (RDF) format.

Ontotext is a software company that produces software relating to data management. Its main products are GraphDB, an RDF database; and Ontotext Platform, a general data management platform based on knowledge graphs. It was founded in 2000 in Bulgaria, and now has offices internationally. Together with the BBC, Ontotext developed one of the early large-scale industrial semantic applications, Dynamic Semantic Publishing, starting in 2010.

<span class="mw-page-title-main">Ian Horrocks</span> British academic (b.1958)

Ian Robert Horrocks is a professor of computer science at the University of Oxford in the UK and a Fellow of Oriel College, Oxford. His research focuses on knowledge representation and reasoning, particularly ontology languages, description logic and optimised tableaux decision procedures.

In the context of the Semantic Web, Ontology versioning is the process of formally distinguishing between different versions of vocabularies.

CICLing is an annual conference on computational linguistics (CL) and natural language processing (NLP). The first CICLing conference was held in 2000 in Mexico City. The conference is attended by one to two hundred of NLP and CL researchers and students every year. As of 2017, it is ranked within the top 20 sources on computational linguistics by Google Scholar. Past CICLing conferences have been held in Mexico, Korea, Israel, Romania, Japan, India, Greece, Nepal, Egypt, Turkey, Hungary, and Vietnam; the 2019 event was held in France.

Knowledge extraction is the creation of knowledge from structured and unstructured sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to information extraction (NLP) and ETL, the main criterion is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge or the generation of a schema based on the source data.

<span class="mw-page-title-main">Ulrike Sattler</span>

Ulrike M. Sattler is a professor of computer science in the information management group of the Department of Computer Science at the University of Manchester and a visiting professor at the University of Oslo.

GeoSPARQL is a standard for representation and querying of geospatial linked data for the Semantic Web from the Open Geospatial Consortium (OGC). The definition of a small ontology based on well-understood OGC standards is intended to provide a standardized exchange basis for geospatial RDF data which can support both qualitative and quantitative spatial reasoning and querying with the SPARQL database query language.

The Extended Semantic Web Conference, formerly known as the European Semantic Web Conference, is a yearly international academic conference on the topic of the Semantic Web. The event began in 2004, as the European Semantic Web Symposium. The goal of the event is "to bring together researchers and practitioners dealing with different aspects of semantics on the Web".

<span class="mw-page-title-main">UMBEL</span>

UMBEL is a logically organized knowledge graph of 34,000 concepts and entity types that can be used in information science for relating information from disparate sources to one another. It was retired at the end of 2019. UMBEL was first released in July 2008. Version 1.00 was released in February 2011. Its current release is version 1.50.

In natural language processing, linguistics, and neighboring fields, Linguistic Linked Open Data (LLOD) describes a method and an interdisciplinary community concerned with creating, sharing, and (re-)using language resources in accordance with Linked Data principles. The Linguistic Linked Open Data Cloud was conceived and is being maintained by the Open Linguistics Working Group (OWLG) of the Open Knowledge Foundation, but has been a point of focal activity for several W3C community groups, research projects, and infrastructure efforts since then.

A semantic triple, or RDF triple or simply triple, is the atomic data entity in the Resource Description Framework (RDF) data model. As its name indicates, a triple is a sequence of three entities that codifies a statement about semantic data in the form of subject–predicate–object expressions.

OntoLex is the short name of a vocabulary for lexical resources in the web of data (OntoLex-Lemon) and the short name of the W3C community group that created it.

<span class="mw-page-title-main">Knowledge graph</span> Type of knowledge base

In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics or relationships underlying these entities.

