Difference between revisions of "Extending a search engine with semantic information"

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Revision as of 21:28, 21 September 2009

Title: Extending a search engine with semantic information
Description: We are used to keyword-based search engines, where only documents matching the exact words in the query are retrieved.

Aim of this project is to expand a traditional search engine with semantic information, so that also documents containing words related to the ones in the query can be retrieved. Existing thesauri and ontologies can be used, as well as more dynamic and interactive sources of knowledge such as user tags and wikipedia pages and categories.

Starting points for this work can be the projects "SeQuEx - Semantic Query Expansion" and "Enriching search results with semantic metadata".

Tutor: DavidLaniado (david.laniado@gmail.com), MarcoColombetti (colombet@elet.polimi.it)
Start: Nowwarning.pngThe date "Now" was not understood.
Students: 1 - 2
CFU: 5 - 20
Research Area: Social Software and Semantic Web
Research Topic: Semantic Search
Level: Bs, Ms
Type: Course, Thesis
Status: Proposalwarning.png"Proposal" is not in the list of possible values (Active, Closed) for this property.


We are used to keyword-based search engines, where only documents matching the exact words in the query are retrieved.

Aim of this project is to expand a traditional search engine with semantic information, so that also documents containing words related to the ones in the query can be retrieved. Existing thesauri and ontologies can be used for the expansion, as well as more dynamic and interactive sources of knowledge such as user tags and wikipedia pages and categories.

Starting points for this work can be the projects SeQuEx - Semantic Query Expansion and Enriching search results with semantic metadata.

Tools and instruments
the project should be preferibly implemented in Java, extending Solr, an open source enterprise search server based on the Lucene Java search library.
Related projects
SeQuEx - Semantic Query Expansion
Enriching search results with semantic metadata