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We address user system interaction issues in product search and recommender systems: how to help users select the most preferential item from a large collection of alternatives. As such systems must crucially rely on an accurate and complete model of user ...
The internet provides an unprecedented variety of opportunities to people. Whether looking for a place to go on vacation, an apartment to rent, or a PC to buy, the potential customer is faced with countless possibilities. Most people have difficulty findin ...
Nowadays more and more people are looking for products online, and a massive amount of products are being sold through e-commerce systems. It is crucial to develop effective online product search tools to assist users to find their desired products and to ...
We consider example-critiquing systems that help people search for their most preferred item in a large catalog. We compare 6 existing approaches in terms of user or system-centric, implicit or explicit use of preferences, assumptions used and their behavi ...
In a service-oriented e-commerce environment, it is a crucial task to help consumers choose desired products efficiently from a huge amount of dynamically configured product candidates. Decision agents can be designed to provide interactive decision aids f ...
We consider interactive tools that help users search for their most preferred item in a large collection of options. In particular, we examine example-critiquing, a technique for enabling users to incrementally construct preference models by critiquing exa ...
As people increasingly rely on interactive decision support systems to choose products and make decisions, building effective interfaces for these systems becomes more and more challenging due to the explosion of on-line information, the initial incomplete ...
The world today is full of information systems which make huge quantities of information available. This incredible amount of information is clearly overwhelming Internet endusers. As a consequence, intelligent tools to identify worthwhile information are ...
Critiquing techniques provide an easy way for users to feedback their preferences over one or several attributes of the products in a conversational recommender system. While unit critiques only allow users to critique one attribute of the products each ti ...
To make accurate recommendations, recommendation systems currently require more data about a customer than is usually available. We conjecture that the weaknesses are due to a lack of inductive bias in the learning methods used to build the prediction mode ...
