Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher Laura Po and Sonia Bergamaschi DII, University of Modena and Reggio Emilia, Italy March 2010 Hue City Vietnam

The idea When we are dealing with data sources, we are dealing with structure information that are labeled by humans. Humans use lexical expressions to assign names. Natural language labels provide a rich connection between formal objects (e.g. classes and properties) and their intended meanings. Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

Lexical knowledge inside sources It is necessary to address the problem of how the concepts are "labelled", i.e. understanding the meaning behind the names denoting ontology elements. In NLP (Natural Language Processing), Word Wense Disambiguation (WSD) is the process of identifying which sense of a word (i.e. meaning) is used in any given sentence, when the word has a number of distinct senses (polysemy). Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

Lexical knowledge inside sources It is necessary to address the problem of how the concepts are "labelled", i.e. understanding the meaning behind the names denoting ontology elements. sentence In NLP (Natural Language Processing), Word Wense Disambiguation (WSD) is the process of identifying which sense of a word (i.e. meaning) is used in any given sentence, when the word has a number of distinct senses (polysemy). Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

Applications of WSD Information Retrieval Information Extraction Machine Translation Content Analysis Word Processing Lexicography The Semantic Web ◦ ontology learning: to build domain taxonomies and enrich large-scale semantic networks Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010 Roberto Navigli. Word Sense Disambiguation: A Survey, ACM Computing Surveys, 41(2), 2009Word Sense Disambiguation: A Survey

Lexical Annotation Lexical Annotation is a particular metadata annotation that refers to a semantic resource. Each lexical annotation has the property to own one or more lexical descriptions. Lexical Annotation ◦ assigns meanings to class and property names w.r.t. a semantic resource (WordNet) ◦ derives relationships among source elements Lexical Annotation can be an effective method to solve ambiguity problems! Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

Lexical Annotation – an example Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010 Hypernym of BookSYNVolume Book BTCatalog (Catalog  Book) lexical relationships extracted √ √√ √ BT

The ontology matching problem An ontology is an explicit specification of a conceptualization (Gruber, 1993). The ontology matching process, for two separate and autonomous ontologies, O1 and O2, consists of finding corresponding entities in ontologies O1 and O2 Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

Ontology matchers Several ontology matchers have been proposed in litterature, altought the most do not take advantage of the linguistic aspect of the involved ontologies. different meanings In particular, ontology matchers do not discern elements with different meanings. Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

The SCARLET matcher Scarlet* is a technique for discovering relationships between two concepts by making use of online available ontologies. Scarlet discovers semantic relationships between concepts by exploiting the entire Semantic Web as a source of background knowledge. Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010 * SCARLET has been developed by the Knowledge and Media Institute at Milton Keynes, UK.

The SCARLET matcher By using semantic search engines (Swoogle and WATSON), it finds online ontologies containing concepts with the same names as the candidate concepts and then it derives mappings from the relationships in the online ontologies. Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010 Ontology 1Ontology 2 Online Ontology BA A0A0 B0B0   Legenda anchoring relationship

The SCARLET matcher Scarlet is able to identify disjoint relations, subsumption relations, and correspondences. All relations are obtained by using derivation rules which explore direct relations and also relations deduced by applying subsumption reasoning. Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010 Ontology 1Ontology 2 Online Ontologies BA A0A0  B0B0  C C0C0  Legenda anchoring relationship

The evaluation of SCARLET On a large-scale, real life data sets SCARLET retrived a precision value of 70% More than half of incorrect anchonring were due to ambiguities. SCARLET is not able to take advantage of the ontological context in which a concept appears. Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010 Lexical Annotation can used to solve the ambiguity problems!

