Purpose and Process of Federated Search
– Federated search allows users to search multiple databases at once in real time.
– It provides single point access to many information resources.
– Federated search returns data in a standard or partially homogenized form.
– It offers a real-time view of all sources.
– Federated search can personalize vertical preference for ambiguous queries.
– Federated searching consists of transforming and broadcasting a query to multiple databases or web resources.
– The results collected from the databases are merged and presented in a unified format.
– Federated search portals search public access bibliographic databases, library catalogues, and web-based search engines.
– Portals de-dupe the results list by merging and removing duplicates.
– Federated search is as current as the individual information sources, as they are searched in real time.
Implementation and Challenges of Federated Search
– Metasearch engines are one application of federated searching.
– Metasearch does not overcome the shortcomings of component search engines, such as incomplete indexes.
– Translating the search query to be compatible with component search engines is a challenge.
– Scalability is a challenge in the implementation of federated search engines.
– Cascaded federated search enables a large number of information sources to be searched via a single query.
– Federated searches present challenges compared to conventional searches.
– Maintaining the performance and response speed of a federated search engine is difficult as more information sources are combined.
– Ensuring compatibility of search queries with component search engines is a challenge.
– Federated search faces scalability challenges.
– Federated search engines need to address challenges related to ranking and relevance of search results.
Examples of Federated Search Engines
– WorldWideScience is a federated search engine composed of more than 40 information sources.
– Science.gov is a federated search portal that federates more than 30 information sources.
– Sesam is a federated search application built on top of an open-sourced platform.
– LinkedIn search engine uses federated search to personalize vertical orders based on user intent.
– SWIRL Search is an open-source federated search engine with pre-built connectors to popular search engines.
Passing of Credentials and Mapping Results
– Credentials must be passed to secure data sources for federated search.
– Different login credentials for different systems require mapping to each search engine’s security domain.
– Maintaining appropriate security is crucial when passing user credentials.
– Combining facets from multiple sources into one set presents technical challenges.
– Understanding next page links is necessary for allowing users to navigate through combined results.
– Linked open data via RDF can help solve the challenge of mapping results to a common form.
– Ontologies can be added to map results using RDF technology.
Sorting and Scoring Results, and Robust Query
– Each web resource has its own relevance score and sorted results orders.
– Relevance varies greatly among federates, making it difficult to interleave results effectively.
– Determining the most relevant results is challenging or even impossible.
– Federated search may need to limit itself to the minimal set of query capabilities common to all federates.
– Inconsistencies in query capabilities among federates can limit the search functionality.
– Some federates may not support advanced query features, such as negation or quoted phrases.
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Federated search retrieves information from a variety of sources via a search application built on top of one or more search engines. A user makes a single query request which is distributed to the search engines, databases or other query engines participating in the federation. The federated search then aggregates the results that are received from the search engines for presentation to the user. Federated search can be used to integrate disparate information resources within a single large organization ("enterprise") or for the entire web.
Federated search, unlike distributed search, requires centralized coordination of the searchable resources. This involves both coordination of the queries transmitted to the individual search engines and fusion of the search results returned by each of them.
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