Identifying Common User Behaviour in Multilingual Search Logs

Abstract

Abstract. The LADS (Log Analysis for Digital Societies) task at CLEF aims at investigating user actions in a multilingual setting. We carried out an analysis of search logs with the objectives of investigating how users from different linguistic or cultural backgrounds behave in search, and how the discovery of patterns in user actions could be used for community identification. The findings confirm that users from a different background behave differently, and that there are identifiable patterns in the user actions. The findings suggest that there is scope for further investigation of how search logs can be exploited to personalise and improve cross-language search as well as improve the TEL search system.

Moving towards Adaptive Search in Digital Libraries

“…This log covers the period from 1 January 2007 till 30 June 2008 [2]. In the logs there is a great inclination towards using simple search compared to using advanced search [19]. In our experiments we do not consider queries submitted via the advanced search interface.…”

Multilingual Adaptive Search for Digital Libraries

“…The motivation for the AMIR framework originates from the observations that i) users from different linguistic or cultural backgrounds behave differently in search; ii) there are identifiable patterns in user actions; and iii) user queries and action patterns reflect the mental model or prior knowledge of a user about a search system [3]. These observations call for the need to address adaptivity and multilinguality aspects in DL search.…”

“…Estimates show that 60% of World Wide Web (WWW) users are non-English speakers 3 and the content available in non-English languages is growing fast. The variety in users and language means that regardless of which languages a user speaks, there is a large volume of content which users cannot easily discover, consume or comprehend.…”

Improving query and result list adaptation in personalized multilingual information retrieval

“…So far, the work carried out for this study included: (1) a proposed framework for the delivery and evaluation of PMIR [3]; and (2) exploratory experiments with search history and collection (result) re-ranking on a dataset of multilingual search logs [2]. The next stage of experimentation will involve the investigation and development of algorithms for: (1) constructing multilingual user profiles; (2) pre-translation and post-translation query expansion based on terms from the user profile; and (3) result list re-ranking based on the user's interests, and preferred language.…”