Knowledge Discovery from Log Data Analysis in a Multi-source Search System based on Deep Cleaning

Fatma Lebib, Hakima Mellah, Abdelkrim Meziane

2019

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.

Paper Citation

in Harvard Style

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 - Volume 1: WEBIST, ISBN 978-989-758-386-5, pages 257-264. DOI: 10.5220/0008121102570264

in Bibtex Style

@conference{webist19,
author={Fatma 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 - Volume 1: WEBIST,},
year={2019},
pages={257-264},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008121102570264},
isbn={978-989-758-386-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Knowledge Discovery from Log Data Analysis in a Multi-source Search System based on Deep Cleaning
SN - 978-989-758-386-5
AU - Lebib F.
AU - Mellah H.
AU - Meziane A.
PY - 2019
SP - 257
EP - 264
DO - 10.5220/0008121102570264