References

  1. ↑ Archived 2013-01-16 at archive.today : Rank 2 in WWW category.
  2. ↑ "Microsoft Academic". Archived from the original on 2013-01-04. Retrieved 2012-08-10.: Rank 4 in Database category.
  3. ↑ : Rank 2 in SW category.
  4. ↑ :ISWC2012 web site.
  5. ↑ Denaux, Ronald; Jose Manuel Gomez-Perez (2020). "Linked Credibility Reviews for Explainable Misinformation Detection". arXiv: 2008.12742 [cs.CL].
  6. ↑ Homburg, Timo; Staab, Steffen; Janke, Daniel (2020). "GeoSPARQL+: Syntax, Semantics and System for Integrated Querying of Graph, Raster and Vector Data". The Semantic Web – ISWC 2020 (PDF). Lecture Notes in Computer Science. Vol. 12506. pp. 258–275. doi:10.1007/978-3-030-62419-4_15. ISBN   978-3-030-62418-7. S2CID   221585985.
  7. ↑ Corman, Julien; Florenzano, Fernando; Reutter, Juan L.; Savković, Ognjen (2019). "Validating Shacl Constraints over a Sparql Endpoint". The Semantic Web – ISWC 2019. Lecture Notes in Computer Science. Vol. 11778. pp. 145–163. doi:10.1007/978-3-030-30793-6_9. ISBN   978-3-030-30792-9. S2CID   204754751.
  8. ↑ Vargas, Hernán; Buil-Aranda, Carlos; Hogan, Aidan; López, Claudia (2019). "RDF Explorer: A Visual SPARQL Query Builder". The Semantic Web – ISWC 2019. Lecture Notes in Computer Science. Vol. 11778. pp. 647–663. doi:10.1007/978-3-030-30793-6_37. ISBN   978-3-030-30792-9. S2CID   204754619.
  9. ↑ Anelli, Vito Walter; Di Noia, Tommaso; Di Sciascio, Eugenio; Ragone, Azzurra; Trotta, Joseph (2019). "How to Make Latent Factors Interpretable by Feeding Factorization Machines with Knowledge Graphs". The Semantic Web – ISWC 2019. Lecture Notes in Computer Science. Vol. 11778. pp. 38–56. arXiv: 1909.05038 . doi:10.1007/978-3-030-30793-6_3. ISBN   978-3-030-30792-9. S2CID   202558915.
  10. ↑ Bhatia, Sumit; Dwivedi, Purusharth; Kaur, Avneet (2018). "That's Interesting, Tell Me More! Finding Descriptive Support Passages for Knowledge Graph Relationships". The Semantic Web – ISWC 2018. Lecture Notes in Computer Science. Vol. 11136. pp. 250–267. doi:10.1007/978-3-030-00671-6_15. ISBN   978-3-030-00670-9.
  11. ↑ Salas, Jaime; Hogan, Aidan (2018). "Canonicalisation of Monotone SPARQL Queries". The Semantic Web – ISWC 2018. Lecture Notes in Computer Science. Vol. 11136. pp. 600–616. doi:10.1007/978-3-030-00671-6_35. ISBN   978-3-030-00670-9.
  12. ↑ Hartig, Olaf; Letter, Ian; Pérez, Jorge (2017). "A Formal Framework for Comparing Linked Data Fragments". The Semantic Web – ISWC 2017. Lecture Notes in Computer Science. Vol. 10587. pp. 364–382. doi:10.1007/978-3-319-68288-4_22. ISBN   978-3-319-68287-7.
  13. ↑ Baier, Stephan; Ma, Yunpu; Tresp, Volker (2017). "Improving Visual Relationship Detection Using Semantic Modeling of Scene Descriptions". The Semantic Web – ISWC 2017. Lecture Notes in Computer Science. Vol. 10587. pp. 53–68. arXiv: 1809.00204 . doi:10.1007/978-3-319-68288-4_4. ISBN   978-3-319-68287-7. S2CID   13865212.
  14. ↑ Angles, Renzo; Gutierrez, Claudio (2016). "The Multiset Semantics of SPARQL Patterns". The Semantic Web – ISWC 2016. Lecture Notes in Computer Science. Vol. 9981. pp. 20–36. arXiv: 1610.04315 . doi:10.1007/978-3-319-46523-4_2. ISBN   978-3-319-46522-7. S2CID   5260054.
