Publications

Semantic Annotation of Quantitative Textual Content

Mehrnaz Ghashghaei and John Cuzzola and Ebrahim Bagheri and Ali A. Ghorbani
Reference:
Links to Publication: [www]
Abstract:
Semantic annotation techniques provide the basis for linking textual content with concepts in well grounded knowledge bases. In spite of their many application areas, current semantic annotation systems have some limitations. One of the prominent limitations of such systems is that none of the existing semantic annotator systems are able to identify and disambiguate quantitative (numerical) content. In textual documents such as Web pages, specially technical contents, there are many quantitative information such as product specifications that need to be semantically qualified. In this paper, we propose an approach for annotating quantitative values in short textual content. In our approach, we identify numeric values in the text and link them to an existing property in a knowledge base. Based on this mapping, we are then able to find the concept that the property is associated with; whereby, identifying both the concept and the specific property of that concept that the numeric value belongs to. Our experiments show that our proposed approach is able to reach an accuracy of over 70% for semantically annotating quantitative content.
Bibtex Entry:
@inproceedings{DBLP:conf/semweb/GhashghaeiCBG15, author = {Mehrnaz Ghashghaei and John Cuzzola and Ebrahim Bagheri and Ali A. Ghorbani}, title = {Semantic Annotation of Quantitative Textual Content}, booktitle = {Proceedings of the Third International Workshop on Linked Data for Information Extraction {(LD4IE2015)} co-located with the 14th International Semantic Web Conference {(ISWC} 2015), Bethlehem, Pennsylvania, USA, October 12, 2015.}, pages = {20--33}, year = {2015}, crossref = {DBLP:conf/semweb/2015ld4ie}, url = {http://ceur-ws.org/Vol-1467/LD4IE2015_Ghashghaei.pdf}, timestamp = {Mon, 30 May 2016 16:28:37 +0200}, biburl = {http://dblp.uni-trier.de/rec/bib/conf/semweb/GhashghaeiCBG15}, bibsource = {dblp computer science bibliography, http://dblp.org} abstract ={Semantic annotation techniques provide the basis for linking textual content with concepts in well grounded knowledge bases. In spite of their many application areas, current semantic annotation systems have some limitations. One of the prominent limitations of such systems is that none of the existing semantic annotator systems are able to identify and disambiguate quantitative (numerical) content. In textual documents such as Web pages, specially technical contents, there are many quantitative information such as product specifications that need to be semantically qualified. In this paper, we propose an approach for annotating quantitative values in short textual content. In our approach, we identify numeric values in the text and link them to an existing property in a knowledge base. Based on this mapping, we are then able to find the concept that the property is associated with; whereby, identifying both the concept and the specific property of that concept that the numeric value belongs to. Our experiments show that our proposed approach is able to reach an accuracy of over 70\% for semantically annotating quantitative content. } }




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