n-Keyword based Automatic Query Generation

In the information retrieval process, the selection of keywords and the generation of queries are very critical for the efficient retrieval. However, users experience the difficulties of selecting major keywords without being aware of the domain context. This paper proposes an automatic query genera...

Full description

Saved in:
Bibliographic Details
Main Authors: Ryu, Hoyeon, Kim, Gunhee, Yoo, Kyeongjong, Ha, Sungdo
Format: Conference Proceeding
Language:English
Subjects:
Context awareness
Context modeling
Data mining
Decision making
Information retrieval
Information systems
Ontologies
Project management
Research and development
Thesauri
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In the information retrieval process, the selection of keywords and the generation of queries are very critical for the efficient retrieval. However, users experience the difficulties of selecting major keywords without being aware of the domain context. This paper proposes an automatic query generation method using n-Keyword expansion model, which consists of keyword extraction, keyword expansion and query generation. This method uses context model, semantic thesaurus and ontology. The keyword extraction is for finding document annotation data and document instances that are inferred from ontology and making the list of document keyword. n- Keyword, keywords expanded from the user input keyword, is constructed by selecting candidate keywords and assigning weight value to each candidate keyword from semantic thesaurus and document keyword list after consideration of context models. The query generation expands and generates the query using weighted keywords and query patterns. In retrieval for documents, n-Keyword using semantic thesaurus makes more useful query than users' keyword.
DOI:10.1109/ICHIT.2006.253595