Today's Internet search engines help users locate information based on the textual similarity of a query and potential documents. Given the large number of documents available, the user often finds too many documents, and even if the textual similarity is high, in many cases the matching documents are not relevant or of interest. Our goal is to explore other ways to decide if documents are "of ...

Intelligent software assistants are becoming more common in the e-commerce domain. We are working on a personal travel assistant. The goal of this application is to use case based reasoning to assist the user in arranging flights. It offers personalised service to its users and automatically learns their travel preferences. It stores these preferences in a user model that is directly related to...

Recommending new items for suitable users is an important yet challenging problem due to the lack of preference history for the new items. Non-collaborative user modeling techniques that rely on the item features can be used to recommend new items. However, they only use the past preferences of each user to provide recommendations for that user. They do not utilize information from the past pre...

In this paper we describe a novel approach to case-based product recommendation. It is novel because it does not leverage the usual static, feature-based, purely similarity-driven approaches of traditional case-based recommenders. Instead we harness experiential cases, which are automatically mined from user generated reviews, and we use these as the basis for a form of recommendation that emph...

Fuzzy similarity measure is very useful in fuzzy information retrieval. This study presents a new method based on fuzzy-number similarity measure to deal with fuzzy information retrieval problems. The proposed method can obtain the suitable retrieval results for the user because it translate the degree of satisfaction F~ into a linguistic term, and user can easily determine whether the retrieve...

Two key elements in the area of cognitive ergonomics are user-system performance and the user similarity. However, with the introduction of skinnable user interfaces, a technology that gives the user interface a chameleon-like ability, elements such as aesthetic, fun, and especially user individuality and identity become more important. This paper presents two explorative studies on user person...

In this article, we present an object tracking system which allows interactive user feedback to improve the accuracy of the tracking process in real-time video. In addition, we describe the hybrid maximum likelihood similarity, which integrates traditional metrics with the maximum likelihood estimated metric. The hybrid similarity measure is used to improve the dynamic relevance feedback proces...

• based on Ch. 9 in Rajaraman and Ullman: Mining Massive Data Sets. • CF – major alternative to content-based approach to RS. • more popular, because ... • assumes no meta-data or “features” on items or users available; nor requires any features to be easily extractable. • Idea: Treat the column of each item as a representation of the item; how is it liked by various users. • Similarly, the pro...

Similarity has highly application dependent and even subjective characteristics. Similarity models therefore have to be adaptable to application specific requirements and individual user preferences. We focus on two aspects of adaptable similarity search: (1) Adaptable Similarity Models. Examples include pixelbased shape similarity as well as 2D and 3D shape histograms, applied to biomolecular ...

In this paper, we present a Web recommender system for recommending, predicting and personalizing music playlists based on a user model. We have developed a hybrid similarity matching method that combines collaborative filtering with ontology-based semantic distance measurements. We dynamically generate a personalized music playlist, from a selection of recommended playlists, which comprises th...