Semantic document indexing and search engine framework
Domain-speciﬁc communities, especially technical and scientiﬁc, willing to build search engines and information systems to manage documents with ﬁne-grained semantic annotations.
Search engines and information systems development.
AlvisIR is a complete suite for indexing documents with ﬁne-grained semantic annotations. The search engine performs a semantic analysis of the user query and searches for synonyms and sub-concepts.
AlvisIR has two main components:
1. the indexing tool and search daemon based on IndexDataʼs Zebra that supports standard CQL queries,
2. the web user interface featuring result snippets, query-term highlight, facet ﬁltering and concept hierarchy browsing.
Setting up a search engine requires the semantic resources for query analysis (synonyms and concept hierarchy) and a set of annotated documents. AlvisIR is closely integrated with AlvisNLP and TyDI for document annotation and semantic resources acquisition respectively.
Indicative indexing time: 24mn for a corpus containing 5 million annotations.
Indicative response time: 18s for a response containing 20,000 annotations.
Sources available upon request. Free of use for academic institutions.