TY - CONF T1 - TOSS: an extension of TAX with ontologies and similarity queries T2 - Proceedings of the 2004 ACM SIGMOD international conference on Management of data Y1 - 2004 A1 - Hung,Edward A1 - Deng,Yu A1 - V.S. Subrahmanian KW - ontologies KW - semantic integration of heterogeneous data KW - similarity enhancement KW - XML databases AB - TAX is perhaps the best known extension of the relational algebra to handle queries to XML databases. One problem with TAX (as with many existing relational DBMSs) is that the semantics of terms in a TAX DB are not taken into account when answering queries. Thus, even though TAX answers queries with 100% precision, the recall of TAX is relatively low. Our TOSS system improves the recall of TAX via the concept of a similarity enhanced ontology (SEO). Intuitively, an ontology is a set of graphs describing relationships (such as isa, partof, etc.) between terms in a DB. An SEO also evaluates how similarities between terms (e.g. "J. Ullman", "Jeff Ullman", and "Jeffrey Ullman") affect ontologies. Finally, we show how the algebra proposed in TAX can be extended to take SEOs into account. The result is a system that provides a much higher answer quality than TAX does alone (quality is defined as the square root of the product of precision and recall). We experimentally evaluate the TOSS system on the DBLP and SIGMOD bibliographic databases and show that TOSS has acceptable performance. JA - Proceedings of the 2004 ACM SIGMOD international conference on Management of data T3 - SIGMOD '04 PB - ACM CY - New York, NY, USA SN - 1-58113-859-8 UR - http://doi.acm.org/10.1145/1007568.1007649 M3 - 10.1145/1007568.1007649 ER -