The aim of information retrieval systems is to retrieve relevant information according to the query provided. The queries are often vague and uncertain. Thus, to improve the system, we propose an Automatic Query Expansion technique, to expand the query by adding new terms to the user s initial query so as to minimize query mismatch and thereby improving retrieval performance. Most of the existing techniques for expanding queries do not take into account the degree of semantic relationship among words. In this paper, the query is expanded by exploring terms which are semantically similar to the initial query terms as well as considering the degree of relationship, that is, “fuzzy membership- between them. The terms which seemed most relevant are used in expanded query and improve the information retrieval process. The experiments conducted on the queries set show that the proposed Automatic query expansion approach gave a higher precision, recall, and F measure then non fuzzy edge weights. Tarun Goyal | Ms. Shalini Bhadola | Ms. Kirti Bhatia "Automatic Query Expansion Using Word Embedding Based on Fuzzy Graph Connectivity Measures" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45074.pdf Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/45074/automatic-query-expansion-using-word-embedding-based-on-fuzzy-graph-connectivity-measures/tarun-goyal
International Journal of Trend in Scientific Research and Development (IJTSRD)
Volume 5 Issue 5, July-August 2021 Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470
@ IJTSRD | Unique Paper ID – IJTSRD45074 | Volume – 5 | Issue – 5 | Jul-Aug 2021
Page 1429
Automatic Query Expansion Using Word Embedding
Based on Fuzzy Graph Connectivity Measures
Tarun Goyal
1
, Ms. Shalini Bhadola
2
, Ms. Kirti Bhatia
3
1M Tech Student, 2Assistant Professor, 3HOD,
1, 2, 3Computer Science & Engineering, Sat Kabir Institute of Technology and Management
Bahadurgarh (HR) Affiliated by Maharshi Dayanand University (Rohtak), Haryana, India
ABSTRACT
The aim of information retrieval systems is to retrieve relevant
information according to the query provided. The queries are often
vague and uncertain. Thus, to improve the system, we propose an
Automatic Query Expansion technique, to expand the query by
adding new terms to the user‟s initial query so as to minimize query
mismatch and thereby improving retrieval performance. Most of the
existing techniques for expanding queries do not take into account
the degree of semantic relationship among words. In this paper, the
query is expanded by exploring terms which are semantically similar
to the initial query terms as well as considering the degree of
relationship, that is, “fuzzy membership” between them. The terms
which seemed most relevant are used in expanded query and improve
the information retrieval process. The experiments conducted on the
queries set show that the proposed Automatic query expansion
approach gave a higher precision, recall, and F- measure then non-
fuzzy edge weights.
KEYWORDS: Information Retrieval; Fuzzy Log; WordNet; Centrality
How to cite this paper: Tarun Goyal |
Ms. Shalini Bhadola | Ms. Kirti Bhatia
"Automatic Query Expansion Using
Word Embedding Based on Fuzzy
Graph
Connectivity
Measures"
Published
in
International
Journal of Trend in
Scientific Research
and Development
(ijtsrd), ISSN: 2456-
6