Outline Content-Based Image Retrieval Query-by-Example Query-by-Feature Feature Vector.
A MIND MAP QUERY IN INFORMATION RETRIEVAL
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Transcript of A MIND MAP QUERY IN INFORMATION RETRIEVAL
Presented in:
Fourth International Conference on Computer Science, Engineering and Applications
(ICCSEA 2014), July 26 – 27, 2014 in Chennai, India
Traditional Approach:Bag of Words-misinterpretation of user’s
need user cannot express clearly the main words of
his idea of search and the less important words.
idea of the user is packaged in a linear form which does not express the nodes in the network of the user’s mind.
Related Work:Pearl trees system:Storing interests in Mind MapsSearch:
Bag of WordsSelecting a Pearl
Problem:Semantic ClusteringEx. “popular terms Information Retrieval”
Proposed Approach
Mind Map Query:
Mind Map query formulation by the user andAn internal representation of the Mind Map
query by the IR system.
Example Query:“The definition of a concept in a thesaurus or
by standard norms”Bag of Words: Equal Weighting for all terms: “definition of concept thesaurus standard norms”
Example Query: “a good java course which describes
inheritance and polymorphism, but also contains other notions of java. This course should contain exercises”
Bag Of Words: “good java course inheritance polymorphism
exercises”
Example Query:“the definition of a semantic resource, for
example thesaurus, ontology”
Bag Of Words: semantic resource definition
Internal Semantic for Mind Map Queries
Where= The power of importance between levels = The weight attributed to the leafs of the
graph The depth of the node in the query graph h = The height of the query graph
Calculation:W1=Term Weight of PrecisionW1=W2=W3=W4=
Term Precision was twice more important than other terms.
Experimentation:On medical corpus (CLEF 2009, (Cross
Language Evaluation Forum)74’902 images from 20’000 English journal
articles in Radiology.25 queries in the collection test.
IRS based QueryMind Map Query
ReferencesRihab Ayed, Farah Harrathi, M. Mohsen Gammoudi and
Mahran Farhat(2014) A Mind Map Query in Information Retrieval: The ‘User Query Idea’ concept and preliminary results. Fourth International Conference on Computer Science, Engineering and Applications (ICCSEA 2014), July 26 – 27, 2014 in Chennai, India
Kamvar, M., Kellar, M., Patel, R. and Xu, Y. (2009) Computers and iPhones and Mobile Phones, a logs based comparison of search users on different devices. In Proceedings of the 18th International Conference on World Wide Web (Madrid, Spain, April 20-24, 2009). WWW'09. ACM, New York,NY,801-810.