Towards multilingual user models for Personalized Multilingual Information Retrieval

Ghorab, M. Rami; Zhou, Dong; Steichen, Ben; Wade, Vincent

doi:10.1145/2047403.2047411

Cited by 7 publications

(13 citation statements)

References 13 publications

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“…In keeping with this trend, this study as well as other current research in MLIR shifts the focus from a system-oriented approach to a more user centered approach that emphasizes user experience and user perception: in this case, the emphasis is less on the language proficiency (primarily English) of the user or their search expertise. For MLIR system users, some studies have proposed developing Personalized Multilingual Information Retrieval models (PMLIR) that take into consideration factors such as users' browsing and search behavior (Ghorab, Zhou, Steichen, & Wade, 2011;Steichen, Ghorab, O'Connor, Lawless, & Wade, 2014).…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Multilingual Information Retrieval & Use: Perceptions and Practices Amongst Bi/Multilingual Academic Users

Nzomo

Ajiferuke

Vaughan

et al. 2016

The Journal of Academic Librarianship

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Section: Conclusion and Future Researchmentioning

confidence: 99%

Multilingual Information Retrieval & Use: Perceptions and Practices Amongst Bi/Multilingual Academic Users

Nzomo

Ajiferuke

Vaughan

et al. 2016

The Journal of Academic Librarianship

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“…Given the fact that there is a vast amount of data found on the internet, these data can exist in different languages [6]. It is possible that the data requested from a user will not be available in his native language but be available in a foreign language.…”

Section: Multilingual Personalizationmentioning

confidence: 99%

Factors Influencing the Quality of the User Experience in Ubiquitous Recommender Systems

Polatidis

Georgiadis

2014

Distributed, Ambient, and Pervasive Interactions

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Abstract. The use of mobile devices and the rapid growth of the internet and networking infrastructure has brought the necessity of using Ubiquitous recommender systems. However in mobile devices there are different factors that need to be considered in order to get more useful recommendations and increase the quality of the user experience. This paper gives an overview of the factors related to the quality and proposes a new hybrid recommendation model.

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“…Ghorab, Zhou et al [1] investigate the representation, creation, use, and evaluation of user models for personalised IR in a multilingual environment. They argue that their proposed representation of a user model, which is created from the user search history, would be more suitable for personalised multilingual information retrieval.…”

Section: Accepted Workhop Papersmentioning

confidence: 99%

Personalised multilingual hypertext retrieval

Agosti

Luca

Lawless

et al. 2011

Proceedings of the First Workshop on Personalised Multilingual Hypertext Retrieval

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The aims of the workshop on Personalised Multilingual Hypertext Retrieval (PMHR) are twofold: to set the scene in this challenging area, allowing the different communities engaged in related research topics to meet and to determine a program of actions to undertake; to devise a strategy for the evaluation of PMHR systems, which should define the collection of resources to use to evaluate such systems together with the evaluation metrics to use. The workshop results will be of use in the design of personalised tools that can help end-users fully benefit from the use of distributed multilingual hypertext content. Background and MotivationSearch engines have traditionally followed "a one size fits all" paradigm and returned the same results for all users. They do not adapt to the user, the domain, or the search context. Thus, the search process and the number and type of results returned are not tailored to the individual user or their search situation. Personalised hypertext retrieval is concerned with adapting the search process to the user's needs. This includes adapting the system, the query-document similarity metrics, the search results, and their presentation to an individual user. The personalisation process can be based on models of the user, the domain, and the search context, but no standard representation or resources have evolved to-date.It can often be the case that non-native English speakers suffer limited or restricted online experiences as typically the majority of web content is still authored in English. Machine translated versions of content may be generated for some languages, but this is not always the case. This results in the user being greatly restricted in the content collections across which they can search. 1The papers accepted for the PMHR 2011 workshop start to explore the use of multilingual hypertext retrieval technologies and adaptive personalisation techniques to enable end-users to write queries in their native language, but receive results collated from content collections in a variety of languages, all tailored for consumption by the end-user.To reach useful results, it is necessary to solicit cooperation between researchers working in many different areas, such as hypertext and adaptive hypertexts, cross-lingual information retrieval, personalised search, personalisation for Web and hypertexts, and recommender systems. Goals and ObjectivesPersonalised multilingual hypertext retrieval has to be viewed as an interdisciplinary research task, as it can include ideas from adaptive hypertext, user modelling for adaptive hypertext, personalisation for Web and hypertext, humancomputer interaction, and interactive authoring environments.The main goals of the workshop are: to develop a roadmap to follow which identifies the different research challenges that need to be faced in the design and implementation of personalised multilingual hypertext retrieval systems and tools of use for the end-user; to develop a strategy for the evaluation of PMHR systems, in addition, to define the collec...

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Towards multilingual user models for Personalized Multilingual Information Retrieval

Cited by 7 publications

References 13 publications

Multilingual Information Retrieval & Use: Perceptions and Practices Amongst Bi/Multilingual Academic Users

Multilingual Information Retrieval & Use: Perceptions and Practices Amongst Bi/Multilingual Academic Users

Factors Influencing the Quality of the User Experience in Ubiquitous Recommender Systems

Personalised multilingual hypertext retrieval

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