Semantic Search Arrives at the Web(About) There are two approaches toward semantic search and both have received attention in the past months. The first approach builds on the automatic analysis of text using Natural Language Processing (NLP). The second approach uses semantic web technologies, which aims to make the web more easily searchable by allowing publishers to expose their (meta)data.
alphaWorks : Scalable Highly Expressive Reasoner : Overview(About) Scalable Highly Expressive Reasoner (SHER) is a breakthrough technology that provides ontology analytics over highly expressive ontologies (OWL-DL without nominals). SHER does not do any inferencing on load; hence it deals better with quickly changing data (the downside is, of course, that reasoning is performed at query time). The tool can reason on approximately seven million triples in seconds, and it scales to data sets with 60 million triples, responding to queries in minutes. It has been used to semantically index 300 million triples from medical literature. SHER tolerates logical inconsistencies in the data, and it can quickly point you to these inconsistencies in the data and help you clean up inconsistencies before issuing semantic queries. The tool explains (or justifies) why a particular result set is an answer to the query; this explanation is useful for validation by domain experts.