[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Claire Ibarboure ; Ludovic Tanguy and Franck Amadieu

Affiliation: CLLE: CNRS & University of Toulouse, France

Keyword(s): Word Embeddings, Information Retrieval, Queries, Search Strategies.

Abstract: In order to represent the global strategies deployed by a user during an information retrieval session on the Web, we compare different pretrained vector models capable of representing the queries submitted to a search engine. More precisely, we use static (type-level) and contextual (token-level, such as provided by transformers) word embeddings on an experimental French dataset in an exploratory approach. We measure to what extent the vectors are aligned with the main topics on the one hand, and with the semantic similarity between two consecutive queries (reformulations) on the other. Even though contextual models manage to differ from the static model, it is with a small margin and a strong dependence on the parameters of the vector extraction. We propose a detailed analysis of the impact of these parameters (e.g. combination and choice of layers). In this way, we observe the importance of these parameters on the representation of queries. We illustrate the use of models with a r epresentation of a search session as a trajectory in a semantic space. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 79.170.44.78

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Ibarboure, C. ; Tanguy, L. and Amadieu, F. (2023). Which Word Embeddings for Modeling Web Search Queries? Application to the Study of Search Strategies. In Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR; ISBN 978-989-758-671-2; ISSN 2184-3228, SciTePress, pages 273-280. DOI: 10.5220/0012177600003598

@conference{kdir23,
author={Claire Ibarboure and Ludovic Tanguy and Franck Amadieu},
title={Which Word Embeddings for Modeling Web Search Queries? Application to the Study of Search Strategies},
booktitle={Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR},
year={2023},
pages={273-280},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012177600003598},
isbn={978-989-758-671-2},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR
TI - Which Word Embeddings for Modeling Web Search Queries? Application to the Study of Search Strategies
SN - 978-989-758-671-2
IS - 2184-3228
AU - Ibarboure, C.
AU - Tanguy, L.
AU - Amadieu, F.
PY - 2023
SP - 273
EP - 280
DO - 10.5220/0012177600003598
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic

<style> #socialicons>a span { top: 0px; left: -100%; -webkit-transition: all 0.3s ease; -moz-transition: all 0.3s ease-in-out; -o-transition: all 0.3s ease-in-out; -ms-transition: all 0.3s ease-in-out; transition: all 0.3s ease-in-out;} #socialicons>ahover div{left: 0px;} </style>