Search with SWOOGLE
Swoogle, the Semantic web search engine for Semantic Web ontologies, documents, terms and data published on the Web , is a research project carried out by the ebiquity research group in the Computer Science and Electrical Engineering Department at the University of Maryland. Swoogle is a crawler-based indexing and retrieval system for the Semantic Web. It extracts metadata for each discovered document, and computes relations between documents. Discovered documents are also indexed by an information retrieval system which can use either character N-Gram or URIrefs as keywords to find relevant documents and to compute the similarity among a set of documents.
Swoogle is an online repository of SWDs.
The Semantic Web’s distributed nature raises significant data access problems like how can an agent discover, index, search and navigate knowledge on the Semantic Web? Swoogle was developed to facilitate webscale semantic web data access by providing these services to both human and software agents.
Swoogle provided services to human users through a browser interface and to software agents via RESTful web services. Several techniques were used to rank query results inspired by the PageRank algorithm developed at Google but adapted to the semantics and use patterns found in semantic web documents.
Swoogle Interface
A general user can query with keywords, and the SWDs matching those keywords will be returned in ranked order.
Objectives of Swoogle
- More and more SWDs, both ontology and instance a physically distributed all over the web.
- A retrieval system that organizes these documents in a systematic way.
Why use Swoogle
- Avoid creating new ontologies
- Need for reuse
Services of Swoogle
- Search Semantic web ontologies.
- Search Semantic web instance data.
- Archive different versions of Semantic Web documents.
- Provide meta data of Semantic web documents and support browsing the Semantic web.
Swoogle Architecture
The SWD discovery component discovers the potential SWDs throughout the Web and keeps up-to-date information about SWDs. The metadata creation component caches a snapshot of a SWD and generates objective metadata about SWDs at both the syntax level and the semantic level. The data analysis component uses the cached SWDs and the created metadata to derive analytical reports, such as classification of SWOs and SWDBs, rank of SWDs, and the IR index of SWDs. The interface component focuses on providing data services to the Semantic Web community.
