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

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|title=Extending a search engine with semantic information
 
|title=Extending a search engine with semantic information
 
|image=velociraptor.png
 
|image=velociraptor.png
|description=We are used to keyword-based search engines, where only documents matching the exact words in the query are retrieved. In a traditional search engine, if you submit the query "a dinosaur in a university in Lombardy" you won't probably find a document containing the phrase "a velociraptor in Politecnico di Milano", even if it's more or less what you were looking for.
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|description=We are used to keyword-based search engines, where only documents matching the exact words in the query are retrieved. In a traditional search engine, if you submit the query "a dinosaur in a university in Lombardy" you won't probably find a document containing the phrase "a velociraptor in Politecnico di Milano", even though it's more or less what you were looking for.
  
 
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 collaborative sources of knowledge such as user tags and wikipedia pages and categories.  
 
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 collaborative sources of knowledge such as user tags and wikipedia pages and categories.  
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Starting points for this work can be the projects "SeQuEx - Semantic Query Expansion" and "Enriching search results with semantic metadata".
 
Starting points for this work can be the projects "SeQuEx - Semantic Query Expansion" and "Enriching search results with semantic metadata".
 
|tutor=DavidLaniado;MarcoColombetti
 
|tutor=DavidLaniado;MarcoColombetti
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|studmin=1
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|studmax=2
 
|cfumin=5
 
|cfumin=5
 
|cfumax=20
 
|cfumax=20
|studmin=1
 
|studmax=2
 
 
|resarea=Social Software and Semantic Web
 
|resarea=Social Software and Semantic Web
 
|restopic=Semantic Search
 
|restopic=Semantic Search
|level=Bs;Ms
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|level=Bs; Ms
|type=Course;Thesis
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|type=Course; Thesis
 
}}
 
}}
 
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We are used to keyword-based search engines, where only documents matching the exact words in the query are retrieved. In a traditional search engine, if you submit the query "a dinosaur in a university in Lombardy" you won't probably find a document containing the phrase "a velociraptor in Politecnico di Milano", even though it's more or less what you were looking for.
 
+
We are used to keyword-based search engines, where only documents matching the exact words in the query are retrieved. In a traditional search engine, if you submit the query "a dinosaur in a university in Lombardy" you won't probably find a document containing the phrase "a velociraptor in Politecnico di Milano", even if it's more or less what you were looking for.
+
  
 
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 collaborative sources of knowledge such as user tags and wikipedia pages and categories.  
 
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 collaborative sources of knowledge such as user tags and wikipedia pages and categories.  

Revision as of 10:11, 23 October 2009

Title: Extending a search engine with semantic information
Velociraptor.png

Image:velociraptor.png

Description: We are used to keyword-based search engines, where only documents matching the exact words in the query are retrieved. In a traditional search engine, if you submit the query "a dinosaur in a university in Lombardy" you won't probably find a document containing the phrase "a velociraptor in Politecnico di Milano", even though it's more or less what you were looking for.

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 collaborative 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

We are used to keyword-based search engines, where only documents matching the exact words in the query are retrieved. In a traditional search engine, if you submit the query "a dinosaur in a university in Lombardy" you won't probably find a document containing the phrase "a velociraptor in Politecnico di Milano", even though it's more or less what you were looking for.

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 collaborative 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