  15. ↑ Zhu, Linhong; Ghasemi-Gol, Majid; Szekely, Pedro; Galstyan, Aram; Knoblock, Craig A. (2016). "Unsupervised Entity Resolution on Multi-type Graphs". The Semantic Web – ISWC 2016. Lecture Notes in Computer Science. Vol. 9981. pp. 649–667. doi:10.1007/978-3-319-46523-4_39. ISBN   978-3-319-46522-7.
  16. ↑ Zhang, Lei; Rettinger, Achim; Zhang, Ji (2016). "A Probabilistic Model for Time-Aware Entity Recommendation". The Semantic Web – ISWC 2016. Lecture Notes in Computer Science. Vol. 9981. pp. 598–614. doi:10.1007/978-3-319-46523-4_36. ISBN   978-3-319-46522-7.
  17. ↑ Rietveld, L. J.; Beek, W. G. J.; Schlobach, S. (2015). "LOD Lab: Experiments at LOD Scale (Compressed Contribution)".
  18. ↑ Roussakis, Yannis; Chrysakis, Ioannis; Stefanidis, Kostas; Flouris, Giorgos; Stavrakas, Yannis (2015). "A Flexible Framework for Understanding the Dynamics of Evolving RDF Datasets". The Semantic Web - ISWC 2015. Lecture Notes in Computer Science. Vol. 9366. pp. 495–512. doi:10.1007/978-3-319-25007-6_29. ISBN   978-3-319-25006-9.
  19. ↑ Usbeck, Ricardo; Ngonga Ngomo, Axel-Cyrille; Röder, Michael; Gerber, Daniel; Coelho, Sandro Athaide; Auer, Sören; Both, Andreas (2014). "AGDISTIS - Graph-Based Disambiguation of Named Entities Using Linked Data". The Semantic Web – ISWC 2014. Lecture Notes in Computer Science. Vol. 8796. pp. 457–471. doi:10.1007/978-3-319-11964-9_29. ISBN   978-3-319-11963-2. S2CID   14301767.
  20. ↑ Sequeda, Juan F.; Arenas, Marcelo; Miranker, Daniel P. (2014). "OBDA: Query Rewriting or Materialization? In Practice, Both!". The Semantic Web – ISWC 2014. Lecture Notes in Computer Science. Vol. 8796. pp. 535–551. doi:10.1007/978-3-319-11964-9_34. ISBN   978-3-319-11963-2.
  21. ↑ Lutz, Carsten; Seylan, İnanç; Toman, David; Wolter, Frank (2013). "The Combined Approach to OBDA: Taming Role Hierarchies Using Filters". Advanced Information Systems Engineering. Lecture Notes in Computer Science. Vol. 7908. pp. 314–330. doi:10.1007/978-3-642-41335-3_20. ISBN   978-3-642-38708-1.
  22. ↑ Pujara, Jay; Miao, Hui; Getoor, Lise; Cohen, William (2013). "Knowledge Graph Identification". Advanced Information Systems Engineering. Lecture Notes in Computer Science. Vol. 7908. pp. 542–557. doi:10.1007/978-3-642-41335-3_34. ISBN   978-3-642-38708-1. S2CID   11564235.
  23. ↑ Parundekar, Rahul; Knoblock, Craig A.; Ambite, José Luis (2012). "Discovering Concept Coverings in Ontologies of Linked Data Sources". The Semantic Web – ISWC 2012. Lecture Notes in Computer Science. Vol. 7649. pp. 427–443. doi:10.1007/978-3-642-35176-1_27. ISBN   978-3-642-35175-4.
  24. ↑ Jung, Jean Christoph; Lutz, Carsten (2012). "Ontology-Based Access to Probabilistic Data with OWL QL". The Semantic Web – ISWC 2012. Lecture Notes in Computer Science. Vol. 7649. pp. 182–197. doi:10.1007/978-3-642-35176-1_12. ISBN   978-3-642-35175-4.
  25. ↑ Morsey, Mohamed; Lehmann, Jens; Auer, Sören; Ngonga Ngomo, Axel-Cyrille (2011). "DBpedia SPARQL Benchmark – Performance Assessment with Real Queries on Real Data". The Semantic Web – ISWC 2011. Lecture Notes in Computer Science. Vol. 7031. pp. 454–469. doi:10.1007/978-3-642-25073-6_29. ISBN   978-3-642-25072-9.
  26. ↑ Del Vescovo, Chiara; Gessler, Damian D. G.; Klinov, Pavel; Parsia, Bijan; Sattler, Ulrike; Schneider, Thomas; Winget, Andrew (2011). "Decomposition and Modular Structure of Bio Portal Ontologies". The Semantic Web – ISWC 2011. Lecture Notes in Computer Science. Vol. 7031. pp. 130–145. doi:10.1007/978-3-642-25073-6_9. ISBN   978-3-642-25072-9.
