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BLOOMS is an ontology alignment system based on the idea of bootstrapping information already present on the LOD cloud. It was developed particularly for Linked Open Data schema alignment.

To obtain more information about BLOOMS, please have a look at our papers Ontology Alignment for Linked Open Data. (Full research paper at ISWC2010:<ref name=blooms-iswc10>Prateek Jain, Pascal Hitzler, Amit P. Sheth, Kunal Verma, Peter Z. Yeh, Ontology Alignment for Linked Open Data. In: P. Patel-Schneider, Y. Pan, P. Hitzler, P. Mika, L. Zhang, J. Pan, I. Horrocks, B. Glimm (eds.), The Semantic Web - ISWC 2010. 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part I. Lecture Notes in Computer Science Vol. 6496. Springer, Berlin, 2010, pp. 401-416.)</ref>), Contextual Ontology Alignment of LOD with an Upper Ontology: A Case Study with Proton (Full research paper at ESWC2011:<ref name=blooms-eswc11>Prateek Jain,Peter Z. Yeh, Kunal Verma, Reymonrod Vasquez, Mariana Damova, Pascal Hitzler and Amit P. Sheth, Contextual Ontology Alignment of LOD with an Upper Ontology: A Case Study with Proton.In Grigoris Antoniou, Marko Grobelnik, Elena Simperl, Bijan Parsia, Dimitris Plexousakis, Jeff Pan and Pieter De Leenheer, editors, Proceedings of the 8th Extended Semantic Web Conference 2011, volume 6643 of Lecture Notes in Computer Science, Heidelberg, 2011. Springer Berlin. (Acceptance Rate 23.5%)</ref>), Flexible Bootstrapping-Based Ontology Alignment (poster in Ontology Matching Workshop 2010) <ref name=om2010>Prateek Jain, Pascal Hitzler and Amit P. Sheth. Flexible Bootstrapping-Based Ontology Alignment. In Proceedings of the Fifth international Workshop on Ontology Matching (Shanghai, China, November 7th - 11th, 2010). </ref> and paper in Workshop on Working with Multiple Biomedical Ontologies, at ICBO 2011 <ref name=icbo-wombo11>Colin Puri, Karthik Gomadam, Prateek Jain, Peter Z. Yeh, Kunal Verma, Multiple Ontologies in Healthcare Information Technology: Motivations and Recommendation for Ontology Mapping and Alignment.In Proceedings of the Workshop on Working with Multiple Biomedical Ontologies (at ICBO), 26 July 2011, Buffalo, NY, USA. </ref>

BLOOMS is an acronym for Bootstrapping-based Linked Open Data Ontology Matching System.


BLOOMS bootstrapping approach utilizes the Wikipedia category hierarchy for aligning ontologies. BLOOMS constructs a forest (i.e., a set of trees) TC (known as BLOOMS forest for C) for each matching candidate class name C, which roughly corresponds to a selection of supercategories of the class name. Comparison of the forests TC and TB for matching candidate classes C and B then yields a decision whether or not (and with which of the candidate relations) C and B should be aligned.


We performed a comprehensive evaluation of BLOOMS using third party datasets and other state-of-the-art systems in ontology matching. More specifically, BLOOMS has been evaluated in two different ways.

  • We examined the ability of BLOOMS to serve as a general purpose ontology matching system, by comparing it with other systems on the Ontology Alignment Evaluation Initiative (OAEI) benchmarks.
  • Secondly, we evaluated BLOOMS for the purpose of LOD schema integration and compared it with other systems for ontology matching on LOD schema alignment.

For both the evaluations BLOOMS has been compared with the state of the art tools in ontology mapping.

Systems for Comparison

  • RiMOM: RiMOM was the top system in the oriented track of OAEI in terms of f-measure and availability for download.
  • AROMA: AROMA ranked second in the 2008 OAEI Benchmark event.
  • OMViaUO <ref name=omviauo-2009>Mascardi, V., Locoro, A., and Rosso, P. 2010. Automatic Ontology Matching via Upper Ontologies: A Systematic Evaluation. IEEE Trans. on Knowl. and Data Eng. 22, 5 (May. 2010), 609-623. DOI=</ref>: OMViaUO utilizes upper level ontologies such as SUMO and DOLCE as semantic bridges in the ontology matching process.
  • S-Match: S-Match approach utilizes the semantic information implicitly or explicitly codified in the labels of nodes and arc for computing the semantic correspondences.
  • Alignment-API: Alignment API provides a framework for expressing and sharing ontology alignments. Please note we utilized wordnet based method of Alignment API for matching. Alignment API should be considered as a straw man approach for the purpose of this evaluation.

Comparison Ontology Alignment Evaluation Initiative Oriented Track

Results Ontology Alignment Initiative Oriented Matching Track

Test Prec Rec Prec Rec Prec Rec Prec Rec Prec Rec Prec Rec
1XX 0 0 0.04 0.06 0.01 0.71 NaN 0 1 1 1 1
4XX 0 0 0.01 0.03 0.05 0.30 0.84 0.08 0.67 0.85 0.54 0.51
3XX 0.01 0.03 0.04 0.047 0.01 0.14 0.74 0.11 0.59 0.81 1 0.84
Avg. 0.00 0.01 0.04 0.04 0.03 0.38 0.63 0.07 0.75 0.88 0.84 0.78

Comparison Ontology Alignment Evaluation Initiative Benchmark Track

Results Ontology Alignment Initiative Benchmark Track

Test Prec Rec Prec Rec Prec Rec Prec Rec Prec Rec Prec Rec
1XX 0.11 1 0.26 0.37 0.59 0.96 0.71 1 1 1 1 1
4XX 0.1 0.2 0.21 0.31 0.3 0.54 0.38 0.49 0.88 0.65 0.89 0.78
3XX 0.1 0.2 0.28 0.28 0.45 0.77 0.62 0.84 0.80 0.76 0.80 0.80
Avg. 0.1 0.46 0.25 0.33 0.45 0.76 0.57 0.78 0.88 0.81 0.89 0.66

Comparison Linked Open Data schema Alignment

Test Prec Rec Prec Rec Prec Rec Prec Rec Prec Rec Prec Rec
Music Ontology, BBC Program 0.4 0 1 0 err err 0.04 0.28 0 0 0.63 0.78
Music Ontology, DBpedia 0 0 0 0 err err 0.08 0.30 0.45 0.01 0.39 0.62
FOAF, DBpedia 0 0 0 0 err err 0.11 0.40 0.33 0.04 0.67 0.73
Geonames, DBpedia 0 0 0 0 err err 0.23 1 0 0 0 0
SIOC, FOAF 0 0 0 0 0.3 0.2 0.52 0.11 0.30 0.20 0.55 0.64
Semantic Web Conf. Ontology, AKT Portal Ontology 0.12 0.05 0.16 0.03 err err 0.06 0.4 0.38 0.03 0.42 0.59
Semantic Web Conf. Ontology, DBpedia 0 0 0 0 err err 0.15 0.50 0.27 0.01 0.70 0.40
Avg. 0.07 0.01 0.17 0 NA NA 0.17 0.43 0.25 0.04 0.48 0.54

The selection of parameters for A-API, OMViaUO and AROMA hardly make any difference on this dataset, as this data shows.




This work is funded primarily by NSF Award:IIS-0842129, titled III-SGER: Spatio-Temporal-Thematic Queries of Semantic Web Data: a Study of Expressivity and Efficiency. Pascal Hitzler acknowledges support by the Wright State University Research Council. Thanks to Jacob Saunders for developing the GUI of BLOOMS framework.