loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Fatma Zohra Lebib 1 ; Hakima Mellah 2 and Abdelkrim Meziane 2

Affiliations: 1 University of Science and Technology Houari Boumediene, USTHB, Algiers, Algeria, Research Center in Scientific and Technical Information, CERIST, Algiers and Algeria ; 2 Research Center in Scientific and Technical Information, CERIST, Algiers and Algeria

Keyword(s): Log Files Analysis, Web Usage Mining, Multi-source Search System, Knowledge Extraction, Information Source, User Profile.

Abstract: In a multi-source search system, understanding users’ interests and behaviour is essential to improve the search and adapt the results according to each user profile. The interesting information characterizing the users can be hidden in large log files, whereas it must be discovered, extracted and analyzed to build an accurate user profile. This paper presents an approach which analyzes the log data of a multi-source search system using the web usage mining techniques. The aim is to capture, model and analyze the behavioural patterns and profiles of users interacting with this system. The proposed approach consists of two major steps, the first step “pre-processing” eliminates the unwanted data from log files based on predefined cleaning rules, and the second step “processing” extracts useful data on user’s previous queries. In addition to the conventional cleaning process that removes irrelevant data from the log file, such as access of multimedia files, error codes and accesses of Web robots, deep cleaning is proposed, which analyzes the queries structure of different sources to further eliminate unwanted data. This allows to accelerate the processing phase. The generated data can be used for personalizing user-system interaction, information filtering and recommending appropriate sources for the needs of each user. (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 3.237.232.196

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:
Lebib, F.; Mellah, H. and Meziane, A. (2019). Knowledge Discovery from Log Data Analysis in a Multi-source Search System based on Deep Cleaning. In Proceedings of the 15th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-386-5; ISSN 2184-3252, SciTePress, pages 257-264. DOI: 10.5220/0008121102570264

@conference{webist19,
author={Fatma Zohra Lebib. and Hakima Mellah. and Abdelkrim Meziane.},
title={Knowledge Discovery from Log Data Analysis in a Multi-source Search System based on Deep Cleaning},
booktitle={Proceedings of the 15th International Conference on Web Information Systems and Technologies - WEBIST},
year={2019},
pages={257-264},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008121102570264},
isbn={978-989-758-386-5},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Web Information Systems and Technologies - WEBIST
TI - Knowledge Discovery from Log Data Analysis in a Multi-source Search System based on Deep Cleaning
SN - 978-989-758-386-5
IS - 2184-3252
AU - Lebib, F.
AU - Mellah, H.
AU - Meziane, A.
PY - 2019
SP - 257
EP - 264
DO - 10.5220/0008121102570264
PB - SciTePress