  27. ↑ Wang, Shenghui; Groth, Paul (2010). "Measuring the Dynamic Bi-directional Influence between Content and Social Networks". The Semantic Web – ISWC 2010. Lecture Notes in Computer Science. Vol. 6496. pp. 814–829. doi:10.1007/978-3-642-17746-0_51. ISBN   978-3-642-17745-3.
  28. ↑ Packer, Heather S.; Gibbins, Nicholas; Jennings, Nicholas R. (2010). "Forgetting Fragments from Evolving Ontologies". The Semantic Web – ISWC 2010. Lecture Notes in Computer Science. Vol. 6496. pp. 582–597. doi:10.1007/978-3-642-17746-0_37. ISBN   978-3-642-17745-3.
  29. ↑ Kuter, Ugur; Golbeck, Jennifer (2009). "Semantic Web Service Composition in Social Environments". The Semantic Web - ISWC 2009. Lecture Notes in Computer Science. Vol. 5823. pp. 344–358. doi:10.1007/978-3-642-04930-9_22. ISBN   978-3-642-04929-3.
  30. ↑ Papavassiliou, Vicky; Flouris, Giorgos; Fundulaki, Irini; Kotzinos, Dimitris; Christophides, Vassilis (2009). "On Detecting High-Level Changes in RDF/S KBS". The Semantic Web - ISWC 2009. Lecture Notes in Computer Science. Vol. 5823. pp. 473–488. doi:10.1007/978-3-642-04930-9_30. ISBN   978-3-642-04929-3.
  31. ↑ Horridge, Matthew; Parsia, Bijan; Sattler, Ulrike (2008). "Laconic and Precise Justifications in OWL". The Semantic Web - ISWC 2008. Lecture Notes in Computer Science. Vol. 5318. pp. 323–338. doi:10.1007/978-3-540-88564-1_21. ISBN   978-3-540-88563-4.
  32. ↑ Zeginis, Dimitris; Tzitzikas, Yannis; Christophides, Vassilis (2007). "On the Foundations of Computing Deltas Between RDF Models". The Semantic Web. Lecture Notes in Computer Science. Vol. 4825. pp. 637–651. doi:10.1007/978-3-540-76298-0_46. ISBN   978-3-540-76297-3.
  33. ↑ Falconer, Sean M.; Storey, Margaret-Anne (2007). "A Cognitive Support Framework for Ontology Mapping". The Semantic Web. Lecture Notes in Computer Science. Vol. 4825. pp. 114–127. doi:10.1007/978-3-540-76298-0_9. ISBN   978-3-540-76297-3.
  34. ↑ Pérez, Jorge; Arenas, Marcelo; Gutierrez, Claudio (2006). "Semantics and Complexity of SPARQL". The Semantic Web - ISWC 2006. Lecture Notes in Computer Science. Vol. 4273. pp. 30–43. doi:10.1007/11926078_3. ISBN   978-3-540-49029-6.
  35. ↑ Mika, Peter (2005). "Ontologies Are Us: A Unified Model of Social Networks and Semantics". The Semantic Web – ISWC 2005. Lecture Notes in Computer Science. Vol. 3729. pp. 522–536. doi:10.1007/11574620_38. ISBN   978-3-540-29754-3.
  36. ↑ Guo, Yuanbo; Pan, Zhengxiang; Heflin, Jeff (2004). "An Evaluation of Knowledge Base Systems for Large OWL Datasets". The Semantic Web – ISWC 2004. Lecture Notes in Computer Science. Vol. 3298. pp. 274–288. doi:10.1007/978-3-540-30475-3_20. ISBN   978-3-540-23798-3.
  37. ↑ Magkanaraki, Aimilia; Tannen, Val; Christophides, Vassilis; Plexousakis, Dimitris (2003). "Viewing the Semantic Web through RVL Lenses". The Semantic Web - ISWC 2003. Lecture Notes in Computer Science. Vol. 2870. pp. 96–112. doi:10.1007/978-3-540-39718-2_7. ISBN   978-3-540-20362-9.
  38. ↑ Patel-Schneider, Peter F.; Siméon, Jérôme (2002). "Building the Semantic Web on XML". The Semantic Web — ISWC 2002. Lecture Notes in Computer Science. Vol. 2342. pp. 147–161. doi:10.1007/3-540-48005-6_13. ISBN   978-3-540-43760-4.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.