Recommender systems have proven to be an important response to the information overload problem, by providing users with more proactive and personalized information services. And collaborative filtering techniques have proven to be an vital component of many such recommender systems as they facilitate the generation of high-quality recom-mendations by… (More)
Introduction The utility problem-certain " harmful " knowledge may actually degrade system performance(problem solving efficiency or time) The swamping problem-the expense of searching large case-bases for appropriate cases with which to solve the current problem.
Recently the world of the web has become more social and more real-time. Facebook and Twitter are perhaps the exemplars of a new generation of social, real-time web services and we believe these types of service provide a fertile ground for recommender systems research. In this paper we focus on one of the key features of the social web, namely the creation… (More)
Case-based reasoning systems solve problems by reusing a corpus of previous problem solving experience stored as a case-base of individual problem solving cases. In this paper we describe a new technique for constructing compact competent case-bases. The technique is novel in its use of an explicit model of case competence. This allows cases to be selected… (More)
Case-based reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving (i.e., new problems are solved by reusing and if necessary adapting the solutions to similar problems that were solved in the past). It has enjoyed considerable success in a wide variety of problem solving tasks and… (More)
Mobile phones are becoming increasingly popular as a means of information access while on-the-go. Mobile users are likely to be interested in locating different types of content. However, the mobile space presents a number of key challenges, many of which go beyond issues with device characteristics such as screen-size and input capabilities. In particular,… (More)
Recommending news stories to users, based on their preferences, has long been a favourite domain for recommender systems research. In this paper, we describe a novel approach to news recommendation that harnesses real-time micro-blogging activity, from a service such as Twitter, as the basis for promoting news stories from a user's favourite RSS feeds. A… (More)
Search engines continue to struggle with the challenges presented by Web search: vague queries, impatient users and an enormous and rapidly expanding collection of unmo-derated, heterogeneous documents all make for an extremely hostile search environment. In this paper we argue that conventional approaches to Web search – those that adopt a traditional ,… (More)