The main goals of the workshop are:
1) to develop a roadmap to follow which identifies the different research challenges that need to be faced to envisage, design and implement personalised multilingual web systems and tools of use for the end-user;
2) to develop a strategy to follow for the identification of the process to use for the evaluation of PMW systems, in addition, to define the collection of web documents to use to evaluate such types of systems together with the metrics to use.
Personalised multilingual web science 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, human-computer interaction, and interactive authoring environments.
Our first workshop on Personalized Multilingual Hypertext Retrieval took place in conjunction with the ACM Conference on Hypertext and Hypermedia 2011 and attracted researchers working in interdisciplinary Web areas. Following the success of this workshop, we think that the current workshop topics are relevant and suitable for the Web Science Conference. Search 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 her/his search situation. Personalised Web Science 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.
Topics include, but are not limited to:
- Multilingual semantic search and intelligent information retrieval, extraction and filtering (e.g. How does a multilingual setting affect personalised Web Science?)
- Multilingualism in semantic search or in context-aware and semantic recommender systems
- Recommender systems, adaptation engines, algorithms for personalised multilingual Web Science User modelling and adaptation (e.g. creation and exploitation of individual or stereotypical user profiles)
- Content personalisation and personalised result presentation (e.g. result presentation beyond the ranked list to enable users to fully benefit from the semantics carried by the hypertext structure)
- Domain modelling (e.g. adaptation to different domains)
- Creating relevant linguistic resources (processing user models, query logs or forum postings); privacy issues
- External knowledge resources for personalised multilingual Web Science (e.g. ontologies)
- Personalized and multilingual ontologies (and their application) Personalisation of multilingual tools, Tools and methods for bilingual search
- Evaluation methodologies and metrics for personalised Web Science