SCARLET + lexical annotation By identifying a meaning (or a set of meanings) for each concept it is possible to, more accurately, compare the concept with the concepts that appear in online ontologies. Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

How Lexical Annotation enhances the ontology matching performance Performing lexical annotation on the ontologies involved in the matching process allows: ◦ to detect false positive mappings ◦ to discover new mappings ◦ to identify synonyms and more general classes for a given concept Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010 Improving precision Improving recall

Lexical annotation improvements 1 - detection of false positive mappings Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010 Ontology 1Ontology 2 BA A0A0 B0B0   SYNSET 4 SYNSET 3 SYNSET 2 SYNSET 1 X X If a concept and its anchoring concept have disregarding meanings (i.e. if they do not have the same list of meanings), the anchoring is detect as a false positive.

Lexical annotation improvements 1- detection of false positive mappings Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010 Ontology 1 BA A0A0  B0B0  C C0C0  Ontology 2 SYNSET 4 SYNSET 3 SYNSET 2 SYNSET 1 X X

Lexical annotation improvements 2 - new mapping discovery Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010 Ontology 1Ontology 2 BA  SYNSET 4 SYNSET 3 SYNSET 2 SYNSET 1 hyponym

Lexical annotation improvements 3 - identification of synonyms and more general concepts Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010 Ontology 1Ontology 2 B home house B0B0   SYNSET 4 SYNSET 3 SYNSET 2 SYNSET 1 New anchoring

ALA tool We employ the Automatic Lexical Annotation tool to perform lexical annotation of the ontologies involved in the matching process (source ontologies, online ontologies). ALA combines the output of 4 WSD algorithms and 2 heuristic rules. The combination is a sequential composition: ◦ only the first algorithm is executed on the entire data source, the following algorithms are executed only on the set of concepts that were not disambiguated by the previous ones. Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

Lexical Annotation Evaluation The application of lexical annotation techniques on the SCARLET results has been tested on two test cases: ◦ NALT+AGROVOC two real life thesauri: the United Nations Food and Agriculture Organization (FAO)’s AGROVOC thesaurus, the United States National Agricultural Library (NAL) Agricultural thesaurus NALT ◦ OAEI 2006 benchmark The benchmark is bibliographic domain, the bibliographic ontologies we took into account are the reference ontology and the Karlsruhe ontology. Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

Lexical Annotation Evaluation: detection of incorrect anchoring The results of the automatic lexical annotation have been compared with the manual evaluation done by an expert on the entire set of matching. Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010 the most are due to the presence of compound nouns

Lexical Annotation Evaluation: new mapping discovery After the execution of lexical annotation, we computed a mapping between two concepts, if we find a relationship between their corresponding meanings in WordNet. Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

Lexical Annotation Evaluation: comparison We compared our results with a multiontology disambiguation method that has been previously applied on SCARLET Unlike multiontology disambiguation method that retrieves similarity measures, our method offers a definite answer regarding the detection of synonym relationships. Comparing the results, we evaluated some possible thresholds on the similarity measures retrieved by the multiontolgy disambiguation method (0.19 – 0.22). Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

Conclusion We proposed and experimentally investigated a method to solve ambiguity problems in the context of ontology matching by using automatic lexical annotation techniques (ALA tool). The method has been applied on SCARLET, a semantic web based matcher. Experimental results have proved that by performing lexical annotation of ontologies we are able to: ◦ to detect false positive mappings ◦ to discover new mappings Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

Future work on lex ann + matchers Lexical Annotation is able to identify synonymous and generalization of concepts. Implementing this will give the matcher the possibility to widen the search among online ontologies, thus, improving matching results. In order to cope with more complex ontologies, our method needs to be extended by including the treatment of compound terms and abbreviations (published at ER2009). The method could be coped with any matcher. Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

Future perspectives There are several scenarios where we applied lexical annotation ◦ Data integration ◦ Ontology matching ◦ Disambiguation/classification of Google hits New scenarios ◦ blogs ◦ social networks ◦ Mash up ?! Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po ACIIDS - 26/03/2010

Thanks for your attention! ACIIDS - 26/03/2010Automatic Lexical Annotation Applied to the SCARLET Ontology Matcher - Laura Po