INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Automatically Mining Facets For Queries From Their Search Results Using Association Rule And Textual Entailment
Authors Name:
Khot Kishor Ganpati
, B.R.Solunke
Unique Id:
IJSDR2109011
Published In:
Volume 6 Issue 9, September-2021
Abstract:
We address the issue of discovering inquiry features which are numerous gatherings of words or expressions that clarify and sum up the substance covered by a question. We accept that the significant parts of a question are typically introduced and rehashed in the inquiry's top recovered records in the style of records, and question features can be mined out by conglomerating these huge records. We further dissect the issue of rundown duplication, and discover better question aspects can be mined by demonstrating fine-grained similitudes among records and punishing the copied records. A Facet item is typically a word or a phrase. A query may have multiple facets that summaries the information about the query from different perspectives. We address the problem of finding query facets which are multiple groups of words or phrases that explain and summarize the content covered by a query. We propose a systematic solution, which we refer to automatically mine query facets by extracting and grouping frequent list from free text ,html tags, and repeat regions within top search result. We assume that important aspect of query are usually presented and repeated in the queries top retrieved document in the style of lists, query facets can be mined out by aggregating these significant lists
Keywords:
Query Facet, Faceted Search, Summarization, User Intent
Cite Article:
"Automatically Mining Facets For Queries From Their Search Results Using Association Rule And Textual Entailment", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.6, Issue 9, page no.64 - 69, September-2021, Available :http://www.ijsdr.org/papers/IJSDR2109011.pdf
Downloads:
000337070
Publication Details:
Published Paper ID: IJSDR2109011
Registration ID:193655
Published In: Volume 6 Issue 9, September-2021
DOI (Digital Object Identifier):
Page No: 64 - 69
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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