ontology portals fishery 20040205

FAO Ontology Portal Prototypes FISHERY: 

FAO Ontology Portal Prototypes FISHERY January 2004

Functionalities: 

Functionalities Form versus meaning: Traditional Search Concept Search Implemented functionalities: synonym search multilingual capability terminology brokering disambiguation related concepts query expansion Basic natural language queries Semantic navigation of bibliographical metadata Semantic Navigation of Knowledge Alphabetic list ... as a starting point Core Fishery Concepts ... as a starting point

Additional Functionalities: 

Additional Functionalities Functionalities to further develop: Intelligent query expansion Natural language queries (paraphrasing) check spelling parsing stemming Semantic Navigation of Knowledge Thesaurus based

Demo: 

Demo

1) Form versus meaning: a) Traditional Search: 

1) Form versus meaning: a) Traditional Search The system gets records from different portals using the string vessel

1) Form versus meaning: a) Traditional SearchFAOBIB results: 

1) Form versus meaning: a) Traditional Search FAOBIB results Using a free text search, the system retrieves all records containing the string “vessel” including records not pertinent to the user’s intended meaning of the term Using a keyword search, the system retrieves 0 results as the thesaurus used in this portal does not use vessel as a keyword

1) Form versus meaning: b) Concept Search: 

1) Form versus meaning: b) Concept Search In a concept based search the system retrieves all meanings represented by the term vessel. For example: vessel can refer to the concept blood vessel vessel can also be interpreted as ship

2) Implemented functionalities: a) synonym search: 

2) Implemented functionalities: a) synonym search The same records will be retrieved regardless of the specific synonyms or singular/plural forms that the user uses to refer to a concept.

2) Implemented functionalities: b) multilingual capability: 

2) Implemented functionalities: b) multilingual capability The system is also able to understand a concept even when different languages are used.

2) Implemented functionalities: c) terminology brokering: 

2) Implemented functionalities: c) terminology brokering User query terms are converted into the respective corresponding variants used in a given information system

2) Implemented functionalities: d) disambiguation: 

2) Implemented functionalities: d) disambiguation When the query term is ambiguous all concepts that correspond to that term are displayed to the user and disambiguated using the parent concept

2) Implemented functionalities: e) related concepts: 

2) Implemented functionalities: e) related concepts Concepts related to the user query are displayed (e.g. for query refinements, etc.)

2) Implemented functionalities:f) query expansion (ex. 1): 

2) Implemented functionalities: f) query expansion (ex. 1) The query can be refined using one or more related concept(s)

2) Implemented functionalities:f) query expansion  (ex. 2): 

2) Implemented functionalities: f) query expansion (ex. 2) To improve query results (in terms of quality and quantity), it is possible to select one or more translations or related terms...

Slide15: 

...The query will then take into consideration all selected lexicalizations to improve the query. The system will broker the refined query using the terms from a given portal..

3) Basic natural language queries: 

3) Basic natural language queries Bibliographical records related to fishing vessel in Kenya

4) Semantic navigation of bibliographical metadata: 

4) Semantic navigation of bibliographical metadata

5) Semantic Navigation of Knowledge: a) Alphabetic list ... as a starting point: 

5) Semantic Navigation of Knowledge: a) Alphabetic list ... as a starting point

5) Semantic Navigation of Knowledge: b) Core Fishery Concepts ... as a starting point: 

5) Semantic Navigation of Knowledge: b) Core Fishery Concepts ... as a starting point parent concept(s) children concept(s)

Additional Functionalities: 

Additional Functionalities

a) Intelligent query expansion: 

a) Intelligent query expansion japanese fishing vessel The system search for documents related to Japan and fishing vessel If 0 results are retrieved, the system search for Asia and fishing vessel etc.

b) Natural language queries (paraphrasing): 

b) Natural language queries (paraphrasing) japanese fishing vessel tuna ships in the Caribbean sea etc. The System check first for spelling errors, parse the query

c) Semantic Navigation of Knowledge: a) Thesaurus based: 

c) Semantic Navigation of Knowledge: a) Thesaurus based Highlighting the originator thesaurus. User can select a specific thesaurus to look for.