TY - CHAP T1 - Alignment-based querying of linked open data T2 - On the Move to Meaningful Internet Systems: OTM 2012 Y1 - 2012 A1 - Joshi, Amit Krishna A1 - Prateek Jain A1 - Pascal Hitzler A1 - Peter Z. Yeh A1 - Kunal Verma A1 - Amit Sheth A1 - Mariana Damova JF - On the Move to Meaningful Internet Systems: OTM 2012 PB - Springer ER - TY - CONF T1 - Moving beyond SameAs with PLATO: Partonomy detection for Linked Data T2 - 23rd ACM Conference on Hypertext and Social Media, HT '12 Y1 - 2012 A1 - Prateek Jain A1 - Pascal Hitzler A1 - Kunal Verma A1 - Peter Z. Yeh A1 - Amit Sheth ED - Ethan V. Munson ED - Markus Strohmaier KW - Linked Open Data Cloud KW - Mereology KW - Part of Relation AB -

The Linked Open Data (LOD) Cloud has gained significant traction over the past few years. With over 275 interlinked datasets across diverse domains such as life science, geography, politics, and more, the LOD Cloud has the potential to support a variety of applications ranging from open domain question answering to drug discovery.

Despite its significant size (approx. 30 billion triples), the data is relatively sparely interlinked (approx. 400 million links). A semantically richer LOD Cloud is needed to fully realize its potential. Data in the LOD Cloud are currently interlinked mainly via the owl:sameAs property, which is inadequate for many applications. Additional properties capturing relations based on causality or partonomy are needed to enable the answering of complex questions and to support applications.

In this paper, we present a solution to enrich the LOD Cloud by automatically detecting partonomic relationships, which are well-established, fundamental properties grounded in linguistics and philosophy. We empirically evaluate our solution across several domains, and show that our approach performs well on detecting partonomic properties between LOD Cloud data.

JF - 23rd ACM Conference on Hypertext and Social Media, HT '12 PB - ACM CY - Milwaukee, WI, USA UR - http://doi.acm.org/10.1145/2309996.2310004 ER - TY - CONF T1 - Contextual Ontology Alignment of LOD with an Upper Ontology: A Case Study with Proton T2 - The Semantic Web: Research and Applications - 8th Extended Semantic Web Conference, ESWC 2011 Y1 - 2011 A1 - Prateek Jain A1 - Peter Z. Yeh A1 - Kunal Verma A1 - Reymonrod G. Vasquez A1 - Mariana Damova A1 - Pascal Hitzler A1 - Amit Sheth ED - Grigoris Antoniou ED - Marko Grobelnik ED - Elena Paslaru Bontas Simperl ED - Bijan Parsia ED - Dimitris Plexousakis ED - Pieter De Leenheer ED - Jeff Z. Pan AB -

The Linked Open Data (LOD) is a major milestone towards realizing the Semantic Web vision, and can enable applications such as robust Question Answering (QA) systems that can answer queries requiring multiple, disparate information sources. However, realizing these applications requires relationships at both the schema and instance level, but currently the LOD only provides relationships for the latter. To address this limitation, we present a solution for automatically finding schema-level links between two LOD ontologies – in the sense of ontology alignment. Our solution, called BLOOMS+, extends our previous solution (i.e. BLOOMS) in two significant ways. BLOOMS+ 1) uses a more sophisticated metric to determine which classes between two ontologies to align, and 2) considers contextual information to further support (or reject) an alignment. We present a comprehensive evaluation of our solution using schema-level mappings from LOD ontologies to Proton (an upper level ontology) – created manually by human experts for a real world application called FactForge. We show that our solution performed well on this task. We also show that our solution significantly outperformed existing ontology alignment solutions (including our previously published work on BLOOMS) on this same task.

JF - The Semantic Web: Research and Applications - 8th Extended Semantic Web Conference, ESWC 2011 PB - Springer CY - Heraklion, Crete, Greece VL - 6643 UR - http://dx.doi.org/10.1007/978-3-642-21034-1_6 ER - TY - CONF T1 - Linked Data Is Merely More Data T2 - Linked Data Meets Artificial Intelligence, Papers from the 2010 AAAI Spring Symposium Y1 - 2010 A1 - Prateek Jain A1 - Pascal Hitzler A1 - Peter Z. Yeh A1 - Kunal Verma A1 - Amit Sheth ED - Dan Brickley ED - Vinay K. Chaudhri ED - Harry Halpin ED - Deborah McGuinness AB -

In this position paper, we argue that the Linked Open Data (LoD) Cloud, in its current form, is only of limited value for furthering the Semantic Web vision. Being merely a weakly linked “triple collection,” it will only be of very limited bene- fit for the AI or Semantic Web communities. We describe the corresponding problems with the LoD Cloud and give directions for research to remedy the situation.

JF - Linked Data Meets Artificial Intelligence, Papers from the 2010 AAAI Spring Symposium PB - AAAI CY - Stanford, California, USA UR - http://www.aaai.org/ocs/index.php/SSS/SSS10/paper/view/1130 ER - TY - CONF T1 - Ontology Alignment for Linked Open Data T2 - The Semantic Web - ISWC 2010 - 9th International Semantic Web Conference, ISWC 2010 Y1 - 2010 A1 - Prateek Jain A1 - Pascal Hitzler A1 - Amit Sheth A1 - Kunal Verma A1 - Peter Z. Yeh ED - Peter F. Patel-Schneider ED - Yue Pan ED - Pascal Hitzler ED - Peter Mika ED - Lei Zhang ED - Jeff Z. Pan ED - Ian Horrocks ED - Birte Glimm AB -

The Web of Data currently coming into existence through the Linked Open Data (LOD) effort is a major milestone in realizing the Semantic Web vision. However, the development of applications based on LOD faces difficulties due to the fact that the different LOD datasets are rather loosely connected pieces of information. In particular, links between LOD datasets are almost exclusively on the level of instances, and schema-level information is being ignored. In this paper, we therefore present a system for finding schema-level links between LOD datasets in the sense of ontology alignment. Our system, called BLOOMS, is based on the idea of bootstrapping information already present on the LOD cloud. We also present a comprehensive evaluation which shows that BLOOMS outperforms state-of-the-art ontology alignment systems on LOD datasets. At the same time, BLOOMS is also competitive compared with these other systems on the Ontology Evaluation Alignment Initiative Benchmark datasets.

JF - The Semantic Web - ISWC 2010 - 9th International Semantic Web Conference, ISWC 2010 PB - Springer CY - Shanghai, China VL - 6496 UR - http://dx.doi.org/10.1007/978-3-642-17746-0_26 ER -