A Theme-based Search Technique

Abstract:- This work presents an intelligent search engine, called ORCA, that returns the most relevant documents for user’s queries. This search engine analyses the queries and builds themes (models) to be used when the engine is confronted with similar queries. The intelligent component is used fo...

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Bibliographic Details
Main Authors: Nida Al-chalabi, Khalil Shihab
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Subjects:
Information Filtering
User’s Model
Search Engines
Latent Search Analysis
Orca
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.416.3008
http://www.wseas.us/e-library/conferences/2007cscc/papers/561-331.pdf
Description
Summary:Abstract:- This work presents an intelligent search engine, called ORCA, that returns the most relevant documents for user’s queries. This search engine analyses the queries and builds themes (models) to be used when the engine is confronted with similar queries. The intelligent component is used for constructing a model of the user behavior and using that model to fetch and even pre-fetch information and documents considered of interest to the user. It uses both latent semantic analysis and web page feature selection for clustering web pages. Latent semantic analysis is used to find the semantic relations between keywords, and between documents.

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