Web search is typically memory-less, in the sense that each new search query is considered
afresh and 'solved'from scratch. We believe that this reflects the strong information retrieval …

Web search is the main way for millions of users to access information every day, but we
continue to struggle when it comes to finding the right information at the right time. In this …

Collaborative Web search is a community-based approach to adaptive Web search that is
fundamentally case-based: the results of similar past search sessions are reused in …

This article addresses the problem to predict user behaviours on a Web site which is very
known to be an important way for improving the e ectiveness of Web sites. Our objective is to …

This paper describes and evaluates a case-based approach to personalizing Web search by
post-processing the results returned by a Web search engine to reflect the interests of a …

We present in this paper a hybrid neuro-symbolic system called “CASEP2”, which combines
the case-based reasoning with an adequate artificial neural network “M-SOM-ART” for …

For the main part, when it comes to questions of retrieval, the focus of CBR research has
been on the retrieval of cases from a repository of experience knowledge or case base. In …

Abstract Collaborative Web Search is an approach to Web search that takes advantage of
ideas from casebased reasoning in order to improve upon the results of a standard search …

In this paper we present Casep2: a hybrid neuro-symbolic system combining case-based
reasoning (CBR) and artificial neural networks that aims at clustering and classifying users' …

HeyStaks is a case-based social search system that allows users to create and share case
bases of search experiences (called staks) and uses these staks as the basis for result …